Search NASA⌕ Search

SEARCH · Search NASA

Results for “STRATIFICATION”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 847 records · Page 47
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

SPRUCE Deep Peat Microbial Diversity, CO2 and CH4 Production in Response to Nutrient, Temperature, and pH Treatments during Incubation Studies

This dataset contains the results of a microcosm incubation study on deep peat collected from the Spruce and Peatland Responses Under Changing Environments (SPRUCE) experimental site within the Marcell Experimental Forest in northern Minnesota, USA in September 2014. Microcosms were monitored for carbon dioxide (CO2) and methane (CH4) production, and microbial community dynamics were assessed using quantitative polymerase chain reaction (qPCR) and amplicon sequencing. The experiment was designed with a full factorial design with elevated temperature, nitrogen (N), (P), and pH treatments was used with samples from each transect serving replicates. In all, 96 microcosms were constructed to account for the 16 treatment combinations (Nitrogen x Phosphorous x pH x temperature), 2 time points, and 3 replicates. Temperature treatments were 6 degrees C, to mimic the SPRUCE ambient plot temperatures, and 15 degrees C to mimic the SPRUCE +9 degrees C treatment. These data show that one year of deep peat warming, microbial community structure and abundance of bacterial, archaeal, fungal, and methanogenic populations showed strong vertical stratification across the peat depth profile yet no clear response to the temperature treatments (Kluber et al, 2020). In an effort to identify factors that may be limiting decomposition and microbial community change in deep peat, we conducted an anerobic microcosm incubation of deep peat (150-200 cm depth). This dataset contains one data file in comma-separate values (*.csv) format. Additional metadata are provided: a data dictionary and a file-level metadata file in comma-separate values (.csv) format and a user guide in PDF (*.pdf) format.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Low-Temperature Combustion of High Octane Fuels in a Gasoline Compression Ignition Engine

Gasoline Compression Ignition (GCI) has been shown as one of the advanced combustion concepts that could potentially provide a pathway to achieve cleaner and more efficient combustion engines. Fuel and air in GCI are not fully premixed as compared to homogeneous charge compression ignition (HCCI) which is a completely kinetic-controlled combustion system. Therefore, the combustion phasing can be controlled by the time of injection, usually post injection in a multiple-injection scheme, to mitigate combustion noise. Gasoline fuels ignite more difficult than Diesel. The autoignition quality of gasoline can be indicated by research octane number (RON). Fuels with high octane tend to have more resistance to auto-ignition, hence more time for fuel-air mixing. In this study, three fuels, namely, Aromatic, Alkylate, and E30, with similar RON value of 98 but different hydrocarbon compositions were tested in a multi-cylinder engine under GCI combustion mode. Considerations of EGR, start of injection (SOI), and boost were investigated to study the sensitivity of dilution, local stratification, and reactivity of the charge, respectively, for each fuel. Combustion phasing was kept constant during the experiments to the changes in ignition and combustion process before and after 50% of the fuel mass is burned. Emission characteristics at different levels of EGR and lambda were revealed for all fuels with E30 having the lowest filter smoke number (FSN) and was also most sensitive to the change in dilution. Reasonably low combustion noise (< 90 dB) and stable combustion (COVIMEP < 3%) were maintained during the experiments. The second part of this paper contains visualization of the combustion process obtained from endoscope imaging for each fuel at selected conditions. Soot radiation signal from GCI combustion were strong during late injection, and also more intense at low EGR conditions. Furthermore, soot/temperature profiles indicated only the high-temperature combustion period, while cylinder pressure-based heat release rate (HRR) showed a two-stage combustion phenomenon.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

From Mouse to Human: Cellular Morphometric Subtype Learned From Mouse Mammary Tumors Provides Prognostic Value in Human Breast Cancer

Mouse models of cancer provide a powerful tool for investigating all aspects of cancer biology. In this study, we used our recently developed machine learning approach to identify the cellular morphometric biomarkers (CMB) from digital images of hematoxylin and eosin (H&E) micrographs of orthotopic Trp53-null mammary tumors (n = 154) and to discover the corresponding cellular morphometric subtypes (CMS). Of the two CMS identified, CMS-2 was significantly associated with shorter survival (p = 0.0084). We then evaluated the learned CMB and corresponding CMS model in MMTV-Erbb2 transgenic mouse mammary tumors (n = 53) in which CMS-2 was significantly correlated with the presence of metastasis (p = 0.004). We next evaluated the mouse CMB and CMS model on The Cancer Genome Atlas breast cancer (TCGA-BRCA) cohort (n = 1017). Kaplan–Meier analysis showed significantly shorter overall survival (OS) of CMS-2 patients compared to CMS-1 patients (p = 0.024) and added significant prognostic value in multi-variable analysis of clinical and molecular factors, namely, age, pathological stage, and PAM50 molecular subtype. Thus, application of CMS to digital images of routine workflow H&E preparations can provide unbiased biological stratification to inform patient care.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

MetaboTools: A comprehensive toolbox for analysis of genome-scale metabolic models

Metabolomic data sets provide a direct read-out of cellular phenotypes and are increasingly generated to study biological questions. Previous work, by us and others, revealed the potential of analyzing extracellular metabolomic data in the context of the metabolic model using constraint-based modeling. With the MetaboTools, we make our methods available to the broader scientific community. The MetaboTools consist of a protocol, a toolbox, and tutorials of two use cases. The protocol describes, in a step-wise manner, the workflow of data integration, and computational analysis. The MetaboTools comprise the Matlab code required to complete the workflow described in the protocol. Tutorials explain the computational steps for integration of two different data sets and demonstrate a comprehensive set of methods for the computational analysis of metabolic models and stratification thereof into different phenotypes. The presented workflow supports integrative analysis of multiple omics data sets. Importantly, all analysis tools can be applied to metabolic models without performing the entire workflow. Taken together, the MetaboTools constitute a comprehensive guide to the intra-model analysis of extracellular metabolomic data from microbial, plant, or human cells. In conclusion, this computational modeling resource offers a broad set of computational analysis tools for a wide biomedical and non-biomedical research community.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Comparing the response of the indigenous microbial community to crude oil amendment in oxic versus hypoxic conditions

The Caspian Sea is the world’s largest landlocked saline lake which lies between Europe and Asia. This region is particularly known for its large-scale oil reserves, pipelines, and drilling activities, which have contributed to the environmental decline of this lake. In addition to pollution from the petroleum industry, drainage from various river basins brings an influx of residential, industrial, and agricultural effluents that induce eutrophication and hypoxic conditions in deeper, colder waters, creating an oxygen gradient. The temperature and oxygen stratification in this environment has presented a unique opportunity to investigate the potential of the biodegradative processes carried out by the indigenous microbial community. We believe these indigenous microbes possess different metabolic capabilities to degrade oil as they adapted to declining oxygen concentrations and temperatures with increasing depths over a prolonged period. Hence, community structure and composition will vary with depth. Microcosms were set up to observe the indigenous microbial reaction after a 60 ppm native crude oil amendment over 115 days. Surface water microcosms were incubated at 28ºC and aerated while deep water microcosms were incubated at 8ºC under anaerobic conditions. These two environmental conditions represent the temperature and oxygen extremes along the gradient and were selected as we try to simulate the indigenous community’s response to this oil contamination. DNA was extracted and amplified from these microcosms and sequenced. Bioinformatic analysis was performed to track changes in the abundance of taxa present and biodiversity over different time points to show the progression of community structure. All microcosms showed the presence of hydrocarbon-degrading phyla, whose presence is consistent with other reports from oil-enriched environments. However, distinct communities were observed in oxic versus hypoxic microcosms. Orders of Bacteria related to sulfate and nitrogen cycling were found in hypoxic microcosms, indicating a possible mechanism for the anaerobic biodegradation of crude oil. GC-MS analysis of initial and final microcosms also provided evidence of degradation of hydrocarbon fractions in both warm, oxic and cold, hypoxic conditions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

A Review of Offshore Methane Quantification Methodologies

Since pre-industrial times, anthropogenic methane emissions have increased and are partly responsible for a changing global climate. Natural gas and oil extraction activities are one significant source of anthropogenic methane. While methods have been developed and refined to quantify onshore methane emissions, the ability of methods to directly quantify emissions from offshore production facilities remains largely unknown. Here, we review recent studies that have directly measured emissions from offshore production facilities and critically evaluate the suitability of these measurement strategies for emission quantification in a marine environment. The average methane emissions from production platforms measured using downwind dispersion methods were 32 kg h−1 from 188 platforms; 118 kg h−1 from 104 platforms using mass balance methods; 284 kg h−1 from 151 platforms using aircraft remote sensing; and 19,088 kg h−1 from 10 platforms using satellite remote sensing. Upon review of the methods, we suggest the unusually large emissions, or zero emissions observed could be caused by the effects of a decoupling of the marine boundary layer (MBL). Decoupling can happen when the MBL becomes too deep or when there is cloud cover and results in a stratified MBL with air layers of different depths moving at different speeds. Decoupling could cause: some aircraft remote sensing observations to be biased high (lower wind speed at the height of the plume); the mass balance measurements to be biased high (narrow plume being extrapolated too far vertically) or low (transects miss the plume); and the downwind dispersion measurements much lower than the other methods or zero (plume lofting in a decoupled section of the boundary layer). To date, there has been little research on the marine boundary layer, and guidance on when decoupling happens is not currently available. We suggest an offshore controlled release program could provide a better understanding of these results by explaining how and when stratification happens in the MBL and how this affects quantification methodologies.

Riddick, Stuart N. (ORCID:0000000316841843)↗
DOE OSTI2022

The Thermal Response of a Packed Bed Thermal Energy Storage System upon Saturated Steam Injection Using Distributed Temperature Sensing

The effectiveness of a thermal energy storage (TES) system is typically characterized with the help of thermal stratification or temperature gradients along the direction of heat injection, which is typically the flow direction of heat transfer fluid. The steepness of temperature gradients are a direct indicator of the effectiveness or efficiency of the heat storage or dispatch process. The temperature gradient evolution along the packed bed of ceramic particles upon saturated steam injection is presented in this work. Distributed temperature sensing based on optical frequency domain reflectometry was deployed in a packed bed of ceramic particles to capture the thermal front evolution in the axial direction. The physical processes accompanying steam injection in packed beds are complex due to phase change, transitioning two-phase flow, and changes in condensate accumulation. Therefore, the variation of thermal response of the TES system for various steam injection flow rates was experimentally studied using a high-resolution distributed temperature sensing system in a chemically inert alumina particle-packed bed. Distinct zones of different heat transfer modes were observed during the steam injection experiments. A distinct conduction zone, evident from diffuse thermal fronts, was observed at low flow rates, and these thermal gradients became sharper as the flow rate increased. The diffuse thermal fronts in the heat storage media suggest a low exergy efficiency of the TES system, as energy losses started initiating before a significant fraction of the bed was saturated with steam.

25 ENERGY STORAGE↗
DOE OSTI2024

A Comparative Experimental Analysis of Natural Gas Dual Fuel Combustion Ignited by Diesel and Poly OxyMethylene Dimethyl Ether

Dual-fuel low-temperature combustion is a possible solution for alleviating the tradeoff between oxides of nitrogen and soot emissions in conventional diesel combustion, albeit with poor combustion stability, high carbon monoxide, and unburned hydrocarbon emissions at low engine loads. The present work compares emissions and combustion (heat release and other metrics) of both diesel and poly-oxy methylene dimethyl ether as high-reactivity fuels to ignite natural gas while leveraging spray-targeted reactivity stratification, which involved multiple injections of the high-reactivity fuels. The experiments included six parametric sweeps of: (1) start of first injection, (2) start of second injection, (3) percentage of energy substitution of natural gas, (4) commanded injection duration ratio, (5) rail pressure, and (6) intake pressure. The experiments were performed on a 1.8 L heavy-duty single-cylinder research engine operating at a medium speed of 1339 rev/min. Not-to-exceed limits for the indicated oxides of nitrogen emissions, maximum pressure rise rate, and the coefficient of variation of the indicated mean effective pressure were set to 1 g/kWh, 10 bar/CAD, and 10%, respectively. The indicated emissions decreased and combustion improved significantly for both fueling combinations when the experimental procedure was applied.

Partridge, Kendyl Ryan↗
DOE OSTI2023

Modeling of Liquid Hydrogen Tank Cooled with Para-Orthohydrogen Conversion

With the accelerating development of liquid-hydrogen storage facilities, the problem of boil-off hydrogen losses becomes very important. A promising method to reduce these losses is to utilize the endothermic para-orthohydrogen conversion of vented hydrogen, which can effectively decrease heat loads on a hydrogen tank. To model such a process, a hybrid computational model has been developed, based on the application of computational fluid dynamics for an ullage space, where knowledge of thermal stratification is important, and reduced-order models for other system elements. The simulation results for a spheroidal tank in selected conditions indicated a 10–25% reduction of boil-off losses due to cooling produced by vented hydrogen undergoing para-ortho-conversion.

08 HYDROGEN↗
DOE OSTI2022

Integrating Deep Learning and Hydrodynamic Modeling to Improve the Great Lakes Forecast

The Laurentian Great Lakes, one of the world’s largest surface freshwater systems, pose a modeling challenge in seasonal forecast and climate projection. While physics-based hydrodynamic modeling is a fundamental approach, improving the forecast accuracy remains critical. In recent years, machine learning (ML) has quickly emerged in geoscience applications, but its application to the Great Lakes hydrodynamic prediction is still in its early stages. This work is the first one to explore a deep learning approach to predicting spatiotemporal distributions of the lake surface temperature (LST) in the Great Lakes. Our study shows that the Long Short-Term Memory (LSTM) neural network, trained with the limited data from hypothetical monitoring networks, can provide consistent and robust performance. The LSTM prediction captured the LST spatiotemporal variabilities across the five Great Lakes well, suggesting an effective and efficient way for monitoring network design in assisting the ML-based forecast. Furthermore, we employed an explainable artificial intelligence (XAI) technique named SHapley Additive exPlanations (SHAP) to uncover how the features impact the LSTM prediction. Our XAI analysis shows air temperature is the most influential feature for predicting LST in the trained LSTM. The relatively large bias in the LSTM prediction during the spring and fall was associated with substantial heterogeneity of air temperature during the two seasons. In contrast, the physics-based hydrodynamic model performed better in spring and fall yet exhibited relatively large biases during the summer stratification period. Finally, we developed a statistical integration of the hydrodynamic modeling and deep learning results based on the Best Linear Unbiased Estimator (BLUE). The integration further enhanced prediction accuracy, suggesting its potential for next-generation Great Lakes forecast systems.

Xue, Pengfei (ORCID:000000025702421X)↗
DOE OSTI2025

Realistic Noise Generation to Enhance Realism of Virtual Lidar Scans

Many real-world phenomena corrupt light detection and ranging (lidar) measurements, such as laser energy attenuation, variations in aerosol concentration and composition with height, and hard target returns. Accurate studies of lidar scans using virtual lidar methods should include some realistic model of these corrupting effects to generate more realistic simulations of lidar scans. We present a simple model that characterizes noise caused by energy attenuation and aerosol stratification. The model requires limited inputs and is developed for a Halo Photonics Streamline XR lidar but is readily generalizable for other lidar systems. A critical component of this model is a model of the standard deviation of measured wind speed as a function of the backscattered signal’s signal-to-noise ratio. We derive a general model for this behavior that can be adapted to different scan settings.

17 WIND ENERGY↗
DOE OSTI2016

Mapping Arctic plant functional type distributions in the Barrow Environmental Observatory using WorldView-2 and LiDAR datasets

Multi-scale modeling of Arctic tundra vegetation requires characterization of the heterogeneous tundra landscape, which includes representation of distinct plant functional types (PFTs). We combined high-resolution multi-spectral remote sensing imagery from the WorldView-2 satellite with light detecting and ranging (LiDAR)-derived digital elevation models (DEM) to characterize the tundra landscape in and around the Barrow Environmental Observatory (BEO), a 3021-hectare research reserve located at the northern edge of the Alaskan Arctic Coastal Plain. Vegetation surveys were conducted during the growing season (June August) of 2012 from 48 1 m 1 m plots in the study region for estimating the percent cover of PFTs (i.e., sedges, grasses, forbs, shrubs, lichens and mosses). Statistical relationships were developed between spectral and topographic remote sensing characteristics and PFT fractions at the vegetation plots from field surveys. These derived relationships were employed to statistically upscale PFT fractions for our study region of 586 hectares at 0.25-m resolution around the sampling areas within the BEO, which was bounded by the LiDAR footprint. We employed an unsupervised clustering for stratification of this polygonal tundra landscape and used the clusters for segregating the field data for our upscaling algorithm over our study region, which was an inverse distance weighted (IDW) interpolation. We describe two versions of PFT distribution maps upscaled by IDW from WorldView-2 imagery and LiDAR: (1) a version computed from a single image in the middle of the growing season; and (2) a version computed from multiple images through the growing season. This approach allowed us to quantify the value of phenology for improving PFT distribution estimates. We also evaluated the representativeness of the field surveys by measuring the Euclidean distance between every pixel. This guided the ground-truthing campaign in late July of 2014 for addressing uncertainty based on representativeness analysis by selecting 24 1 m 1 m plots that were well and poorly represented. Ground-truthing indicated that including phenology had a better accuracy (R 2 =0.75, RMSE=9.94) than the single image upscaling (R 2 =0.63 , RMSE=12.05) predicted from IDW. We also updated our upscaling approach to include the 24 ground-truthing plots, and a second ground-truthing campaign in late August of 2014 indicated a better accuracy for the phenology model (R 2 =0.61 , RMSE=13.78 ) than only using the original 48 plots for the phenology model (R 2 =0.23 , RMSE=17.49). After all, we believe that the cluster-based IDW upscaling approach and the representativeness analysis offer new insights for upscaling high-resolution data in fragmented landscapes. This analysis and approach provides PFT maps needed to inform land surface models in Arctic ecosystems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

An evaluation of prognostic factors, oncologic outcomes, and management for primary and recurrent squamous cell carcinoma of the vulva

Objective: To evaluate prognostic factors, outcomes, and management patterns of patients treated for squamous cell carcinoma of the vulva. Methods: One hundred sixty-four women were retrospectively identified with primary squamous cell carcinoma of the vulva treated at our institution between 1/1996–12/2018. Descriptive statistics were performed on patient, tumor, and treatment characteristics. The χ 2 tests and t-tests were used to compare categorical variables and continuous variables, respectively. Recurrence free survival (RFS), overall survival (OS), and disease-specific survival (DSS) were analyzed with Kaplan-Meier estimates, the log-rank test, and Cox proportional hazards. Results: Median follow-up was 52.5 months. Five-year RFS was 67.9%, 60.0%, 42.1%, and 20.0% for stage I–IV, respectively. Five-year DSS was 86.2%, 81.6%, 65.0%, and 42.9% for stage I–IV, respectively. On multivariate analysis, positive margins predicted overall RFS (hazard ratio [HR]=3.55; 95% confidence interval [CI]=1.18–10.73; p=0.025), while presence of lichen sclerosus on pathology (HR=2.78; 95% CI=1.30–5.91; p=0.008) predicted local RFS. OS was predicted by nodal involvement (HR=2.51; 95% CI=1.02–6.13; p=0.043) and positive margins (HR=5.19; 95% CI=2.03–13.26; p=0.001). Adjuvant radiotherapy significantly improved RFS (p=0.016) and DSS (p=0.012) in node-positive patients. Median survival after treatment of local, groin, and pelvic/distant recurrence was 52, 8, and 5 months, respectively. Conclusion: For primary treatment, more conservative surgical approaches can be considered with escalation of treatment in patients with concurrent precursor lesions, positive margins, and/or nodal involvement. Further studies are warranted to improve risk stratification in order to optimize treatment paradigms for vulvar cancer patients.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Cluster Configuration Spaces of Finite Type

For each Dynkin diagram $D$, we define a ''cluster configuration space'' ${\mathcal{M}}_D$ and a partial compactification ${\widetilde {\mathcal{M}}}_D$. For $D = A_{n-3}$, we have ${\mathcal{M}}_{A_{n-3}} = {\mathcal{M}}_{0,n}$, the configuration space of $n$ points on ${\mathbb P}^1$, and the partial compactification ${\widetilde {\mathcal{M}}}_{A_{n-3}}$ was studied in this case by Brown. The space ${\widetilde {\mathcal{M}}}_D$ is a smooth affine algebraic variety with a stratification in bijection with the faces of the Chapoton-Fomin-Zelevinsky generalized associahedron. The regular functions on ${\widetilde {\mathcal{M}}}_D$ are generated by coordinates $u_\gamma$, in bijection with the cluster variables of type $D$, and the relations are described completely in terms of the compatibility degree function of the cluster algebra. As an application, we define and study cluster algebra analogues of tree-level open string amplitudes.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Supplement to “Torsional oscillations of a magnetar with a tangled magnetic field” (2016, ApJL, 823, L1)

We introduce a mean-field formalism with which to study the oscillations of a neutron star or other stellar object with a dipolar magnetic field plus a topologically distinct isotropic magnetic tangle that stabilizes the field configuration. In terms of the ratio of the energy density of the tangled field to that in the dipolar component b {sub t} {sup 2}, we obtain separable equations for the eigenfunctions and eigenfrequencies for a star of uniform density. We show that finite b {sub t} {sup 2} breaks the Alfvén continuum that is supported by the dipolar component of the field into discrete normal modes, and we quantify the splitting. Assuming the estimated dipole fields of 7×10{sup 14} G in SGR 1900+14 and 2×10{sup 15} G in SGR 1806–20, and tuning b {sub t} {sup 2} to match the lowest-frequency quasi-periodic oscillations observed to accompany flares in these objects, we infer b{sub t}{sup 2}=13.3 and 0.17, respectively. The predicted spectrum is about three times denser than that observed in SGR 1900+14, and much denser in SGR 1806–20. If the dipole field of SGR 1806–20 has been overestimated, the spectrum of normal modes will be less dense. We show that for b{sub t}{sup 2}≫1, as stability considerations suggest, the crust is nearly dynamically irrelevant. Moreover, density stratification generally shifts the eigenfrequencies up by about 20%, a change that can be mostly subsumed in a uniform density model with a slightly different choice of stellar radius or mass.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Far-infrared line spectra of active galaxies from the Herschel/PACS spectrometer: The complete database

We present a coherent database of spectroscopic observations of far-IR fine-structure lines from the Herschel/Photoconductor Array Camera and Spectrometer archive for a sample of 170 local active galactic nuclei (AGNs), plus a comparison sample of 20 starburst galaxies and 43 dwarf galaxies. Published Spitzer/IRS and Herschel/SPIRE line fluxes are included to extend our database to the full 10–600 μm spectral range. The observations are compared to a set of Cloudy photoionization models to estimate the above physical quantities through different diagnostic diagrams. We confirm the presence of a stratification of gas density in the emission regions of the galaxies, which increases with the ionization potential of the emission lines. The new [O iv]{sub 25.9μm}/[O iii]{sub 88μm} versus [Ne iii]{sub 15.6μm}/[Ne ii]{sub 12.8μm} diagram is proposed as the best diagnostic to separate (1) AGN activity from any kind of star formation and (2) low-metallicity dwarf galaxies from starburst galaxies. Current stellar atmosphere models fail to reproduce the observed [O iv]{sub 25.9μm}/[O iii]{sub 88μm} ratios, which are much higher when compared to the predicted values. Finally, the ([Ne iii]{sub 15.6μm} + [Ne ii]{sub 12.8μm})/([S iv]{sub 10.5μm} +[S iii]{sub 18.7μm}) ratio is proposed as a promising metallicity tracer to be used in obscured objects, where optical lines fail to accurately measure the metallicity. The diagnostic power of mid- to far-infrared spectroscopy shown here for local galaxies will be of crucial importance to study galaxy evolution during the dust-obscured phase at the peak of the star formation and black hole accretion activity (1<z<4). This study will be addressed by future deep spectroscopic surveys with present and forthcoming facilities such as the James Webb Space Telescope, the Atacama Large Millimeter/submillimeter Array, and the Space Infrared telescope for Cosmology and Astrophysics.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Photometry of Outer Solar System Objects from the Dark Energy Survey. II. A Joint Analysis of Trans-Neptunian Absolute Magnitudes, Colors, Light Curves and Dynamics

For the 696 trans-Neptunian objects (TNOs) with absolute magnitudes 5.5 < H r < 8.2 detected in the Dark Energy Survey, we characterize the relationships between their dynamical state and physical properties—namely H r , indicating size; colors, indicating surface composition; and flux variation semiamplitude A, indicating asphericity and surface inhomogeneity. We seek “birth” physical distributions that can recreate these parameters in every dynamical class. We show that the observed colors of these TNOs are consistent with two Gaussian distributions in griz space, “near-infrared bright” (NIRB) and “near-infrared faint” (NIRF), presumably an inner and outer birth population, respectively. We find a model in which both the NIRB and NIRF H r and A distributions are independent of current dynamical states, supporting their assignment as birth populations. All objects are consistent with a common rolling p(H r ), but NIRF objects are significantly more variable. Cold classicals (CCs) are purely NIRF, while hot classical (HC), scattered, and detached TNOs are consistent with ≈ 70% NIRB and the resonance NIRB fractions show significant variation. The NIRB components of the HCs and of some resonances have broader inclination distributions than the NIRFs, i.e. their current dynamics retains information about birth location. We find evidence for radial stratification within the birth NIRB population, in that HC NIRBs are on average redder than detached or scattered NIRBs; a similar effect distinguishes CCs from other NIRFs. We estimate total object counts and masses of each class within our H r range. These results will strongly constrain models of the outer solar system.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Investigating the Unusual Spectroscopic Time Evolution in SN 2012fr

The type Ia supernova (SN) 2012fr displayed a curious combination of its Si ii λλ5972, 6355 features. This includes the ratio of their pseudo-equivalent widths, placing it at the border of the shallow silicon (SS) and core normal (CN) spectral subtype in the Branch diagram, while the Si ii λ6355 expansion velocities place it as a high-velocity (HV) object in the Wang et al. spectral type that most intriguingly evolves slowly, placing it in the low-velocity gradient (LVG) typing of Benetti et al. Only 5% of SNe Ia are HV and located in the SS+CN portion of the Branch diagram, and fewer than 10% of SNe Ia are both HV and LVG. These features point toward SN 2012fr being quite unusual, similar in many ways to the peculiar SN 2000cx. We modeled the spectral evolution of SN 2012fr to see if we could gain some insight into its evolutionary behavior. We use the parameterized radiative transfer code SYNOW to probe the abundance stratification of SN 2012fr at pre-maximum, maximum, and post-maximum light epochs. We also use a grid of W7 models in the radiative transfer code PHOENIX to probe the effect of different density structures on the formation of the Si ii λ6355 absorption feature at post-maximum epochs. We find that the unusual features observed in SN 2012fr are likely due to a shell-like density enhancement in the outer ejecta. We report on possible reasons for atypical Ca ii absorption features, and suggest that they are related to the Si ii features.

79 ASTRONOMY AND ASTROPHYSICS↗