Engineering topics

Kassemi, M.

Publications and source records attributed to Kassemi, M..

At least 19 records

NASA NTRS2019

CFD Jet Mixing Model Validation Against Zero-Boil-Off Tank (ZBOT) Microgravity Experiment

The Zero-Boil-Off Tank (ZBOT) experiments are a series of small scale two-phase fluids physics experiments conducted aboard the International Space Station (ISS) in 2017. A goal of these experiments is to study various fundamental fluid flow, heat and mass transport, and phase change phenomena that control storage tank pressurization and pressure control in microgravity. In this paper, results of a state-of-the-art two-phase CFD (Computational Fluid Dynamics) storage tank model are presented and validated against jet mixing data provided by microgravity ZBOT experiments. Jet-ullage interaction was studied in the experiment for different jet speeds representing different flow regimes, and tank fill levels. Effects of various physical parameters, such as, jet angle, gravitational acceleration and surface tension value were investigated. Computational parameters, such as turbulence and surface tension models and interface capturing scheme, affecting jet-ullage interaction were also studied. Computational results were compared to experimental results for model validation.

Turbulence↗

NASA NTRS2019

CFD Jet Mixing Model Validation against Zero-Boil-Off Tank (ZBOT) Microgravity Experiment

The Zero-Boil-Off Tank (ZBOT) experiments are a series of small scale two-phase fluids physics experiments conducted aboard the International Space Station (ISS) in 2017. A goal of these experiments is to study various fundamental fluid flow, heat and mass transport, and phase change phenomena that control storage tank pressurization and pressure control in microgravity. In this paper, results of a state-of-the-art two-phase CFD storage tank model are presented and validated against jet mixing data provided by microgravity ZBOT experiments. Jet-ullage interaction was studied in the experiment for different jet speeds representing different flow regimes, and tank fill levels. Effects of various physical parameters, such as, jet angle, gravitational acceleration and surface tension value were investigated. Computational parameters, such as turbulence and surface tension models and interface capturing scheme, affecting jet-ullage interaction were also studied. Computational results were compared to experimental results for model validation.

Mixing↗

NASA NTRS2019

SINDA/FLUINT and Thermal Desktop Multi-Node Settled and Unsettled Propellant Tank Modeling of Zero Boil Off Test

Cryogenic propellant storage tank self-pressurization involves complex physical phenomena which are usually analytically modelled via complex multidimensional CFD (Computational Fluid Dynamics) codes. Unfortunately these codes, even when modelling axisymmetric domains, may take weeks or longer to obtain transient pressure and temperature information for relatively short periods of time (several seconds to several hours). Propellant tank storage end-to-end mission simulations can last a duration of days to weeks to months. Multi-node modelling of propellant tanks is a viable alternative to traditional CFD modelling and presents the advantage of greatly reduced run times on the order of hours and days compared to the weeks or longer for CFD codes. A multi-node model represents the fluid within the storage tank, as well as the storage tank itself, as a fluid-thermal network. This type of setup is not necessarily geometrically based. This can be accomplished using a commercial generalized fluid-thermal network code, such as SINDA/FLUINT (SF). The advantage of using a fluid-thermal network code like SF lies in its extensive ability to model the external environment of the storage tank through the graphical user interface, Thermal Desktop (TD). The total heat load into the tank may be a function of heaters and a complex radiative environment as well. Thermal Desktop may be used to address the detailed radiative environment of the tank as well as building a geometrically accurate depiction of the storage tank itself.

Thermal Desktop↗

NASA NTRS2019

SINDA/FLUINT and Thermal Desktop Multi-Node Settled and Unsettled Propellant Tank Modeling of Zero Boil Off Test

Cryogenic propellant storage tank self-pressurization involves complex physical phenomena which are usually analytically modelled via complex multidimensional CFD codes. Unfortunately these codes, even when modelling axisymmetric domains, may takes weeks or longer to obtain transient pressure and temperature information for relatively short periods of time (several seconds to several hours). Propellant tank storage end-to-end mission simulations can last a duration of days to weeks to months. Multi-node modelling of propellant tanks is a viable alternative to traditional CFD modelling and presents the advantage of greatly reduced run times on the order of hours and days compared to the weeks or longer for CFD codes. A multi-node model represents the fluid within the storage tank, as well as the storage tank itself, as a fluid-thermal network. This type of setup is not necessarily geometrically based. This can be accomplished using a commercial generalized fluid-thermal network code, such as SINDA/FLUINT (SF). The advantage of using a fluid-thermal network code like SF lies in its extensive ability to model the external environment of the storage tank through the graphical user interface, Thermal Desktop (TD). The total heat load into the tank may be a function of heaters and a complex radiative environment as well. Thermal Desktop may be used to address the detailed radiative environment of the tank as well as building a geometrically accurate depiction of the storage tank itself.

Sakowski, Barbara↗

NASA NTRS2018

Validation of a CFD Model Predicting the Effect of High Level Lateral Acceleration Sloshing on the Heat Transfer and Pressure Drop in a Small-Scale Tank in Normal Gravity

A two-phase CFD model is developed to study the effects of sloshing with high level lateral acceleration on the heat transfer and pressure drop in a small scale tank. Computational results are compared to the data provided by a non-isothermal sloshing experiment without phase change conducted by T. Himeno et al. at the University of Tokyo and JAXA in 2011. The results of the current model are, also, compared to CFD predictions reported by Himeno et al. A step change in lateral acceleration was applied in the experiment. Different levels of lateral acceleration amplitude, varying between 0G and 0.5G, were considered. CFD results for interface movement and tank pressure are presented and compared in this paper to the experimental data for the case in which the value of lateral acceleration was set to 0.5G. The effects of initial and boundary conditions and turbulence modeling approach on the tank pressure change during sloshing are discussed in detail. The effect of conjugate heat transfer in the tank wall is also studied to show its important role in determining the tank pressure evolution. The results of the Reynolds Averaged Navier Stokes (RANS) models are compared to the results of the Large Eddy Simulation model (LES) to underscore the importance of correctly capturing the effects of turbulence for high fidelity predictions.

multiphase flow↗

NASA NTRS2018

Validation of Heat Transfer Correlations in Line Chill-Down Tests of Cryogenic Fluid in SINDA/FLUINT

Line chill-down is an important process in cryogenic tank propellant management, storage, and usage Complex flow dynamics during these processes: boiling heat transfer (film, transition, and nucleate) Understanding boiling phenomena can lead to efficient line chill-down systems that use less propellant, propellant stored, reducing cost for space missions Line Chill-down heat transfer was modelled using SINDA/FLUINT version 5.8 (SF) Multiple chill-down tests were modelled using: heat transfer correlations readily available in SF using HTN/HTC TIES heat transfer empiricisms developed by the University of Florida (UF) based on a series of liquid nitrogen chill-down tests using SF HTU TIES Chill-down tests modelled: liquid nitrogen tests conducted by the University of Florida horizontal flow, upward flow, and downward flow (Reynolds Numbers ranging 850-231,000)liquid hydrogen tests conducted by NASA Glenn Research Center vertical upward flow (Reynolds Number range of 18,400 - 433,000)The flow rate was measured far downstream of the test section, near the system exit. Where to set the flow rate? SF was highly sensitive, and sometime unstable, setting the test flow rate downstream (the outlet) of the test section model and setting the test pressure upstream (the inlet) of the test section model higher flow rate oscillations at the entrance of the model's test section SF was more stable setting the test flow rate upstream (than the downstream flow rate set case)test pressure was used as an inlet (SF plenum) to set the thermodynamic state (temperature and quality) coming into the system setting the appropriate downstream pressure was the unknown. The pressure drops predicted by SF for the downstream set flow rate boundary condition were much smaller than test section measured pressure drops. The multiphase pressure drop correlations used internally in SF may need to be adjusted. Models with an upstream flow rate set assumed a pressure drop that was small

cryogenic modeling↗

NASA NTRS2018

Validation of Heat Transfer Correlations in Line Chill-Down Tests of Cryogenic Fluid in SINDA/FLUINT

Line Chill-down heat transfer was modelled using SINDA/FLUINT. Multiple chill-down tests were modelled using the heat transfer correlations that are available in SINDA/FLUINT, as well as incorporating heat transfer empiricisms developed by the University of Florida1 based on a series of liquid nitrogen chill-down tests. The chill-down tests that were modelled were the liquid nitrogen tests conducted by the University of Florida1 as well as liquid hydrogen tests conducted by NASA Glenn Research Center2. The liquid nitrogen tests included horizontal flow, upward flow, and downward flow with the liquid Reynolds Numbers ranging 850 - 231,000. The liquid hydrogen test was vertical upward flow at a Reynolds Number range of 18,400 - 433,000. Both the University of Florida's heat transfer correlations and SINDA/FLUINT's internal correlations faired similarly to wall temperature test data. They were acceptable although improvements could be made to the University of Florida correlations as well and SINDA/FLUINT's internal correlations.

cryogenic modeling↗

NASA NTRS2018

Sensitivity Analysis of the Change of Renal Stone Occurrence Rates in Astronauts Using Urine Chemistries

Changes in urine chemistry, during and post-flight, potentially alter the likelihood of renal stones in astronauts. Although much is known about the effects of space flight on urine chemistry, no inflight incidences of renal stones in US astronauts exist and the question How much does this risk change with space flight? remains difficult to accurately quantify. Previous work by our group has illustrated the application of multi-factor deterministic and probabilistic modeling to assess the change in predicted likelihood of renal stone. Utilizing 1517 astronaut urine chemistries to inform the renal stone occurrence rate forecasting model, we performed a sensitivity analysis on urine chemistry components for their influence on predictions of renal stone size and rate of renal stone occurrence.

physiological response↗

NASA NTRS2017

Computational Modeling of Space Physiology for Informing Spaceflight Countermeasure Design and Predictions of Efficacy

MOTIVATION: Spaceflight countermeasures mitigate the harmful effects of the space environment on astronaut health and performance. Exercise has historically been used as a countermeasure to physical deconditioning, and additional countermeasures including lower body negative pressure, blood flow occlusion and artificial gravity are being researched as countermeasures to spaceflight-induced fluid shifts. The NASA Digital Astronaut Project uses computational models of physiological systems to inform countermeasure design and to predict countermeasure efficacy.OVERVIEW: Computational modeling supports the development of the exercise devices that will be flown on NASAs new exploration crew vehicles. Biomechanical modeling is used to inform design requirements to ensure that exercises can be properly performed within the volume allocated for exercise and to determine whether the limited mass, volume and power requirements of the devices will affect biomechanical outcomes. Models of muscle atrophy and bone remodeling can predict device efficacy for protecting musculoskeletal health during long-duration missions. A lumped-parameter whole-body model of the fluids within the body, which includes the blood within the cardiovascular system, the cerebral spinal fluid, interstitial fluid and lymphatic system fluid, estimates compartmental changes in pressure and volume due to gravitational changes. These models simulate fluid shift countermeasure effects and predict the associated changes in tissue strain in areas of physiological interest to aid in predicting countermeasure effectiveness. SIGNIFICANCE: Development and testing of spaceflight countermeasure prototypes are resource-intensive efforts. Computational modeling can supplement this process by performing simulations that reduce the amount of necessary experimental testing. Outcomes of the simulations are often important for the definition of design requirements and the identification of factors essential in ensuring countermeasure efficacy.

biomedical data↗

NASA NTRS2016

Forecasting the Change of Renal Stone Occurrence Rates in Astronauts

physiological response↗

NASA NTRS2016

Modeling Droplet Heat and Mass Transfer during Spray Bar Pressure Control of the Multipurpose Hydrogen Test Bed (MHTB) Tank in Normal Gravity

A CFD model for simulating pressure control in cryogenic storage tanks through the injection of a subcooled liquid into the ullage is presented and applied to the 1g MHTB spray bar cooling experiments. An Eulerian-Lagrangian approach is utilized to track the spray droplets and capture the interaction between the discrete droplets and the continuous ullage phase. The spray model is coupled with the VOF model by performing particle tracking in the ullage, removing particles from the ullage when they reach the interface, and then adding their contributions to the liquid. A new model for calculating the droplet-ullage heat and mass transfer is developed. In this model, a droplet is allowed to warm up to the saturation temperature corresponding to the ullage vapor pressure, after which it evaporates while remaining at the saturation temperature. The droplet model is validated against the results of the MHTB spray-bar cooling experiments with 50% and 90% tank fill ratios. The predictions of the present T-sat based model are compared with those of a previously developed kinetic-based droplet mass transfer model. The predictions of the two models regarding the evolving tank pressure and temperature distributions, as well as the droplets' trajectories and temperatures, are examined and compared in detail. Finally, the ullage pressure and local vapor and liquid temperature evolutions are validated against the corresponding data provided by the MHTB spray bar mixing experiment.

mass transfer↗

NASA NTRS2016

Modeling Ullage Dynamics of Tank Pressure Control Experiment during Jet Mixing in Microgravity

A CFD model for simulating the fluid dynamics of the jet induced mixing process is utilized in this paper to model the pressure control portion of the Tank Pressure Control Experiment (TPCE) in microgravity1. The Volume of Fluid (VOF) method is used for modeling the dynamics of the interface during mixing. The simulations were performed at a range of jet Weber numbers from non-penetrating to fully penetrating. Two different initial ullage positions were considered. The computational results for the jet-ullage interaction are compared with still images from the video of the experiment. A qualitative comparison shows that the CFD model was able to capture the main features of the interfacial dynamics, as well as the jet penetration of the ullage.

active control↗

NASA NTRS2016

Effect of Dietary Countermeasures and Impact of Gravity on Renal Calculi Size Distributions Predicted by PBE-System and PBE-CFD Models

Renal stone disease is not only a concern on earth but can conceivably pose a serious risk to the astronauts health and safety in Space. In this work, two different deterministic models based on a Population Balance Equation (PBE) analysis of renal stone formation are developed to assess the risks of critical renal stone incidence for astronauts during space travel. In the first model, the nephron is treated as a continuous mixed suspension mixed product removal crystallizer and the PBE for the nucleating, growing and agglomerating renal calculi is coupled to speciation calculations performed by JESS. Predictions of stone size distributions in the kidney using this model indicate that the astronaut in microgravity is at noticeably greater but still subcritical risk and recommend administration of citrate and augmented hydration as effective means of minimizing and containing this risk. In the second model, the PBE analysis is coupled to a Computational Fluid Dynamics (CFD) model for flow of urine and transport of Calcium and Oxalate in the nephron to predict the impact of gravity on the stone size distributions. Results presented for realistic 3D tubule and collecting duct geometries, clearly indicate that agglomeration is the primary mode of size enhancement in both 1g and microgravity. 3D numerical simulations seem to further indicate that there will be an increased number of smaller stones developed in microgravity that will likely pass through the nephron in the absence of wall adhesion. However, upon reentry to a 1g (Earth) or 38g (Mars) partial gravitational fields, the renal calculi can lag behind the urinary flow in tubules that are adversely oriented with respect to the gravitational field and grow agglomerate to large sizes that are sedimented near the wall with increased propensity for wall adhesion, plaque formation, and risk to the astronauts.

Renal Stones↗

NASA NTRS2016

Estimating the Rate of Occurrence of Renal Stones in Astronauts

Changes in urine chemistry, during and post flight, potentially increases the risk of renal stones in astronauts. Although much is known about the effects of space flight on urine chemistry, no inflight incidence of renal stones in US astronauts exists and the question "How much does this risk change with space flight?" remains difficult to accurately quantify. In this discussion, we tackle this question utilizing a combination of deterministic and probabilistic modeling that implements the physics behind free stone growth and agglomeration, speciation of urine chemistry and published observations of population renal stone incidences to estimate changes in the rate of renal stone presentation. The modeling process utilizes a Population Balance Equation based model developed in the companion IWS abstract by Kassemi et al. (2016) to evaluate the maximum growth and agglomeration potential from a specified set of urine chemistry values. Changes in renal stone occurrence rates are obtained from this model in a probabilistic simulation that interrogates the range of possible urine chemistries using Monte Carlo techniques. Subsequently, each randomly sampled urine chemistry undergoes speciation analysis using the well-established Joint Expert Speciation System (JESS) code to calculate critical values, such as ionic strength and relative supersaturation. The Kassemi model utilizes this information to predict the mean and maximum stone size. We close the assessment loop by using a transfer function that estimates the rate of stone formation from combining the relative supersaturation and both the mean and maximum free stone growth sizes. The transfer function is established by a simulation analysis which combines population stone formation rates and Poisson regression. Training this transfer function requires using the output of the aforementioned assessment steps with inputs from known non-stone-former and known stone-former urine chemistries. Established in a Monte Carlo system, the entire renal stone analysis model produces a probability distribution of the stone formation rate and an expected uncertainty in the estimate. The utility of this analysis will be demonstrated by showing the change in renal stone occurrence predicted by this method using urine chemistry distributions published in Whitson et al. 2009. A comparison to the model predictions to previous assessments of renal stone risk will be used to illustrate initial validation of the model.

gravitational physiology↗

NASA NTRS2014

Self-Pressurization and Spray Cooling Simulations of the Multipurpose Hydrogen Test Bed (MHTB) Ground-Based Experiment

This paper presents a CFD (computational fluid dynamics) model for simulating the self-pressurization of a large scale liquid hydrogen storage tank. In this model, the kinetics-based Schrage equation is used to account for the evaporative and condensing interfacial mass flows. Laminar and turbulent approaches to modeling natural convection in the tank and heat and mass transfer at the interface are compared. The flow, temperature, and interfacial mass fluxes predicted by these two approaches during tank self-pressurization are compared against each other. The ullage pressure and vapor temperature evolutions are also compared against experimental data obtained from the MHTB (Multipuprpose Hydrogen Test Bed) self-pressurization experiment. A CFD model for cooling cryogenic storage tanks by spraying cold liquid in the ullage is also presented. The Euler- Lagrange approach is utilized for tracking the spray droplets and for modeling interaction between the droplets and the continuous phase (ullage). The spray model is coupled with the VOF (volume of fluid) model by performing particle tracking in the ullage, removing particles from the ullage when they reach the interface, and then adding their contributions to the liquid. Droplet ullage heat and mass transfer are modeled. The flow, temperature, and interfacial mass flux predicted by the model are presented. The ullage pressure is compared with experimental data obtained from the MHTB spray bar mixing experiment. The results of the models with only droplet/ullage heat transfer and with heat and mass transfer between the droplets and ullage are compared.

cryogenic fluid storage↗

NASA NTRS2006

Two Phase Flow Modeling: Summary of Flow Regimes and Pressure Drop Correlations in Reduced and Partial Gravity

The purpose of this report is to provide a summary of state-of-the-art predictions for two-phase flows relevant to Advanced Life Support. We strive to pick out the most used and accepted models for pressure drop and flow regime predictions. The main focus is to identify gaps in predictive capabilities in partial gravity for Lunar and Martian applications. Following a summary of flow regimes and pressure drop correlations for terrestrial and zero gravity, we analyze the fully developed annular gas-liquid flow in a straight cylindrical tube. This flow is amenable to analytical closed form solutions for the flow field and heat transfer. These solutions, valid for partial gravity as well, may be used as baselines and guides to compare experimental measurements. The flow regimes likely to be encountered in the water recovery equipment currently under consideration for space applications are provided in an appendix.

Balasubramaniam, R.↗

NASA NTRS2005

Fluid-structural dynamics of ground-based and microgravity caloric tests

Microgravity caloric tests aboard the 1983 SpaceLab1 mission produced nystagmus results with an intensity comparable to those elicited during post- and pre- flight tests, thus contradicting the basic premise of Barany's convection hypothesis for caloric stimulation. In this work, we present a dynamic fluid structural analysis of the caloric stimulation of the lateral semicircular canal based on two simultaneous driving forces for the endolymphatic flow: natural convection driven by the temperature-dependent density variation in the bulk fluid and expansive convection caused by direct volumetric displacement of the endolymph during the thermal irrigation. Direct numerical simulations indicate that on earth, the natural convection mechanism is dominant. But in the microgravity environment of orbiting spacecraft, where buoyancy effects are mitigated, expansive convection becomes the sole mechanism for producing cupular displacement. A series of transient 1 g and microgravity case studies are presented to delineate the differences between the dynamics of the 1 g and microgravity endolymphatic flows. The impact of these different flow dynamics on the endolymph-cupula fluid-structural interactions is also analyzed based on the time evolutions of cupular displacement and velocity and the transcupular pressure differences.

Gravitation↗

NASA NTRS2001

Effect of Marangoni Convection Generated by Voids on Segregation During Low-G and 1-G Solidification

Solidification experiments, especially microgravity solidification experiments, are often compromised by the evolution of unwanted voids or bubbles in the melt. Although these voids and/or bubbles are highly undesirable, there is currently no effective means of preventing their formation or of eliminating their adverse effects, particularly during microgravity experiments. Marangoni convection caused by these voids can drastically change the transport processes in the melt. Recent microgravity experiments by Matthiesen (1) Andrews (2) and Fripp (3) are perfect examples of how voids and bubbles can affect the outcome of costly space experiments and significantly increase the level of difficulty in interpreting their results. Formation of bubbles have caused problems in microgravity experiments for a long time. Even in the early Skylab mission an unexpectedly large number of bubbles were detected in the four materials processing experiments reported by Papazian and Wilcox (4). They demonstrated that while during ground-based tests bubbles were seen to detach from the interface easily and float to the top of the melt, in low-gravity tests no detachment from the interface occurred and large voids were grown in the crystal. More recently, the lead-tin-telluride crystal growth experiment of Fripp et al.(3) flown aboard the USMP-3 mission has provided very interesting results. The purpose of the study was to investigate the effect of natural convection on the solidification process by growing the samples at different orientations with respect to the gravitational field. Large pores and voids were found in the three solid crystal samples processed in space. Post-growth characterization of the compositional profiles of the cells indicated considerable levels of mixing even in the sample grown in the hot-on-top stable configuration. The mixing was attributed to thermocapillary convection caused by the voids and bubbles which evolved during growth. Since the thermocapillary convection is orientation-independent, diffusion-controlled growth was not possible in any of the samples, even the top-heated one. These results are consistent with recent studies of thermocapillary convection generated by a bubble on a heated surface undertaken by Kassemi and Rashidnia (5-7) where it is numerically and experimentally shown that the thermocapillary flow generated by a bubble in a model fluid (silicone oil) can drastically modify the temperature field through vigorous mixing of the fluid around it, especially under microgravity conditions.

Kassemi, M.↗