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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 955 records · Page 53
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Compositional Variation Tests on DuraMelter 100 with LAW Sub-Envelope B1 Feed in Support of the LAW Pilot Melter, VSL-02R62N0-5, Rev. 0 (May 2003)

The principal objective of the DM100 tests was to demonstrate the robustness of the vitrification process with respect to feed and glass compositional changes resulting from variations in the simulant-to-additive ratio. The DM100-WV unit was selected for these tests; this melter was used for all of the Part B 1 tests on LAW Envelopes A, B, and C sulfate incorporation that were used to support the subsequent tests on the Pilot Melter as well as for the more recent LAW Sub-Envelope Al, A2, A3 and Cl tests. The same melter was selected for the present tests in order to maintain comparisons between the data sets. In addition, the somewhat smaller glass volume for the same melt surface area as compared to the DM100-BL melter means that more glass turnovers are achieved for a given test duration. The DM100 tests used nominal feed and feed with a 15% surplus in waste simulant. Previous Pilot Melter tests on Envelope A with 10% variations (but with sulfate removal) showed significant impacts on glass production rates that were ultimately corrected by adjustments in the sugar additions. Consequently, robustness with respect to throughput as well as sulfate tolerance are important motivations for these tests.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Rapid Optimization of Total Variation with Applications in Imaging, Additive Manufacturing, and Qualification

Total Variation optimization penalizes the gradient of a control variable or state. While this work focuses on image processing in particular, it has also found applications in inverse problems and topology optimization. In image processing, the goal is to maintain faithfulness to the original image while denoising and/or deblurring. Additionally, bilevel optimization over the spatially varying regularization weights can illuminate interfaces such as damage regions and other anomalies. We will address two fundamental challenges with TV-optimization: (i) the typical slow convergence of existing TV-optimization methods, and (ii) the selection of spatially varying TV parameters to promote interface detection. Additionally, we will apply such techniques to image data collected in additive manufacturing. In said context, stochasticity in build events induces flaws in the manufactured piece, compromising the integrity of said part. There is a critical need for in-situ monitoring to spot anomalies once they form, and in this setting we apply our total variation and hyperparameter solvers. We will develop a customized algorithm based on for extreme-scale TV-optimization that achieves super-linear or quadratic-convergence, a critical property for real-time, image-by-image analysis. A worst-case outcome is a preprocessing step that enhances image quality in-situ, specifically for out-of-focus and noisy images.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Effects of SRPPF ARS Effluent Variations on Magnesium Oxysulfate Solidification

A magnesium oxysulfate (MOS) grout formulation has been identified to solidify the liquid effluent from the Savannah River Plutonium Processing Facility (SRPPF) Aqueous Recovery System (ARS). The formulation uses reactive, light burnt MgO (28 wt%), anhydrous MgSO 4 (10 wt%), and dead burnt MgO (62 wt%), resulting in a grout with good mixability, acceptable density, acceptable setting times, and a leachate pH around 9.4, within the assumed Waste Isolation Pilot Plant (WIPP) brine pH range. A series of tests were then designed to observe how this formula reacted to variations in the liquid effluent. Liquid effluent temperature, the caustic pH level, concentration of NaNO 3 , and the presence of neutralization products, trace metals, and/or sodium sulfate (all potential residuals found in the effluent from upstream processing), were evaluated to see how each impacts the grout mixing time, peak temperature, setting time, presence of bleed water, leachate pH, and density. The standard mix has an average mixing time of 18 minutes, peak temperature of 100.5 °C, and set time of 60 minutes. Increasing the temperature of the liquid effluent increased the reaction rate of the mix and reduced mixing and setting times. Between 30 and 40°C the change was relatively small, raising no more than 6 °C compared to the standard mix maximum temperature. Increasing the pH of the liquid effluent had no significant impact on the mix. The addition of neutralization products and trace metals had an overall impact of decreasing the reactivity of the mix. The addition of more ions in the liquid effluent, such as an increase in the concentration of NaNO 3 and the addition of Na 2 SO 4 , generally decreased the reactivity of the mix. None of the variations to the liquid effluent hindered solidification as indicated by the lack of bleed water found on all the samples. The leachate pH values for all mixes tested did not significantly vary from the expected pH of 9.4 and none of the density values fell below 1.8 g/cm 3 . Overall, changes to the liquid effluent were found to have a minimal impact on the formulation suggesting the grout's ability to properly form despite increased temperatures and the presence of residuals typically found in the liquid effluent from the ARS.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2026

VRN3P: Variational Recurrent Neural Network Based Net-Load Prediction under High Solar Penetration

This is the final technical report for the SETO-funded VRN3P project (PNNL# 76914). The goal of this project, led by Pacific Northwest National Laboratory (PNNL), in collaboration with Lawrence Livermore National Laboratory (LLNL) and Portland General Electric (PGE), was to develop and validate a deep variational recurrent neural network-based net-load prediction (VRN3P) framework for probabilistic time-series forecasting of day-ahead net-load under high solar penetration scenarios. The project team reports successful design of a novel probabilistic net-load forecasting architecture, comprising of a variational autoencoder and a recurrent neural network, which demonstrates 30% improvement in forecast performance, 60% improvement in training time, and consumes 44% less memory, when compared with conventional baseline models. The team tested the VRN3P model performance on GridLAB-D test-cases representing varying BTM solar penetration levels of 20%, 30%, and 50%, with integrated time-series net-load profiles provided by the utility partner (PGE). The VRN3P model demonstrate <2% hourly MAPE (averaged over the year) for day- ahead net-load forecast on the test scenario with 20% BTM solar. Transfer learning extension of the VRN3P model has demonstrated 8.33× speed-up in training, while still achieving acceptable forecast performance of 2.24% hourly MAPE on the 30% BTM solar penetration test-scenario. A preliminary version of the VRN3P GridAPPS-D™has been developed, along with a web-based interactive user-interface (named ‘Forte’) which has made available on GitHub for public use.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Variational Quantum Linear Solver

Previously proposed quantum algorithms for solving linear systems of equations cannot be implemented in the near term due to the re quired circuit depth. Here, we propose a hybrid quantum-classical algorithm, called Variational Quantum Linear Solver (VQLS), for solving linear systems on near-term quantum computers. VQLS seeks to variationally prepare |x$\rangle$ such that A|x$\rangle$ ∝ |b$\rangle$. We derive an operationally meaningful termination condition for VQLS that allows one to guarantee that a desired solution precision ϵ is achieved. Specifically, we prove that C $&GreaterSlantEqual;$ ϵ 2 /κ 2 , where C is the VQLS cost function and κ is the condition number of A. We present efficient quantum circuits to estimate C, while providing evidence for the classical hardness of its estimation. Using Rigetti’s quantum computer, we success fully implement VQLS up to a problem size of 1024 × 1024. Finally, we numerically solve nontrivial problems of size up to 2 50 × 2 50 . For the specific examples that we consider, we heuristically find that the time complexity of VQLS scales efficiently in ϵ, κ, and the system size N.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Benchmarking Adaptive Variational Quantum Eigensolvers

By design, the variational quantum eigensolver (VQE) strives to recover the lowest-energy eigenvalue of a given Hamiltonian by preparing quantum states guided by the variational principle. In practice, the prepared quantum state is indirectly assessed by the value of the associated energy. Novel adaptive derivative-assembled pseudo-trotter (ADAPT) ansatz approaches and recent formal advances now establish a clear connection between the theory of quantum chemistry and the quantum state ansatz used to solve the electronic structure problem. Here we benchmark the accuracy of VQE and ADAPT-VQE to calculate the electronic ground states and potential energy curves for a few selected diatomic molecules, namely H 2 , NaH, and KH. Using numerical simulation, we find both methods provide good estimates of the energy and ground state, but only ADAPT-VQE proves to be robust to particularities in optimization methods. Another relevant finding is that gradient-based optimization is overall more economical and delivers superior performance than analogous simulations carried out with gradient-free optimizers. The results also identify small errors in the prepared state fidelity which show an increasing trend with molecular size.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Stover composition in maize and sorghum reveals remarkable genetic variation and plasticity for carbohydrate accumulation

Carbohydrates stored in vegetative organs, particularly stems, of grasses are a very important source of energy. We examined carbohydrate accumulation in adult sorghum and maize hybrids with distinct phenology and different end uses (grain, silage, sucrose or sweetness in stalk juice, and biomass). Remarkable variation was observed for nonstructural carbohydrates and structural polysaccharides during three key developmental stages both between and within hybrids developed for distinct end use in both species. At the onset of the reproductive phase (average 65 days after planting, DAP), a wide range for accumulation of non-structural carbohydrates (free glucose and sucrose combined), was observed in internodes of maize (11-24%) and sorghum (7-36%) indicating substantial variation for transient storage of excess photosynthate during periods of low grain or vegetative sink strength. Remobilization of these reserves for supporting grain fill or vegetative growth was evident from lower amounts in maize (8-19%) and sorghum (9-27%) near the end of the reproductive period (average 95 DAP). At physiological maturity of grain hybrids (average 120 DAP), amounts of these carbohydrates were generally unchanged in maize (9-21%) and sorghum (16-27%) suggesting a loss of photosynthetic assimilation due to weakening sink demand. Nonetheless, high amounts of non-structural carbohydrates at maturity even in grain maize and sorghum (15-18%) highlight the potential for developing dual-purpose (grain/stover) crops. For both species, the amounts of structural polysaccharides in the cell wall, measured as monomeric components (glucose and pentose), decreased during grain fill but remained unchanged thereafter with maize biomass possessing slightly higher amounts than sorghum. In conclusion, availability of carbohydrates in maize and sorghum highlights the potential for developing energy-rich dedicated biofuel or dual-purpose (grain/stover) crops.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Analysis of the Aeroelastic Dynamics of Lightweight Flexible Variations of the SNL-NRT Turbine

Current trends show that wind turbines are growing in size to meet a rising demand for renewable energy generation, and their upscaled rotors have inherently become more flexible to maintain a proportionally lighter design. This is because larger rotors must be less massive relative to their diameter to minimize the levelized cost of energy (LCOE), which means that blades that are notably less stiff are produced as a result. These structural changes to blades are often reflected in their compromised aeroelastic stability and amplified deformation during operation, which has the potential to decrease the blade’s expected lifetime and the performance of the machine overall. Variations in blade flexibility are also known to influence vortex-wake structures downstream of the turbine, causing patterns of velocity deficit to evolve in ways that affect the performance of other turbines in the farm. This research explores how the increased flexibility of modern utility-scale wind turbine blades influences rotor aeroelastic behavior and interactions with farm flow. High-fidelity simulations of Sandia National Laboratories’ (SNL) National Rotor Testbed (NRT) wind turbine are presented. Flexible variations of the NRT baseline blade are simulated in a variety of realistic operational conditions typically expected at the SNL’s SWiFT facility in Lubbock, Texas. Solutions are then compared to investigate how specific changes to the structural properties of the NRT baseline blade’s design and construction can influence its aeroelastic response at the rotor and the evolution of the turbine’s wake.

Farrell, Alayna (ORCID:000000023555720X)↗
DOE OSTI2020

Evaluation of the Four-Dimensional Ensemble-Variational Hybrid Data Assimilation with Self-Consistent Regional Background Error Covariance for Improved Hurricane Intensity Forecasts

The feasibility of a hurricane initialization framework based on the Gridpoint Statistical Interpolation (GSI)-based four-dimensional ensemble-variational (GSI-4DEnVar) hybrid data assimilation system for the Hurricane Weather Research and Forecasting model (HWRF) model is evaluated in this study. The system considers the temporal evolution of error covariances via the use of four-dimensional ensemble perturbations that are provided by high-resolution, self-consistent HWRF ensemble forecasts. It is different from the configuration of the GSI-based three-dimensional ensemble-variational (GSI-3DEnVar) hybrid data assimilation system, similar to that used in the operational HWRF, which employs background error covariances provided by coarser-resolution global ensembles from the National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS) ensemble Kalman filtering data assimilation system. In addition, our proposed initialization framework discards the empirical intensity correction in the vortex initialization package that is employed by the GSI-3DEnVar initialization framework in operational HWRF. Data assimilation and numerical simulation experiments for Hurricanes Joaquin (2015), Patricia (2015), and Matthew (2016) are conducted during their intensity changes. The impacts of two initialization frameworks on the HWRF analyses and forecasts are compared. It is found that GSI-4DEnVar leads to a reduction in track, minimum sea level pressure (MSLP), and maximum surface wind (MSW) forecast errors in all of the HWRF simulations, compared with the GSI-3DEnVar initialization framework. With assimilating high-resolution observations within the hurricane inner-core region, GSI-4DEnVar can produce the initial hurricane intensity reasonably well without the empirical vortex intensity correction. Further diagnoses with Hurricane Joaquin indicate that GSI-4DEnVar can significantly alleviate the imbalances in the initial conditions and enhance the performance of the data assimilation and subsequent hurricane intensity and precipitation forecasts

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Genomic Analysis of the Natural Variation of Fatty Acid Composition in Seed Oils of Camelina sativa

Camelina sativa is an oilseed crop that has shown strong promise as a biofuel feedstock. The profile of fatty acids greatly influences the oil quality; however, genetic mechanisms that determine the natural variation of fatty acid composition in camelina are not fully understood. A genome wide association study (GWAS) was performed to uncover genetic loci that may contribute to the contents of major fatty acids such as oleic and linolenic acids in camelina seed. Two approaches were taken to improve the GWAS efficiency. First, growing a diversity panel of 212 accessions in four locations and two nitrogen fertilization conditions revealed great variation in fatty acid contents in seeds. Second, using an improved reference genome, abundant markers, including 203,320 single nucleotide polymorphisms (SNPs) and 99,067 insertions/deletions (indels), were developed, which refined the population structure of the diversity panel. GWAS resulted in 118 genetic markers across 31 trait/treatment conditions. Closely linked markers were determined based on linkage decay and by comparing secondarily associated markers when highly associated ones were removed. Candidate genes were examined by comparing the pangenomes of 12 high-quality reference genomes. This study provides new resources to understand seed lipid metabolism and improve camelina oils through molecular breeding.

Life Sciences & Biomedicine - Other Topics↗
DOE OSTI2023

Dimensionality Reduction with Variational Encoders Based on Subsystem Purification

Efficient methods for encoding and compression are likely to pave the way toward the problem of efficient trainability on higher-dimensional Hilbert spaces, overcoming issues of barren plateaus. Here, we propose an alternative approach to variational autoencoders to reduce the dimensionality of states represented in higher dimensional Hilbert spaces. To this end, we build a variational algorithm-based autoencoder circuit that takes as input a dataset and optimizes the parameters of a Parameterized Quantum Circuit (PQC) ansatz to produce an output state that can be represented as a tensor product of two subsystems by minimizing $Tr(ρ^2)$. The output of this circuit is passed through a series of controlled swap gates and measurements to output a state with half the number of qubits while retaining the features of the starting state in the same spirit as any dimension-reduction technique used in classical algorithms. The output obtained is used for supervised learning to guarantee the working of the encoding procedure thus developed. We make use of the Bars and Stripes (BAS) dataset for an 8 × 8 grid to create efficient encoding states and report a classification accuracy of 95% on the same. Thus, the demonstrated example provides proof for the working of the method in reducing states represented in large Hilbert spaces while maintaining the features required for any further machine learning algorithm that follows.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Crystal Chemistry and Structural Variations for Zircon Samples from Various Localities

This study investigates the variations of structural parameters and chemistry of a partially metamict and seven detrital zircon samples from different localities using single-crystal X-ray diffraction, synchrotron high-resolution powder X-ray diffraction, and electron-probe micro-analysis techniques. The unit-cell parameters for the eight zircon samples vary linearly with increasing unit-cell volume, V. A zircon sample from the Canadian Arctic Islands has the smallest unit-cell parameters, bond distances, ideal stoichiometric composition, unaffected by α-radiation damage, and is chemically pure. A zircon sample from Jemaa, Nigeria has the largest unit-cell parameters because of the effect of α-radiation doses received over a long time (2384 Ma). All the samples show good correlations between Zr and Si apfu (atom per formula unit) versus unit-cell volume, V. The α-radiation doses in the samples are lower than ~3.5 × 1015 α-decay events/mg. Substitutions of other cations at the Zr and Si sites control the variations of the structural parameters. Relatively large unit-cell parameters and bond distances occur because the Zr site accommodates other cations that have larger ionic radii than the Zr atom. Geological age increases the radiation doses in zircon and it is related to V.

58 GEOSCIENCES↗
DOE OSTI2024

Comprehensive Genome-Wide Natural Variation and Expression Analysis of Tubby-like Proteins Gene Family in Brachypodium distachyon

The Tubby-like proteins (TLPs) gene family is a group of transcription factors found in both animals and plants. In this study, we identified twelve B. distachyon TLPs, divided into six groups based on conserved domains and evolutionary relationships. We predicted cis-regulatory elements involved in light, hormone, and biotic and abiotic stresses. The expression patterns in response to light and hormones revealed that BdTLP3, 4, 7, and 14 are involved in light responses, and BdTLP1 is involved in ABA responses. Furthermore, BdTLP2, 7, 9, and 13 are expressed throughout vegetative and reproductive stages, whereas BdTLP1, 3, 5, and 14 are expressed at germinating grains and early vegetative development, and BdTLP4, 6, 8, and 10 are expressed at the early reproduction stage. The natural variation in the eleven most diverged B. distachyon lines revealed high conservation levels of BdTLP1-6 to high variation in BdTLP7-14 proteins. Based on diversifying selection, we identified amino acids in BdTLP1, 3, 8, and 13, potentially substantially affecting protein functions. This analysis provided valuable information for further functional studies to understand the regulation, pathways involved, and mechanism of BdTLPs.

Plant Sciences↗
DOE OSTI2023

Efficient Application of the Factorized form of the Unitary Coupled-Cluster Ansatz for the Variational Quantum Eigensolver Algorithm by Using Linear Combination of Unitaries

The variational quantum eigensolver is one of the most promising algorithms for near-term quantum computers. It has the potential to solve quantum chemistry problems involving strongly correlated electrons with relatively low-depth circuits, which are otherwise difficult to solve on classical computers. The variational eigenstate is constructed from a number of factorized unitary coupled-cluster terms applied onto an initial (single-reference) state. Current algorithms for applying one of these operators to a quantum state require a number of operations that scale exponentially with the rank of the operator. We exploit a hidden SU(2) symmetry to allow us to employ the linear combination of unitaries approach, Our Prepare subroutine uses n+2 ancilla qubits for a rank-n operator. Our Select (U) scheme uses O(n) Cnot gates. This results in a full algorithm that scales like the cube of the rank of the operator n 3 , a significant reduction in complexity for rank five or higher operators. This approach, when combined with other algorithms for lower-rank operators (when compared to the standard implementation), will make the factorized form of the unitary coupled-cluster approach much more efficient to implement on all types of quantum computers.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

A perturbative analysis of synchrotron spectral index variation over the microwave sky

In this paper, we implement a perturbative approach, first proposed by Bouchet and Gispert, to estimate the variation of the spectral index of galactic polarized synchrotron emission, using a linear combination of simulated Stokes Q polarization maps of selected frequency bands from WMAP and Planck observations on a region of sky dominated by the synchrotron Stokes Q signal. We find that a first order perturbative analysis recovers the input spectral index map well. Along with the spectral index variation map, our method provides a fixed reference index, β-hat {sub 0s}, over the sky portion being analyzed. Using Monte-Carlo simulations, we find that 〈 β-hat {sub 0s}〉=−2.84±0.01, which matches very closely with the position of a peak at β{sub s}(p)=−2.85 of the empirical probability density function of input synchrotron indices obtained from the same sky region. For thermal dust, the mean recovered spectral index 〈 β-hat {sub d}〉=2.00±0.004 from simulations, matches very well with the spatially fixed input thermal dust spectral index β{sub d}=2.00. As accompanying results of the method, we reconstruct cosmic microwave background, thermal dust, and a synchrotron template components with fixed spectral indices over the entire sky region. We use, in our analysis, full pixel–pixel noise covariance matrices of all frequency bands, estimated from the sky region being analyzed. The perturbative technique of this work (1) can build a model with an arbitrary but sufficient degree of accuracy (and precession) as allowed by the data and (2) can produce maximum likelihood estimators for reference indices and templates asymptotically.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

VELOCITY VARIATIONS IN THE PHOENIX–HERMUS STAR STREAM

Measurements of velocity and density perturbations along stellar streams in the Milky Way provide a time-integrated measure of dark matter substructure at larger galactic radius than the complementary instantaneous inner-halo strong lensing detection of dark matter sub-halos in distant galaxies. An interesting case to consider is the proposed Phoenix–Hermus star stream, which is long, thin, and on a nearly circular orbit, making it a particular good target to study for velocity variations along its length. In the presence of dark matter sub-halos, the stream velocities are significantly perturbed in a manner that is readily understood with the impulse approximation. A set of simulations shows that only sub-halos above a few 10{sup 7} M {sub ⊙} lead to reasonably long-lived observationally detectable velocity variations of amplitude of order 1 km s{sup −1}, with an average of about one visible hit per (two-armed) stream over a 3 Gyr interval. An implication is that globular clusters themselves will not have a visible impact on the stream. Radial velocities have the benefit of being completely insensitive to distance errors. Distance errors scatter individual star velocities perpendicular and tangential to the mean orbit, but their mean values remain unbiased. Calculations like these help build the quantitative case to acquire large, fairly deep, precision velocity samples of stream stars.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

DETECTION OF ROTATIONAL SPECTRAL VARIATION ON THE M-TYPE ASTEROID (16) PSYCHE

The asteroid (16) Psyche is of scientific interest because it contains ∼1% of the total mass of the asteroid belt and is thought to be the remnant metallic core of a protoplanet. Radar observations have indicated the significant presence of metal on the surface with a small percentage of silicates. Prior ground-based observations showed rotational variations in the near-infrared (NIR) spectra and radar albedo of this asteroid. However, no comprehensive study that combines multi-wavelength data has been conducted so far. Here we present rotationally resolved NIR spectra (0.7–2.5 μ m) of (16) Psyche obtained with the NASA Infrared Telescope Facility. These data have been combined with shape models of the asteroid for each rotation phase. Spectral band parameters extracted from the NIR spectra show that the pyroxene band center varies from ∼0.92 to 0.94 μ m. Band center values were used to calculate the pyroxene chemistry of the asteroid, whose average value was found to be Fs{sub 30}En{sub 65}Wo{sub 5}. Variations in the band depth (BD) were also observed, with values ranging from 1.0% to 1.5%. Using a new laboratory spectral calibration method, we estimated an average orthopyroxene content of 6% ± 1%. The mass-deficit region of Psyche, which exhibits the highest radar albedo, also shows the highest value for the spectral slope and the minimum BD. The spectral characteristics of Psyche suggest that its parent body did not have the typical structure expected for a differentiated body or that the sequence of events that led to its current state was more complex than previously thought.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Obliquity Variations of Habitable Zone Planets Kepler-62f and Kepler-186f

Obliquity variability could play an important role in the climate and habitability of a planet. Orbital modulations caused by planetary companions and the planet’s spin axis precession due to the torque from the host star may lead to resonant interactions and cause large-amplitude obliquity variability. Here we consider the spin axis dynamics of Kepler-62f and Kepler-186f, both of which reside in the habitable zone around their host stars. Using N-body simulations and secular numerical integrations, we describe their obliquity evolution for particular realizations of the planetary systems. We then use a generalized analytic framework to characterize regions in parameter space where the obliquity is variable with large amplitude. We find that the locations of variability are fine-tuned over the planetary properties and system architecture in the lower-obliquity regimes (≲40°). As an example, assuming a rotation period of 24 hr, the obliquities of both Kepler-62f and Kepler-186f are stable below ∼40°, whereas the high-obliquity regions (60°–90°) allow moderate variabilities. However, for some other rotation periods of Kepler-62f or Kepler-186f, the lower-obliquity regions could become more variable owing to resonant interactions. Even small deviations from coplanarity (e.g., mutual inclinations ∼3°) could stir peak-to-peak obliquity variations up to ∼20°. Undetected planetary companions and/or the existence of a satellite could also destabilize the low-obliquity regions. In all cases, the high-obliquity region allows for moderate variations, and all obliquities corresponding to retrograde motion (i.e., >90°) are stable.

79 ASTRONOMY AND ASTROPHYSICS↗