Self-pressurization of a flightweight liquid hydrogen storage tank subjected to low heat flux

Results are presented for an experimental investigation of self-pressurization and thermal stratification of a 4.89 cu m liquid hydrogen (LH2) storage tank subjected to low heat flux (0.35, 2.0, and 3.5 W/sq m) under normal gravity conditions. Tests were performed at fill levels of 83 to 84 percent (by volume). The LH2 tank was representative of future spacecraft tankage, having a low mass-to-volume ratio and high performance multilayer thermal insulation. Results show that the pressure rise rate and thermal stratification increase with increasing heat flux. At the lowest heat flux, the pressure rise rate is comparable to the homogenous rate, while at the highest heat flux, the rate is more than three times the homogeneous rate. It was found that initial conditions have a significant impact on the initial pressure rise rate. The quasi-steady pressure rise rates are nearly independent of the initial condition after an initial transient period has passed

A pressure control analysis of cryogenic storage systems

Self-pressurization of cryogenic storage tanks due to heat leak through the thermal protection system is examined along with the performance of various pressure control technologies for application in microgravity environments. Methods of pressure control such as fluid mixing, passive thermodynamic venting, and active thermodynamic venting are analyzed using the homogeneous thermodynamic model. Simplified equations suggested may be used to characterize the performance of various pressure control systems and to design space experiments

Self-pressurization of a flightweight liquid hydrogen tank: Effects of fill level at low wall heat flux

Experimental results are presented for the self pressurization and thermal stratification of a 4.89 cu m liquid hydrogen storage tank subjected to low heat flux (2.0 and 3.5 W/sq m) in normal gravity. The test tank was representative of future spacecraft tankage, having a low mass to volume ratio and high performance multilayer thermal insulation. Tests were performed at fill levels of 29 and 49 pcts. (by volume) and complement previous tests at 83 pct. fill. As the heat flux increases, the pressure rise rate at each fill level exceeds the homogeneous rate by an increasing ratio. Herein, this ratio did not exceed a value of 2. The slowest pressure rise rate was observed for the 49 pct. fill level at both heat fluxes. This result is attributed to the oblate spheroidal tank geometry which introduces the variables of wetted wall area, liquid-vapor interfacial area, and ratio of side wall to bottom heating as a function of fill level or liquid depth. Initial tank thermal conditions were found to affect the initial pressure rise rate. Quasi steady pressure rise rates are independent of starting conditions

Membership of Stars in Open Clusters using Random Forest with Gaia Data

Membership of stars in open clusters is one of the most crucial parameters in studies of star clusters. Gaia opened a new window in the estimation of membership because of its unprecedented 6-D data. In the present study, we used published membership data of nine open star clusters as a training set to find new members from Gaia DR2 data using a supervised random forest model with a precision of around 90\%. The number of new members found is often double the published number. Membership probability of a larger sample of stars in clusters is a major benefit in determination of cluster parameters like distance, extinction and mass functions. We also found members in the outer regions of the cluster and found sub-structures in the clusters studied. The color magnitude diagrams are more populated and enriched by the addition of new members making their study more promising.Comment: Accepted for publication in The European Physical Journal ST, Special Issue on Modeling Machine Learning and Astronom

The enhanced YSO population in Serpens

The Serpens Molecular Cloud is one of the most active sites of ongoing star formation at a distance of about 300 pc, and hence is very well-suited for studies of young low-mass stars and sub-stellar objects. In this paper, for the Serpens star forming region, we find potential members of the Young Stellar Objects population from the Gaia DR3 data and study their kinematics and distribution. We compile a catalog of 656 YSOs from available catalogs ranging from X-ray to the infrared. We use this as a reference set and cross-match it to find 87 Gaia DR3 member stars to produce a control sample with revised parameters. We queried the DR3 catalog with these parameters and found 1196 stars. We then applied three different density-based machine learning algorithms (DBSCAN, OPTICS and HDBSCAN) to this sample and found potential YSOs. The three clustering algorithms identified a common set of 822 YSO members from Gaia DR3 in this region. We also classified these objects using 2MASS and WISE data to study their distribution and the progress of star formation in Serpens.Comment: Accepted in Journal of Astrophysics and Astronomy (JoAA

Pleomorphic adenoma of the parotid gland: Report of a case with review of literature

BACKGROUND: Pleomorphic adenomas are benign salivary gland tumors, which predominantly affect the superficial lobe of the parotid gland. The “pleomorphic” nature of the tumor can be explained on the basis of its epithelial and connective tissue origin. The tumor has a female predilection between 30-50 years of age. Slowly progressing asymptomatic swelling is the usual presentation of the tumor. Surgical excision of the tumor mass forms the mainstay of treatment, with utmost care taken to preserve the facial nerve.CASE DETAILS: This case report aims to throw light on an interesting case of pleomorphic adenoma of the parotid gland in a 50 years old female patient. The patient presented with a slowly progressing asymptomatic swelling on the left side of the face. There is also a special emphasis to a detailed review of literature.CONCLUSION: Salivary gland neoplasms can occur at any site where salivary tissue is present. Pleomorphic adenoma is the commonest salivary gland tumor characterized by diverse histomorphological features. Early diagnosis and treatment plan entails thorough history taking, clinical examination, coupled with radiographic and histopathological findings.KEYWORDS: Benign salivary gland tumors, Pleomorphic adenomas, Parotidectom

Using GMM in Open Cluster Membership: An Insight

The unprecedented precision of Gaia has led to a paradigm shift in membership determination of open clusters where a variety of machine learning (ML) models can be employed. In this paper, we apply the unsupervised Gaussian Mixture Model (GMM) to a sample of thirteen clusters with varying ages ($log \ t \approx$ 6.38-9.64) and distances (441-5183 pc) from Gaia DR3 data to determine membership. We use ASteca to determine parameters for the clusters from our revised membership data. We define a quantifiable metric Modified Silhouette Score (MSS) to evaluate its performance. We study the dependence of MSS on age, distance, extinction, galactic latitude and longitude, and other parameters to find the particular cases when GMM seems to be more efficient than other methods. We compared GMM for nine clusters with varying ages but we did not find any significant differences between GMM performance for younger and older clusters. But we found a moderate correlation between GMM performance and the cluster distance, where GMM works better for closer clusters. We find that GMM does not work very well for clusters at distances larger than 3~kpc.Comment: Accepted in Astronomy & Computin