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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 811 records · Page 45
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Detection of Part Porosity in Additive Manufacturing Using Machining

Monitoring of part porosity in additive manufacturing is critical for part qualification and process parameter development. This article describes the monitoring of porosity in additive manufacturing using machining. Grade 91 steel samples with different levels of porosity were additively manufactured using a laser blown-powder process. The samples were machined, and the tool position and cutting power were monitored using the machine controller and an external power transducer, respectively. Results show that the power transducer is sensitive to machining porosities. A novel approach using the standard deviation of cutting power was developed to determine the location of porosities along the length of the machining pass. Test cuts were completed at different machining process parameters. Results showed that the probability of detection was one for pore volume greater than 0.3 mm 3 at different machining parameters. In conclusion, although the detection of porosity using machining is a destructive method for evaluation, it offers a low-cost and fast approach for monitoring porosity in additive manufacturing.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Convolutional neural network identification of galaxy post-mergers in UNIONS using IllustrisTNG

ABSTRACT The Canada–France Imaging Survey (CFIS) will consist of deep, high-resolution r-band imaging over ∼5000 deg2 of the sky, representing a first-rate opportunity to identify recently merged galaxies. Because of the large number of galaxies in CFIS, we investigate the use of a convolutional neural network (CNN) for automated merger classification. Training samples of post-merger and isolated galaxy images are generated from the IllustrisTNG simulation processed with the observational realism code RealSim. The CNN’s overall classification accuracy is 88 per cent, remaining stable over a wide range of intrinsic and environmental parameters. We generate a mock galaxy survey from IllustrisTNG in order to explore the expected purity of post-merger samples identified by the CNN. Despite the CNN’s good performance in training, the intrinsic rarity of post-mergers leads to a sample that is only ∼6 per cent pure when the default decision threshold is used. We investigate trade-offs in purity and completeness with a variable decision threshold and find that we recover the statistical distribution of merger-induced star formation rate enhancements. Finally, the performance of the CNN is compared with both traditional automated methods and human classifiers. The CNN is shown to outperform Gini–M20 and asymmetry methods by an order of magnitude in post-merger sample purity on the mock survey data. Although the CNN outperforms the human classifiers on sample completeness, the purity of the post-merger sample identified by humans is frequently higher, indicating that a hybrid approach to classifications may be an effective solution to merger classifications in large surveys.

Bickley, Robert W.↗
DOE OSTI2021

Raman Microscopy Analysis of Wyoming CarbonSAFE Pilot Well Thin Sections for Mineralogy and Organic Matter Characterization

Scanning confocal Raman microspectroscopy (RMS) was used to analyze thin sections for inorganic mineral content and for evaluation of organic material (OM). Thin sections were selected from a stratigraphic test well core in the Powder River Basin, Wyoming under the Wyoming CarbonSAFE project. The well was analyzed with a variety of rock and fluid characterization techniques to determine the feasibility of a commercial-scale CO2 storage site. RMS complements other analyses, including traditional petrography, SEM, porosity and permeability, and XRD For this aspect of the study, RMS is especially important in the evaluation of OM in sealing lithologies. At prospective geologic CO2 storage sites, it is imperative to assess the unconventional oil and gas potential of seals to ensure that any future development would not compromise the integrity of the seals. Whole-slide mineralogical surveys were performed on thin sections from various shale and sandstone formations. Surveys were analyzed with Direct Classical Least Squares to identify and quantify minerals. The location and concentration of minerals was color-coded and overlaid on optical images for visualization of the distribution of minerals. Dense hyperspectral Raman mapping of OM was performed on five thin sections. Eleven spectral parameters diagnostic of organic type and thermal maturity were used to train a Partial Least Squares (PLS) calibration against a set of artificially matured samples spanning the pre- to mid-oil window. The PLS was applied to the study set and a post-mature set. Additionally, the PLS was applied to each point in hyperspectral maps for visualization of trends in maturity across sample sets and discrimination of organic matter types within a given map. In inorganic surveys on thin sections, a total of 14 unique inorganic minerals were identified in Raman spectra including quartz, dolomite, calcite, hematite and anhydrite. Shale thin sections tended to be dominated by organic material. OM was often observed mixed with inorganic minerals. Sand- and mudstones were dominated by inorganic minerals. The PLS extrapolated the post-mature set to reflectances >1.2%. The study set ranged from very immature to postmature in the median of map fit-peak parameters. However, point maturity maps indicate that matrix OM in all study samples is immature and that discreet organic particles selected for mapping, which may be inertinites, bias medians towards more-mature. The work demonstrates the capabilities of RMS to perform both whole-slide mineralogy and OM analysis with applications to formation evaluation in oil & gas, carbon sequestration and mining. Here, analysis of sealing formations in the well indicates high levels of immature organic matter that would not be a viable target for future oil production that could compromise the CO2 storage site. The work brings together diverse disciplines from geology and petrography to analytical chemistry, big data and microscopy.

Myers, Grant↗
DOE OSTI2025

What causes the variation in superconducting properties of UTe 2 ?

Reaching a consensus on the superconducting order parameter of unconventional superconductors remains a central challenge in the field of magnetically-mediated superconductivity. Though UTe 2 is largely accepted as a rare example of an odd-parity superconductor, its precise order parameter remains highly debated, even at ambient conditions. A key underlying issue is the large sample-to-sample variation in superconducting properties at zero applied pressure and magnetic field. Here, we investigate the origin of the observed variation by means of single crystal x-ray diffraction (SC-XRD) and scanning transmission electron microscopy (STEM) measurements. Our results reveal highly ordered crystalline lattices, in agreement with the expected Immm structure, and no signs of uranium vacancies. Tiny amounts of interstitial defects, however, are observed on the Te2 layers that host Te chains along the b axis. We argue that these defects give rise to slightly enhanced atomic displacement parameters observed in SC-XRD data and are enough to disrupt the unconventional superconducting state in UTe 2 . Our findings highlight the need to focus future order parameter determination efforts on single crystals of UTe 2 with minimal amounts of structural disorder.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

A New Modeling Framework for Multi-Scale Simulation of Hydraulic Fracturing and Production from Unconventional Reservoirs

This paper describes a new modeling framework for microscopic to reservoir-scale simulations of hydraulic fracturing and production. The approach builds upon a fusion of two existing high-performance simulators for reservoir-scale behavior: the GEOS code for hydromechanical evolution during stimulation and the TOUGH+ code for multi-phase flow during production. The reservoir-scale simulations are informed by experimental and modeling studies at the laboratory scale to incorporate important micro-scale mechanical processes and chemical reactions occurring within the fractures, the shale matrix, and at the fracture-fluid interfaces. These processes include, among others, changes in stimulated fracture permeability as a result of proppant behavior rearrangement or embedment, or mineral scale precipitation within pores and microfractures, at µm to cm scales. In our new modeling framework, such micro-scale testing and modeling provides upscaled hydromechanical parameters for the reservoir scale models. We are currently testing the new modeling framework using field data and core samples from the Hydraulic Fracturing Field Test (HFTS), a recent field-based joint research experiment with intense monitoring of hydraulic fracturing and shale production in the Wolfcamp Formation in the Permian Basin (USA). Below, we present our approach coupling the reservoir simulators GEOS and TOUGH+ informed by upscaled parameters from micro-scale experiments and modeling. We provide a brief overview of the HFTS and the available field data, and then discuss the ongoing application of our new workflow to the HFTS data set.

58 GEOSCIENCES↗
DOE OSTI2023

Fundamental effective temperature measurements for eclipsing binary stars – IV. Selection of new benchmark stars and first results for HD 22064

I describe the selection and initial characterization of 20 eclipsing binary stars that are suitable for calibration and testing of stellar models and data analysis algorithms used by the PLATO mission and spectroscopic surveys. The binary stars selected are F-/G-type dwarf stars with M-type dwarf companions that contribute less than 2 per cent of the flux at optical wavelengths. The light curves typically show well-defined total eclipses with very little variability between the eclipses. I have used near-infrared spectra obtained by the APOGEE survey to measure the spectroscopic orbit for both stars in HD 22064. Combined with an analysis of the TESS light curve, I derive the following masses and radii: M 1 = 1.35 ± 0.03M ⊙ , M 2 = 0.58 ± 0.01M ⊙ , R 1 = 1.554 ± 0.014R ⊙ , R 2 = 0.595 ± 0.008R ⊙ . Using R 1 and the parallax from Gaia EDR3, I find that the primary star’s angular diameter is θ = 0.1035 ± 0.0009 mas. The apparent bolometric flux of the primary star is ${\mathcal {F}}_{{\oplus },0} = (7.51\pm 0.09)\times 10^{-9}$ erg cm -2 s -1 . Hence, this F2V star has an effective temperature $T_{\rm eff,1} = 6763{\rm \, K} \pm 39{\rm \, K}$. HD 22064 is an ideal benchmark star that can be used for ‘end-to-end’ tests of the stellar parameters measured by large-scale spectroscopic surveys or stellar parameters derived from asteroseismology with PLATO. The techniques described here for HD 22064 can be applied to the other eclipsing binaries in the sample in order to create an all-sky network of such benchmark stars.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Constrained model calibration of grain structure dependent spall dynamics in shock-loaded tantalum

Here, we perform a gas gun experiment by shock loading tantalum samples of varying grain structures to assess the suitability of a numerical model for simulating spall behavior. The observed differences in spall strength, as well spallation and re-compression history, are not captured in uncalibrated hydrodynamic simulations. An optimization is performed on the Johnson spall model to determine the best parameters that fit the observed trends. Linear stability analysis is employed to motivate bounds on those parameters. Herein, optimized simulations agree well with the experimental results, reproducing pullback depth and recompression timescales across the different samples tested. Further, the observed pullback time of the single crystal sample was found to imply, via the stability analysis, a percolation threshold in good agreement with the theoretical value for a body centered cubic lattice. Therefore, the combined linear stability and percolation analysis shows promise and may be applied to other materials with diverse microstructures. Collectively, the findings demonstrate that the model is suitable for reproducing spall-induced free surface behavior across various microstructures, but also points to caution in using model coefficients for uncalibrated microstructures.

58 GEOSCIENCES↗
DOE OSTI2020

A New Method for Deriving Composition of S-type Asteroids from Noisy and Incomplete Near-infrared Spectra

The surface composition of S-type asteroids can be determined using band parameters extracted from their near-infrared (NIR) spectra (0.7–2.50 μm) along with spectral calibrations derived from laboratory samples. In the past, these empirical equations have been obtained by combining NIR spectra of meteorite samples with information about their composition and mineral abundance. For these equations to give accurate results, the characteristics of the laboratory spectra they are derived from should be similar to those of asteroid spectral data (i.e., similar signal-to-noise ratio (S/N) and wavelength range). Here we present new spectral calibrations that can be used to determine the mineral composition of ordinary chondrite-like S-type asteroids. Contrary to previous work, the S/N of the ordinary chondrite spectra used in this study has been decreased to recreate the S/N typically observed among asteroid spectra, allowing us to obtain more realistic results. In addition, the new equations have been derived for five wavelength ranges encompassed between 0.7 and 2.50 μm, making it possible to determine the composition of asteroids with incomplete data. The new spectral calibrations were tested using band parameters measured from the NIR spectrum of asteroid (25143) Itokawa, and comparing the results with laboratory measurements of the returned samples. We found that the spectrally derived olivine and pyroxene chemistry, which are given by the molar contents of fayalite (Fa) and ferrosilite (Fs), are in excellent agreement with the mean values measured from the samples (Fa{sub 28.6±1.1} and Fs{sub 23.1±2.2}), with a maximum difference of 0.6 mol% for Fa and 1.4 mol% for Fs.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Trace explosives sampling for security applications (TESSA) study: Evaluation of procedures and methodology for contact sampling efficiency

We report the detection of trace amounts of explosive materials is critical to the security at mass transit centers (e.g., airports and railway stations). In a typical screening process, a trap is used to probe a surface of interest to collect and transfer particulate residue to a detector for analysis. The collection of residues from the surface being probed is widely viewed as the limiting step in this process. A multi-institutional study was performed to establish a methodology for the evaluation of sampling media collection efficiencies. Dry deposited residues of 1,3,5-trinitroperhydro-1,3,5-triazine (RDX), C-4 (an RDX-based explosive), and pentaerythritol tetranitrate (PETN) were harvested from acrylonitrile butadiene styrene (ABS) plastic, ballistic nylon (NYL), and uncoated aluminum surfaces using muslin, Texwipe cotton, and stainless-steel mesh traps. Transfer and collection efficiencies of the sample media were calculated based on liquid chromatography-mass spectrometry analysis. Dry transfer efficiencies (DTE%) to all tested surfaces were greater than 75%, with transfer to ABS plastic being the lowest. Collection efficiency (CE%) varied significantly across the traps and the surfaces, yet some conclusions can be drawn; nylon had the lowest CE% for all cases (~10%), and the stainless steel mesh had the lowest CE% for the evaluated traps (~20%). Though the testing parameters have been standardized among the participants to establish a framework for an independent comparison of contact sampling media and surfaces, substantial variations in the DTE% and the CE% were observed, suggesting that other variables can affect contact sampling.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Correlation between cation order/disorder and the electrocaloric effect in the MLCCs of complex perovskite ferroelectrics

The physical properties (dielectric, ferroelectric, piezoelectric, etc.) of complex perovskite ferroelectrics depend on the degree of order/disorder and the scale of the ordered domains. In this study, the electrocaloric (EC) properties of three representative complex perovskite ferroelectrics, Pb(Mg 1/3 Nb 2/3 )O 3 -8PbTiO 3 (PMN-8PT), 1mol% Sm-doped Pb(Mg 1/3 Nb 2/3 )O 3 -8PbTiO 3 (1S-PMN-8PT) and Pb(Sc 1/2 Ta 1/2 )O 3 (PST) are evaluated. Multi-layer ceramic capacitors (MLCCs) with identical structural configurations were fabricated for these three compounds, and their EC properties were characterized by direct measurement using a thermocouple. The EC temperature change of PMN-8PT, 1S-PMN-8PT and PST MLCCs under 20 V μm –1 at room temperature were found to be 1.42 K, 1.54 K, and 3.10 K, respectively. X-ray diffraction and high-resolution transmission electron microscopy data suggests that the high EC performance of PST is related to the ordering of B-site cations (Sc 3+ and Ta 5+ ) with the ordering parameter S = 0.82 and a long coherence length of ~100 nm, such that the sample transitioned from a relaxor ferroelectric to a normal ferroelectric. Furthermore, these results provide pathway towards design of high performance EC materials required for solid state refrigeration and air-conditioning technologies.

36 MATERIALS SCIENCE↗
DOE OSTI2022

PyAlbany: A Python interface to the C++ multiphysics solver Albany

Albany is a parallel C++ finite element library for solving forward and inverse problems involving partial differential equations (PDEs). In this paper we introduce PyAlbany, a newly developed Python interface to the Albany library. PyAlbany can be used to effectively drive Albany enabling fast and easy analysis and post-processing of applications based on PDEs that are pre-implemented in Albany. PyAlbany relies on the library PyBind11 to bind Python with C++ Albany code. Here we detail the implementation of PyAlbany and showcase its capabilities through a number of examples targeting a heat-diffusion problem. In particular we consider the following: (1) the generation of samples for a Monte Carlo application, (2) a scalability study, (3) a study of parameters on the performance of a linear solver, and finally (4) a tool for performing eigenvalue decompositions of matrix-free operators for a Bayesian inference application.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Analysis of autogenous shrinkage-induced microcracks in concrete from 3D images

A new image analysis procedure for quantifying microcracks from three-dimensional (3D) X-ray microCT images of concrete is presented. The method separates microcracks from air voids and aggregates by combining filtering and morphological operations. It was applied to study the effects of supplementary cementitious materials (SCMs) and curing age on autogenous shrinkage-induced microcracks in low w/b ratio concretes, and to determine the representative elementary volume (REV) for various properties of microcracks and air voids. Results showed that slag and silica fume significantly increased autogenous shrinkage and related microcracking. These SCMs increased volume fraction, width, length, dendritic density, anisotropy, and connectivity of microcracks, but decreased specific surface and tortuosity. Similar trends were observed with age. Comparison between 3D and 2D measurements was made. REV analysis showed that a sampling volume of ~20 × 20 × 25 mm{sup 3} is sufficient for characterising most parameters of autogenous shrinkage microcracks and air voids in concrete.

36 MATERIALS SCIENCE↗
DOE OSTI2025

An experimental study on gas-liquid phase fluid migration in hydrate-bearing sediments during hydrate dissociation

Natural gas hydrate production tests face problems such as severe sand blockage, poor gas-liquid phase separation, and significant land subsidence. This is because of the insufficient understanding of the complex phase transition and gas-liquid multi-phase fluid migration during hydrate dissociation. In hydrate-bearing sediment systems, hydrate phase transition couples with gas-liquid fluid migration. The phase transition causes changes in pore structure, which in turn modifies porous infiltration parameters and fluid flow capacity. Meanwhile, alterations in phase interfaces affect key parameters like surface tension and wettability. Gas-liquid fluid migration influences heat and mass transfer, thus affecting phase equilibrium and dissociation rates. To bridge the gap in describing gas-liquid fluid migration during hydrate dissociation in experiments, this research innovatively integrated an unsteady-state gas displacement by water and a quantitative hydrate dissociation process, independently developed a multi-phase seepage experimental system suitable for hydrate dissociation and determined the relationship between seepage parameters and hydrate saturation under different porosity. The results are as follows: a) Core samples with higher initial porosity show a greater recovery rate of fluid flow capacity. b) The retarding effect of multi-phase fluid has a more significant impact on the migration of the wetting phase fluid (water) than that of the non-wetting phase fluid (methane). c) During hydrate dissociation, the evolution of absolute permeability shows an “S-shaped” pattern, and the evolution of relative permeability shows a “wiring-harness” pattern. In conclusion, the findings can provide a theoretical basis for preventing geological disasters and for geotechnical engineering design during hydrate production.

58 GEOSCIENCES↗
DOE OSTI2024

Sensitivity analysis, surrogate modeling, and optimization of pebble-bed reactors considering normal and accident conditions

This research provides a valuable tool that streamlines the optimization process while significantly increasing its accuracy. This study creates a robust framework for reactor design optimization by incorporating comprehensive modeling using the Comprehensive Reactor Analysis Bundle, or BlueCRAB, within the Multiphysics Object-Oriented Simulation Environment (MOOSE). BlueCRAB is the United States Nuclear Regulatory Commission's code suite for non-light water reactor analysis and includes the Griffin, Pronghorn, and Bison applications. This not only improves the efficiency of the optimization process but also enhances the reliability of the results. Such a tool is essential for advancing the state-of-the-art in pebble-bed reactor technology and is critical for achieving the goals of Generation IV reactors, which aim for safe, sustainable, and economically viable nuclear energy solutions. This work presents and applies this workflow on pebble-bed reactors while considering both normal and off-normal conditions. A representative gas-cooled pebble-bed reactor at equilibrium core conditions serves as the nominal design specification for normal operation and is based on previous research. The depressurized loss-of-forced-cooling accident is deployed for off-normal conditions in this work. After defining design-related parameters and quantities of interest regarding reactor safety and performance, this multiphysics model is sampled using the MOOSE stochastic tools module. The result is a comprehensive dataset of configurations, enabling sensitivity analysis and the generation of surrogate models. Subsequently, the dataset and surrogate models are employed in two optimization studies aimed at maximizing fuel utilization and economic profit while adhering to safety and operational constraints. Performing the optimization process with fuel utilization as the metric leads to an improvement of approximately 10%, compared to engineering-judgment-based nominal conditions. The optimization on economic profit leads to an estimated increase of ~300 million USD over the lifetime of the reactor.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Adapted Cell Design for the Operando X‑Ray Absorption Study of a Structurally Evolving Cu Nanoparticle Ensemble during the CO2 Electroconversion to Multicarbon Products

An improved understanding of the materials that will sustain the future of energy production, storage, and delivery calls for better characterization tools. Operando characterization methods have thus become essential for investigating electrocatalytic materials. Without their resulting insights, the study of highly performing catalysts post-mortem cannot viably facilitate the further development of functional catalysts. Herein, we present an operando electrochemical cell designed for hard X-ray absorption spectroscopy (XAS) and specifically adapted to the study of an electrocatalytically active Cu nanoparticle ensemble. So far, this nanocatalyst has proven to pose quite a challenge to characterize due to its unique structural dynamics. Adopting a design comparable to the H-cell employed for all activity testing, we report the satisfactory translation of the active site formation into an XAS-compatible cell. The simultaneous collection of CO2-derived products during XAS characterization enabled the operando characterization of this CO2-reducing active structure. We report a Cu–Cu coordination number of the first scattering path higher than suggested in our previous studies, highlighting the importance of monitoring metastable nanoelectrocatalysts in operando. This study illustrates important caveats for the electrocatalysis community when considering the application of operando XAS. Our results highlight that the sample size, homogeneity, and stability determine how to interpret the measured signal. Considering these parameters carefully, the operando EXAFS results confirm the exceptional undercoordinated character of the Cu nanoparticle ensemble during CO2 reduction to C2+ products.

Louisia, Sheena↗
DOE OSTI2023

Stochastic optimization of a uranium oxide reaction mechanism using plasma flow reactor measurements

Abstract In this work, a coupled Monte Carlo Genetic Algorithm (MCGA) approach is used to optimize a gas phase uranium oxide reaction mechanism based on plasma flow reactor (PFR) measurements. The PFR produces a steady Ar plasma containing U, O, H, and N species with high temperature regions (3000–5000 K) relevant to observing UO formation via optical emission spectroscopy. A global kinetic treatment is used to model the chemical evolution in the PFR and to produce synthetic emission signals for direct comparison with experiments. The parameter space of a uranium oxide reaction mechanism is then explored via Monte Carlo sampling using objective functions to quantify the model-experiment agreement. The Monte Carlo results are subsequently refined using a genetic algorithm to obtain an experimentally corroborated set of reaction pathways and rate coefficients. Out of 12 reaction channels targeted for optimization, four channels are found to be well constrained across all optimization runs while another three channels are constrained in select cases. The optimized channels highlight the importance of the OH radical in oxidizing uranium in the PFR. This study comprises a first step toward producing a comprehensive experimentally validated reaction mechanism for gas phase uranium molecular species formation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Statistical inference of anomalous thermal transport with uncertainty quantification for interpretive 2D SOL models

The critical task of inferring anomalous cross-field transport coefficients is addressed in simulations of boundary plasmas with fluid models. A workflow for parameter inference in the UEDGE fluid code is developed using Bayesian optimization with parallelized sampling and integrated uncertainty quantification. In this workflow, transport coefficients are inferred by maximizing their posterior probability distribution, which is generally multidimensional and non-Gaussian. Uncertainty quantification is integrated throughout the optimization within the Bayesian framework that combines diagnostic uncertainties and model limitations. As a concrete example, we infer the anomalous electron thermal diffusivity $\chi_\perp$ from an interpretive 2D model describing electron heat transport in the conduction-limited region with radiative power loss. The workflow is first benchmarked against synthetic data and then tested on H-, L-, and I-mode discharges to match their midplane temperature and divertor heat flux profiles. We demonstrate that the workflow efficiently infers diffusivity and its associated uncertainty, generating 2D profiles that match 1D measurements. Future efforts will focus on incorporating more complicated fluid models and analyzing transport coefficients inferred from a large database of experimental results.

Bayesian optimization↗
DOE OSTI2020

H i imaging of dwarf star-forming galaxies: masses, morphologies, and gas deficiencies

ABSTRACT The Giant Meter-wave Radio Telescope observations of the H i 21 cm-line emission from 13 nearby dwarf star-forming galaxies are presented. These galaxies are selected from the catalogues of Wolf−Rayet galaxies having very young (≤10 Myr) star formation. The ranges of star formation rates and stellar masses of the sample galaxies are 0.03–1.7 M⊙ yr−1 and 0.04–22.3 × 108 M⊙, respectively. The H i line emission is detected from 12 galaxies with peak column density >1 × 1021 cm−2. The 3σ H i column density sensitivities per channel width of 7 km s−1 for low (60 arcsec × 60 arcsec) resolution images are in the range 0.8–1.9 × 1019 cm−2. The H i channel images, moment images, global profiles, and mass surface density profiles are presented here. The average value of the peak H i mass surface density is estimated to be ∼2.5 M⊙ pc−2, which is significantly less compared to that in massive spiral galaxies. The scaling relations of $(M_{stars} + M_{\rm H\, I} + M_{\rm He})$versus Mdyn, gas fraction versus MB, $M_{\rm H\, I}$versus Mstars, H i-to-stellar mass ratio versus Mstars, and $M_{\rm H\, I}$versus $D_{\rm H\, I}$for the sample galaxies are estimated. These scaling relations can be used to constraint the key parameters in the galaxy evolution models. These galaxies are residing in group environment with galaxy density up to eight galaxy Mpc−3. An H i mass deficiency (with DEFH i > 0.3) is noticed in majority of galaxies for their optical diameters as compared to galaxies in field environments. Clear signatures of tidal interactions in these galaxies could be inferred using the H i images. Isolated H i clouds without known optical counterparts are seen in the vicinity of several galaxies. H i emission envelope is found to be having an offset from the optical envelope in several galaxies. Consistent with the previous studies on galaxy evolution in group environments, tidal interactions seem to play an important role in triggering recent star formation.

Jaiswal, S.↗