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NASA NTRS2000

Thermocapillary Flow and Aggregation of Bubbles on a Solid Wall

During the electrolytic evolution of oxygen bubbles forming on a vertically oriented transparent tin oxide electrode, bubbles were found to be mutually attractive. The mechanism of the aggregation had never been explained satisfactorily until Guelcher et al. attributed it to thermocapillary flow. The gradient of surface tension of the liquid at the bubble's surface, which was established because of reaction heat and ohmic heat loss at the electrode wall, drives flow of the liquid adjacent to each bubble; the bubble "pumps" fluid along its surface away from the wall. Fluid flows toward the bubble to conserve mass and entrains nearby bubbles in the flow pattern. The same logic would apply when two bubbles of equal size are adjacent to each other on a warm wall. Each bubble drives thermocapillary flow and hence entrains the other in its flow pattern, which drives the aggregation. Our objective here is to perform experiments where the temperature gradient at the wall is well known and controlled. The theory can be quantitatively tested by studying aggregation of bubble pairs of equal size, and by varying system parameters such as temperature gradient, bubble size and fluid viscosity. The results are then compared with the theory in a quantitatively rigorous manner. We demonstrate that the theory without adjustable parameters is capable of quantitatively modeling the rate of aggregation of two bubbles. The equations governing the thermocapillary flow around a single stationary bubble on a heated or cooled wall in a semi-infinite domain were solved. Both Reynolds number and Marangoni number were much less than unity. The critical result is that liquid in the vicinity of a warm wall flows toward a stationary collector bubble. Consequently the thermocapillary flow around the stationary bubble entrains another bubble toward itself. The bubbles undergo hindered translation parallel to the wall with velocity U while the fluid flow field is described with u. Two velocities were equated by using a wall hindrance parameter q: U = qu [1] which shows the velocity of bubble is proportional to the entraining velocity. The hindrance parameter q can experimentally be measured independently. q can also be calculated by solving the equations of motion for a bubble translating parallel to a solid wall. The experimental cell is cylindrical with an ID of 10 cm and consists of a 1 cm deep main cell filled with silicone oil and flanked by two thermal reservoirs. The upper thermal reservoir was heated and the lower thermal reservoir was cooled so that the bubbles aggregate. Two types of silicone oil (eta = 0.02 and 0.50 Pa s) were used. Two equal sized air bubbles were injected into the cell with a syringe. The center-to-center distance of bubbles was observed through a microscope. Bubble radius ranged from 0.40 mm to 0.65 mm and the temperature gradients along with the cell ranged from 1400 to 5000 K/m. The bubbles aggregated when heat flows from the wall to the fluid. The velocities of bubbles were in the range of 1 - 10 microns/s. The separation r decreased more quickly when the temperature gradient was higher, bubble size was larger, and the oil viscosity was lower. r decreased more rapidly as the bubbles approached each other. Dimensionless time was arbitrarily set to be zero when the dimensionless center-to-center distance between the bubbles was 4. All the bubble trajectories fall onto one line, especially in the range of dimensionless distance from 4 to 3. This means the relative movement of the bubble pair is proportional to the temperature gradient and bubble size and it is inversely proportional to the viscosity of the oil. This result strongly suggests that the thermocapillary flow-based aggregation mechanism is correct. A value of q can be estimated by fitting the scaled data to Eq. [1]. A best fit value of q was obtained as q = 0.26 with a standard deviation of 0.03. Independent experimental results for q for a 0.5 mm radius bubble, give values of q in the range 0.11 to 0.23. The value of q obtained from solving the equations of motion reveals q has values in the range 0.23 - 0.30. Since the full scale of possible values of q is zero to one, the maximum deviation of independently determined values of q from the best fit value was 15% of this full scale. Thus reasonable quantitative agreement between theory and experiment has been obtained.

Kasumi, Hiroki↗
NASA NTRS2004

NASA Multidimensional Stirling Convertor Code Developed

A high-efficiency Stirling Radioisotope Generator (SRG) for use on potential NASA Space Science missions is being developed by the Department of Energy, Lockheed Martin, Stirling Technology Company, and the NASA Glenn Research Center. These missions may include providing spacecraft onboard electric power for deep space missions or power for unmanned Mars rovers. Glenn is also developing advanced technology for Stirling convertors, aimed at substantially improving the specific power and efficiency of the convertor and the overall power system. Performance and mass improvement goals have been established for second- and third-generation Stirling radioisotope power systems. Multiple efforts are underway to achieve these goals, both in house at Glenn and under various grants and contracts. These efforts include the development of a multidimensional Stirling computational fluid dynamics code, high-temperature materials, advanced controllers, an end-to-end system dynamics model, low-vibration techniques, advanced regenerators, and a lightweight convertor. Under a NASA grant, Cleveland State University (CSU) and its subcontractors, the University of Minnesota (UMN) and Gedeon Associates, have developed a twodimensional computer simulation of a CSUmod Stirling convertor. The CFD-ACE commercial software developed by CFD Research Corp. of Huntsville, Alabama, is being used. The CSUmod is a scaled version of the Stirling Technology Demonstrator Convertor (TDC), which was designed and fabricated by the Stirling Technology Company and is being tested by NASA. The schematic illustrates the structure of this model. Modeled are the fluid-flow and heat-transfer phenomena that occur in the expansion space, the heater, the regenerator, the cooler, the compression space, the surrounding walls, and the moving piston and displacer. In addition, the overall heat transfer, the indicated power, and the efficiency can be calculated. The CSUmod model is being converted to a two-dimensional model of the TDC at NASA Glenn. Validation of the multidimensional Stirling code is an important part of the grant effort. UMN has been generating data in an oscillating-flow test facility using two different test sections: a 90 turn and a cooler/regenerator/heater test section. CSU has created computational fluid dynamics models of both these test sections and has been making comparisons with the data, then improving their models to improve the agreement with the test data. CSU has also been using data available in the literature for code validation. UMN is now preparing to begin fabrication of a new 180 turn test section that will be more representative of certain portions of the Stirling engine geometry. Simulations to almost periodic steady state with the two-dimensional CSUmod model indicate that, to reach periodic steady state on a single 2-GHz desktop computer, 75 to 100 complete simulation cycles would be required and between 1 and 2 months of computer time. Therefore, Glenn has purchased the first 8 computers, of a 64-computer cluster, to be run in parallel to accelerate the simulation. On the basis of CFD Research Corp.'s experience with running the parallelized version of CFD-ACE on their clusters, we estimate that the complete 64-computer cluster will reduce simulation computing time by a factor of about 40. Plans are to continue development of these multidimensional Stirling codes and to use them to study the fluid-flow and heat-transfer phenomena that occur inside Stirling convertors. This is expected to lead to improved thermodynamic loss understanding, onedimensional design and performance codes, and engine performance.

Tew, Roy C.↗
NASA NTRS1998

WARP3D-Release 10.8: Dynamic Nonlinear Analysis of Solids using a Preconditioned Conjugate Gradient Software Architecture

This report describes theoretical background material and commands necessary to use the WARP3D finite element code. WARP3D is under continuing development as a research code for the solution of very large-scale, 3-D solid models subjected to static and dynamic loads. Specific features in the code oriented toward the investigation of ductile fracture in metals include a robust finite strain formulation, a general J-integral computation facility (with inertia, face loading), an element extinction facility to model crack growth, nonlinear material models including viscoplastic effects, and the Gurson-Tver-gaard dilatant plasticity model for void growth. The nonlinear, dynamic equilibrium equations are solved using an incremental-iterative, implicit formulation with full Newton iterations to eliminate residual nodal forces. The history integration of the nonlinear equations of motion is accomplished with Newmarks Beta method. A central feature of WARP3D involves the use of a linear-preconditioned conjugate gradient (LPCG) solver implemented in an element-by-element format to replace a conventional direct linear equation solver. This software architecture dramatically reduces both the memory requirements and CPU time for very large, nonlinear solid models since formation of the assembled (dynamic) stiffness matrix is avoided. Analyses thus exhibit the numerical stability for large time (load) steps provided by the implicit formulation coupled with the low memory requirements characteristic of an explicit code. In addition to the much lower memory requirements of the LPCG solver, the CPU time required for solution of the linear equations during each Newton iteration is generally one-half or less of the CPU time required for a traditional direct solver. All other computational aspects of the code (element stiffnesses, element strains, stress updating, element internal forces) are implemented in the element-by- element, blocked architecture. This greatly improves vectorization of the code on uni-processor hardware and enables straightforward parallel-vector processing of element blocks on multi-processor hardware.

Koppenhoefer, Kyle C.↗
NASA NTRS1995

Fossilization Processes in Thermal Springs

To create a comparative framework for the study of ancient examples, we have been carrying out parallel studies of the microbial biosedimentology, taphonomy and geochemistry of modem and sub-Recent thermal spring deposits. One goal of the research is the development of integrated litho- and taphofacies models for siliceous and travertline sinters. Thermal springs are regarded as important environments for the origin and early evolution of life on Earth, and we seek to utilize information from the fossil record to reconstruct the evolution of high temperature ecosystems. Microbial contributions to the fabric of thermal spring sinters occur when population growth rates keep pace with, or exceed rates of inorganic precipitation, allowing for the development of continuous biofilms or mats. In siliceous thermal springs, microorganisms are typically entombed while viable. Modes of preservation reflect the balance between rates of organic matter degradation, silica precipitation and secondary infilling. Subaerial sinters are initially quite porous and permeable and at temperatures higher than about 20 C, organic materials are usually degraded prior to secondary infilling of sinter frameworks. Thus, organically-preserved microfossils are rare and fossil information consists of characteristic biofabrics formed by the encrustation and underplating of microbial mat surfaces. This probably accounts for the typically low total organic carbon values observed in thermal spring deposits. In mid-temperature, (approx. 35 - 59 C) ponds and outflows, the surface morphology of tufted Phormidium mats is preserved through mat underplating by thin siliceous: crusts. Microbial taxes lead to clumping of ceils and/or preferred filament orientations that together define higher order composite fabrics in thermal spring stromatolites (e.g. network, coniform, and palisade). At lower temperatures (less than 35 C), Calothrix mats cover shallow terracette pools forming flat carpets or pustular surfaces that produce palisade and "shrub" fabrics, respectively. At finer scales, composite fabrics are seen to consist distinctive associations of microstructures formed by the encrustation of individual cells and filaments. Composite fabrics survive the diagenetic transitions from primary opaline silica to quartz and are known from subaerial thermal spring deposits as old as Lower Carboniferous. However, fossil microorganisms tend to be rare in older deposits, and are usually preserved only where cells or sheaths have been stained by iron oxides. In subaqueous mineralizing springs at lower temperatures, early infilling leads to a more rapid and complete reduction in porosity and permeability. This process, along with the slower rates of microbial degradation at lower temperatures, creates a more favorable situation for organic matter preservation. Application of this taphonomic model to the Rhynie Chert, previously interpreted as subaerial, suggest it was probably deposited in a subaqueous spring setting at lower temperatures.

Farmer, Jack D.↗
NASA NTRS1997

Peptide Folding and Translocation Across the Water-Membrane Interface

The ability of small peptides to organize at aqueous interfaces was examined by performing a series of large-scale, molecular dynamics computer simulations of several peptides composed of two amino acids, nonpolar leucine (L) and polar glutamine (Q). The peptides differed in size and sequence of the amino acids. Studies on dipeptides LL, LQ, QL and QQ were extended to two heptamers, LQQLLQL and LQLQLQL, designed to maximize interfacial stability of an alpha-helix and a beta-strand, respectively, by exposing polar side chains to water and nonpolar side chains to a nonpolar phase. Finally, a transition of an undecamer, composed entirely of leucine residues, from a disordered structure in water to an alpha-helix in a nonpolar phase representing the interior of the membrane was investigated. Complete folding of a peptide in solution was accomplished for the first time in computer simulations. The simulations revealed several basic principles governing the sequence-dependent organization of peptides at interfaces. Short peptides tend to accumulate at interfaces and acquire ordered structures, providing that they have a proper sequence of polar and nonpolar amino acids. The dominant factor determining the interfacial structure of peptides is the hydrophobic effect, which is manifested at aqueous interfaces as a tendency for polar and nonpolar groups of the solute to segregate into the aqueous and nonpolar phases, respectively. If peptides consist of nonpolar residue's only, they become inserted into the nonpolar phase. As demonstrated by the example of the leucine undecamer, such peptides fold into an alpha-helix as they partition into the nonpolar medium. The folding proceeds through an intermediate, called 3-10-helix, which remains in equilibrium with the alpha-helix. Once in the nonpolar environment, the peptides can readily change their orientation with respect to the interface from parallel to perpendicular, especially in response to local electric fields. The ability of nonpolar peptides to modify both the structure and orientation with respect to the interface from parallel to perpendicular, especially in response to local electric fields. The ability of nonpolar peptides to modify both the structure and orientation with changing external conditions may have provided a simple mechanism of transmitting signals from the environment to the interior of a cell.

Pohorille, Andrew↗
NASA NTRSDate not supplied

A Modeling Approach to Support Changeability Analysis and Management of Earth Observation Portfolios

Earth observing (EO) mission portfolios provide data on many geophysical parameters that collectively inform our understanding of the Earth system. To observe large-scale climate trends, it is important to collect data on many parameters over time. However, gaps may occur between missions due to formulation complexity, development delays, and uncertain events in operations. These gaps may impact the ability to provide sustained measurements. Developing a balanced EO mission portfolio is key to supporting study of the Earth system. Yet, decision-making at the portfolio level is a complex task because missions often address multiple parameters. Currently, the likelihood of data gaps is often assessed for an individual parameter, but decisions and events can impact data collection for many parameters. This poster introduces a modeling approach that supports management of the many parameter impacts of decisions and uncertain events. The approach provides a foundation for analyzing changeability in EO mission portfolios. Changeability analysis provides insight into a portfolio’s sensitivity to changes caused by decisions or uncertain events. The model is developed to analyze two aspects of changeability, robustness and flexibility, in EO mission portfolios. In context of these portfolios, the authors define robustness as a portfolio’s ability to provide sustained measurements despite future uncertainties, and they define flexibility as the availability of decision alternatives that contribute to parameter coverage at little detriment to the rest of the portfolio. The proposed model characterizes a portfolio’s sensitivity to change by capturing mission-parameter interconnectivity and redundancy in parameter coverage. The model can be analyzed to identify events that can create substantial gaps, thereby revealing focus areas for mitigation efforts. The model can also be analyzed to identify gap mitigation decisions that may improve parameter coverage with little detriment to the rest of the portfolio, thereby revealing favorable pathways for portfolio improvement. Developing a process for identifying these threats and opportunities will be the focus of future work. A parallel poster proposes a standard for visualizing and communicating portfolio-level impacts of decisions and uncertain events.

Lindsey Jacobson↗
NASA NTRS2004

CMOS VLSI Active-Pixel Sensor for Tracking

An architecture for a proposed active-pixel sensor (APS) and a design to implement the architecture in a complementary metal oxide semiconductor (CMOS) very-large-scale integrated (VLSI) circuit provide for some advanced features that are expected to be especially desirable for tracking pointlike features of stars. The architecture would also make this APS suitable for robotic- vision and general pointing and tracking applications. CMOS imagers in general are well suited for pointing and tracking because they can be configured for random access to selected pixels and to provide readout from windows of interest within their fields of view. However, until now, the architectures of CMOS imagers have not supported multiwindow operation or low-noise data collection. Moreover, smearing and motion artifacts in collected images have made prior CMOS imagers unsuitable for tracking applications. The proposed CMOS imager (see figure) would include an array of 1,024 by 1,024 pixels containing high-performance photodiode-based APS circuitry. The pixel pitch would be 9 m. The operations of the pixel circuits would be sequenced and otherwise controlled by an on-chip timing and control block, which would enable the collection of image data, during a single frame period, from either the full frame (that is, all 1,024 ~ 1,024 pixels) or from within as many as 8 different arbitrarily placed windows as large as 8 by 8 pixels each. A typical prior CMOS APS operates in a row-at-a-time ( grolling-shutter h) readout mode, which gives rise to exposure skew. In contrast, the proposed APS would operate in a sample-first/readlater mode, suppressing rolling-shutter effects. In this mode, the analog readout signals from the pixels corresponding to the windows of the interest (which windows, in the star-tracking application, would presumably contain guide stars) would be sampled rapidly by routing them through a programmable diagonal switch array to an on-chip parallel analog memory array. The diagonal-switch and memory addresses would be generated by the on-chip controller. The memory array would be large enough to hold differential signals acquired from all 8 windows during a frame period. Following the rapid sampling from all the windows, the contents of the memory array would be read out sequentially by use of a capacitive transimpedance amplifier (CTIA) at a maximum data rate of 10 MHz. This data rate is compatible with an update rate of almost 10 Hz, even in full-frame operation

Pain, Bedabrata↗
NASA NTRS2012

Can Terrestrial Microbes Grow on Mars?

The theme for AbSciCon 2012 is "Exploring Life: Past and Present, Near and Far." The conference will address our current understanding of life - from processes at the molecular level to those which operate at planetary scales. Studying these aspects of life on Earth provides an essential platform from which to examine the potential for life on other worlds, both within our solar system and beyond. Mars exhibits a variety of extreme environments characterized by high UV and ionizing radiation flux, low pressure anoxic atmosphere, scarce or absent liquid water, extreme low temperatures, etc. The ability of terrestrial microorganisms to survive and adapt to the Mars environment has profound implications for astrobiology, planetary protection, and Mars life detection missions. At the NASA Ames Synthetic Biology Initiative, we believe that synthetic biology has the potential to revolutionize human space exploration. As such, the initiative is dedicated to applying the tools and techniques of synthetic biology to space exploration and astrobiology. Biological solutions will be invaluable for space exploration because they are not resource intensive, and they are versatile and self-renewing. An understanding of how to work with DNA in an unfavorable environment is paramount to utilizing biological tools on space missions. Furthermore, the ability to adjust life to the parameters of Mars is vital both to discovering what life on Mars might look like, and to using biological tools under such conditions. As a first step, we need an energy-efficient, low cost means of transporting, storing, and protecting genomic DNA, DNA parts, and whole microbial strains. Our goal is to develop and demonstrate viable and superior alternatives to standard DNA storage methods, which can be optimized to the conditions of space exploration, using synthetic biology as a tool. This includes protocols and kit designs for easy and repeatable DNA and strain recovery from protective storage conditions. We are constructing newly engineered genetic parts for different valuable host organisms, designed to increased long-term survival and functional retention. These methods should be applied for DNA and strain storage and transportation. In parallel, we seek inspiration from natural organisms that have developed means for survival in extreme environmental conditions. We are utilizing novel techniques for analysis of lipid biomarkers in the Antarctic Dry Valleys in order to identify resident microbes in the Antarctic soil and permafrost, as well as biomarker fossils of organisms that survived in the valleys in ages past. Through the identification of these life forms, we hope to understand and draw on new biological tools and strategies for synthetic biological applications on Mars.

Rothschild, Lynn↗
NASA NTRS2013

The Antarctic Search for Meteorites: A Model for Deep Space Exploration

In an era of shrinking buying power and reduced flight opportunities, NASA must extract the greatest possible value from all sources of insight into the future of human space exploration. Antarctica is one such source. The history of Antarctic exploration has many political and technical parallels with the development of space, and Antarctica's remoteness and harsh climate make it an excellent proxy for space (e.g., [1,2]). Links between exploration of space and of the Antarctic date back to the International Geophysical Year of 1957-1958, which saw both the launch of Sputnik 1 and the establishment of a station at the South Pole. The Antarctic Search for Meteorites (ANSMET) is an annual expedition to the south polar plateau to collect meteorites. Although its intent is not to simulate a space mission, the handful of astronauts who have participated in ANSMET agree that it is very similar to a long-duration space flight. Independently, NASA and other space agencies have simulated deep space exploration missions in "analog" activities at remote field sites on Earth (e.g., [3]). These include NASA Extreme Environment Mission Operations (NEEMO) [4,5], Desert Research And Technology Studies (Desert RATS) [6,7], and the Pavilion Lake Research Project (PLRP or simply Pavilion Lake) [8]. This report focuses on NEEMO, Desert RATS, and PLRP because of the author's firsthand experience with them. Other noteworthy analogs, such as the arctic Haughton Mars Project and the European Space Agency's underground Cooperative Adventure for Valuing and Exercising human behavior and performance Skills (CAVES), are not treated here. NASA analogs often include fully staffed control centers, astronauts serving as crew, and realistic mission timelines lasting one to two weeks. Analogs have provided key insights into system architectures and operational concepts for the future human exploration of deep space. They have pioneered techniques for human communication with significant speed-of-light delays, for conducting spacewalks on natural objects with negligible surface gravity, and for empowering exploration crews to work with reduced dependence on a ground control center. They have field-tested dozens of emerging technologies including spacewalking tools and full-scale prototype vehicles and habitats. They have provided valuable experience for astronauts preparing for their first space flight, and for flown crewmembers who will take command roles on later flights. Some analogs, especially PLRP, have connected observers in the field with science teams in remotely located control centers to produce high-quality, publishable scientific results. The analogs have accomplished all of this at a tiny fraction of the cost of an actual space flight. This report treats ANSMET as space flight analog. The chapter following this introduction describes ANSMET in depth. The report then presents data on logistics and crew considerations that may be useful for developers of future human space exploration missions. It offers detailed comparisons between ANSMET and past, present, and future space flights on the Space Shuttle, the International Space Station (ISS), and a proposed Mars mission. Those comparisons are intended to complement the work of Eppler [2], who compares ANSMET to the Apollo moon flights. This report also compares ANSMET with the Desert RATS, NEEMO, and PLRP analogs. It then presents observations and makes recommendations related to ANSMET's value as a simulated space mission. The report ends with a short conclusion. The remainder of this introductory chapter provides background material to help readers interpret the rest of the report. It gives brief overviews of Space Shuttle and ISS missions along with information on a notional future human flight to Mars. It also presents the general features of three of NASA's space flight "analog" projects. With those points of reference in place, the chapter concludes with an overview of ANSMET.

Love, Stanley G.↗
NASA NTRS2002

Shadowgraph Study of Gradient Driven Fluctuations

A fluid or fluid mixture, subjected to a vertical temperature and/or concentration gradient in a gravitational field, exhibits greatly enhanced light scattering at small angles. This effect is caused by coupling between the vertical velocity fluctuations due to thermal energy and the vertically varying refractive index. Physically, small upward or downward moving regions will be displaced into fluid having a refractive index different from that of the moving region, thus giving rise to the enhanced scattering. The scattered intensity is predicted to vary with scattering wave vector q, as q(sup -4), for sufficiently large q, but the divergence is quenched by gravity at small q. In the absence of gravity, the long wavelength fluctuations responsible for the enhanced scattering are predicted to grow until limited by the sample dimensions. It is thus of interest to measure the mean-squared amplitude of such fluctuations in the microgravity environment for comparison with existing theory and ground based measurements. The relevant wave vectors are extremely small, making traditional low-angle light scattering difficult or impossible because of stray elastically scattered light generated by optical surfaces. An alternative technique is offered by the shadowgraph method, which is normally used to visualize fluid flows, but which can also serve as a quantitative tool to measure fluctuations. A somewhat novel shadowgraph apparatus and the necessary data analysis methods will be described. The apparatus uses a spatially coherent, but temporally incoherent, light source consisting of a super-luminescent diode coupled to a single-mode optical fiber in order to achieve extremely high spatial resolution, while avoiding effects caused by interference of light reflected from the various optical surfaces that are present when using laser sources. Results obtained for a critical mixture of aniline and cyclohexane subjected to a vertical temperature gradient will be presented. The sample was confined between two horizontal parallel sapphire plates with a vertical spacing of 1 mm. The temperatures of the sapphire plates were controlled by independent circulating water loops that used Peltier devices to add or remove heat from the room air as required. For a mixture with a temperature gradient, two effects are involved in generating the vertical refractive index gradient, namely thermal expansion and the Soret effect, which generates a concentration gradient in response to the applied temperature gradient. For the aniline/cyclohexane system, the denser component (aniline) migrates toward the colder surface. Consequently, when heating from above, both effects result in the sample density decreasing with altitude and are stabilizing in the sense that no convective motion occurs regardless of the magnitude of the applied temperature gradient. The Soret effect is strong near a binary liquid critical point, and thus the dominant effect is due to the induced concentration gradient. The results clearly show the divergence at low q and the predicted gravitational quenching. Results obtained for different applied temperature gradients at varying temperature differences from the critical temperature, clearly demonstrate the predicted divergence of the thermal diffusion ratio. Thus, the more closely the critical point is approached, the smaller becomes the temperature gradient required to generate the same signal. Two different methods have been used to generate pure concentration gradients. In the first, a sample cell was filled with a single fluid, ethylene glycol, and a denser miscible fluid, water, was added from below thus establishing a sharp interface to begin the experiment. As time went on the two fluids diffused into each other, and large amplitude fluctuations were clearly observed at low q. The effects of gravitational quenching were also evident. In the second method, the aniline/cyclohexane sample was used, and after applying a vertical temperature gradient for several hours, the top and bottom temperatures were set equal and the thermal gradient died on a time scale of seconds, leaving the Soret induced concentration gradient in place. Again, large-scale fluctuations were observed and died away slowly in amplitude as diffusion destroyed the initial concentration gradient.

Cannell, David↗
NASA NTRSDate not supplied

Modeling and Simulation of Tank Pressure Control using Zero-Boil Off Active Thermal Control for LOXSAT Technology Demonstration Mission

To-date, research and modeling of cryogenic fluid management technologies (CFM) for spaceflight has been limited to ground tests, short-duration zero-g simulations (e.g. drop towers), and small-scale experiments on-orbit. There has not been a large-scale flight demonstration of a flight-like system. As future NASA missions to take humans further from Earth will require large, in-space cryogenic propulsion vehicles, it is imperative to begin collecting flight data for these systems to accurately model and design future vehicles. To meet this goal, NASA awarded tipping point technology demonstration awards to Eta Space, Lockheed Martin, Space Exploration Technologies (SpaceX), and United Launch Alliance (ULA) to demonstrate on-orbit storage and transfer of cryogenic propellant. For its award, Eta Space is developing LOXSAT-1. It is a small satellite that will be launched on a Rocket Lab Electron rocket. The spacecraft consists of a Rocket Lab Photon spacecraft bus with a primary payload of a spherical liquid oxygen (LOX) storage tank with thermodynamic control systems. The primary objective of the mission is to demonstrate zero-boil-off storage of liquid oxygen. To accomplish this objective, the payload is equipped with an active thermal control system fluid loop that consists of propellant management device (PMD), positive-displacement pump, heat exchanger connected to a cryocooler, and a spray bar mixing injector. When the fluid loop is operating, fluid is drawn from the tank by the PMD and pumped through the heat exchanger, lowering the fluid temperature below the fluid temperature in the tank. This subcooled liquid is then injected back into the tank through the spray bar. The subcooled injected liquid has two effects. If it is sprayed into the ullage space, the injected liquid will form into jets or droplets and exchange heat with the ullage gas. This will cool and condense the gas, reducing the pressure in the tank. Additionally, the liquid that is not sprayed through the ullage, as well as any remaining liquid spray from the ullage, will rejoin the liquid mass of the tank, lowering the bulk temperature of the liquid. These combines effects provide for zero-boil off pressure control by lowering the tank pressure and the liquid saturation pressure simultaneously, ensuring the liquid stays subcooled. To model these complex mechanics and predict the performance of the active thermal control system, NASA is providing Eta Space with 3 parallel models of the tank. The approach of providing 3 different models allows for cross-checking and comparisons between the three to better understand how different modeling assumptions and selection semi-empirical factors affects the modeling result. Additionally, developing 3 models provides three different schemes for numerical simulation, providing confidence that results depict real physical phenomenon and not numerical quirks of the program. Within the tank thermodynamics, there are two primary areas of heat transfer we concern ourselves with: the heat transfer between the ullage space and the droplet spray, and between the ullage space and bulk liquid. For the droplet heat transfer, there are multiple sets of assumptions that can be made and correlations that can be used. Currently, two working models - the TankSIM model and Easy5 model – provide for an overview of the different approaches available. The TankSIM model and Easy5 model use two different models for droplet heating and evaporation that illustrate how the models use different types of mechanisms to arrive at the same answer. For the TankSIM model, droplets are treated as spheres of constant radius. Heat is transferred from the ullage to the droplet and warms the droplet until it reaches saturation, then the droplet begins evaporating and reducing its radius and mass. To calculate the heat transfer coefficient between the droplet and ullage, the Ranz-Marshall correlation is used. To determine the number of droplets in the ullage, a resident mass approach is used. This approach averages the number of droplets such that residuals at the start-up and shut-off of the spray bar cancel out. This same approach is used in the Easy5 model. The GFSSP model implements a linked list to track individual droplet “nodes” within the model. For the Easy5 model, the droplet is assumed to have an interface at a temperature equal to the saturation temperature corresponding to the pressure of the gas phase. The heat transfer from the gas to the interface and the interface to the droplet bulk is then calculated, and the net mass transfer between the droplet and interface is determined by performing an energy balance across the interface. For the gas side of the interface, the Ranz-Marshall correlation is used. For the liquid side of the interface, a variety of correlations were tried, including Kronig and Brink (1950) and effective conductivity models. As a result of these assumptions, the Easy5 model currently predicts faster depressurization, as at saturated vapor conditions, the heat transfer coeffect on the liquid side for the Easy5 model is greater than the heat transfer coefficient predicted by Ranz-Marshall used in the TankSIM code. This greater heat flux translates into faster condensation of the saturated ullage gas. At the bulk liquid to ullage interface, the models are in much closer agreement. Both models model the ullage as a sphere centered within the bulk liquid in the tank, and both use the energy-jumping boundary condition to model heat and mass transfer across the interface. There are slight differences in how the interface temperature is calculated, however. The Easy5 model assumes the temperature of the interface is equal to the saturation temperature associated with the pressure of the gas phase. The TankSIM model calculates this temperature with Alabovskii’s equation, which provides a correction factor for interface temperatures. Analysis tasks are focused on determining rates of depressurization within the tank during active cooling operation. To maintain net positive suction head at the pump inlet, the tank pressure cannot fall faster than the saturation pressure associated with the temperature of the bulk liquid. Additionally, there is interest in analyzing the performance of the loop at different pump speeds and cryocooler input powers. Adjusting the flowrate affects both the performance of the heat exchanger between the cryocooler and pumped liquid, and the heat transfer between the droplet spray and the ullage. Ideally, a pump speed and cryocooler power can be selected that will allow the tank to operate in zero-boil-off mode with a very narrow range of storage pressure.

Cameron J. Hines↗
NASA NTRSDate not supplied

Modeling and Simulation of Tank Pressure Control using Zero-Boil Off Active Thermal Control for LOXSAT Technology Demonstration Mission

To-date, research and modeling of cryogenic fluid management technologies (CFM) for spaceflight has been limited to ground tests, short-duration zero-g simulations (e.g. drop towers), and small-scale experiments on-orbit. There has not been a large-scale flight demonstration of a flight-like system. As future NASA missions to take humans further from Earth will require large, in-space cryogenic propulsion vehicles, it is imperative to begin collecting flight data for these systems to accurately model and design future vehicles. To meet this goal, NASA awarded tipping point technology demonstration awards to Eta Space, Lockheed Martin, Space Exploration Technologies (SpaceX), and United Launch Alliance (ULA) to demonstrate on-orbit storage and transfer of cryogenic propellant. For its award, Eta Space is developing LOXSAT-1. It is a small satellite that will be launched on a Rocket Lab Electron rocket. The spacecraft consists of a Rocket Lab Photon spacecraft bus with a primary payload of a spherical liquid oxygen (LOX) storage tank with thermodynamic control systems. The primary objective of the mission is to demonstrate zero-boil-off storage of liquid oxygen. To accomplish this objective, the payload is equipped with an active thermal control system fluid loop that consists of propellant management device (PMD), positive-displacement pump, heat exchanger connected to a cryocooler, and a spray bar mixing injector. When the fluid loop is operating, fluid is drawn from the tank by the PMD and pumped through the heat exchanger, lowering the fluid temperature below the fluid temperature in the tank. This subcooled liquid is then injected back into the tank through the spray bar. The subcooled injected liquid has two effects. If it is sprayed into the ullage space, the injected liquid will form into jets or droplets and exchange heat with the ullage gas. This will cool and condense the gas, reducing the pressure in the tank. Additionally, the liquid that is not sprayed through the ullage, as well as any remaining liquid spray from the ullage, will rejoin the liquid mass of the tank, lowering the bulk temperature of the liquid. These combines effects provide for zero-boil off pressure control by lowering the tank pressure and the liquid saturation pressure simultaneously, ensuring the liquid stays subcooled. To model these complex mechanics and predict the performance of the active thermal control system, NASA is providing Eta Space with 3 parallel models of the tank. The approach of providing 3 different models allows for cross-checking and comparisons between the three to better understand how different modeling assumptions and selection semi-empirical factors affects the modeling result. Additionally, developing 3 models provides three different schemes for numerical simulation, providing confidence that results depict real physical phenomenon and not numerical quirks of the program. Within the tank thermodynamics, there are two primary areas of heat transfer we concern ourselves with: the heat transfer between the ullage space and the droplet spray, and between the ullage space and bulk liquid. For the droplet heat transfer, there are multiple sets of assumptions that can be made and correlations that can be used. Currently, two working models - the TankSIM model and Easy5 model – provide for an overview of the different approaches available. The TankSIM model and Easy5 model use two different models for droplet heating and evaporation that illustrate how the models use different types of mechanisms to arrive at the same answer. For the TankSIM model, droplets are treated as spheres of constant radius. Heat is transferred from the ullage to the droplet and warms the droplet until it reaches saturation, then the droplet begins evaporating and reducing its radius and mass. To calculate the heat transfer coefficient between the droplet and ullage, the Ranz-Marshall correlation is used. To determine the number of droplets in the ullage, a resident mass approach is used. This approach averages the number of droplets such that residuals at the start-up and shut-off of the spray bar cancel out. This same approach is used in the Easy5 model. The GFSSP model implements a linked list to track individual droplet “nodes” within the model. For the Easy5 model, the droplet is assumed to have an interface at a temperature equal to the saturation temperature corresponding to the pressure of the gas phase. The heat transfer from the gas to the interface and the interface to the droplet bulk is then calculated, and the net mass transfer between the droplet and interface is determined by performing an energy balance across the interface. For the gas side of the interface, the Ranz-Marshall correlation is used. For the liquid side of the interface, a variety of correlations were tried, including Kronig and Brink (1950) and effective conductivity models. As a result of these assumptions, the Easy5 model currently predicts faster depressurization, as at saturated vapor conditions, the heat transfer coeffect on the liquid side for the Easy5 model is greater than the heat transfer coefficient predicted by Ranz-Marshall used in the TankSIM code. This greater heat flux translates into faster condensation of the saturated ullage gas. At the bulk liquid to ullage interface, the models are in much closer agreement. Both models model the ullage as a sphere centered within the bulk liquid in the tank, and both use the energy-jumping boundary condition to model heat and mass transfer across the interface. There are slight differences in how the interface temperature is calculated, however. The Easy5 model assumes the temperature of the interface is equal to the saturation temperature associated with the pressure of the gas phase. The TankSIM model calculates this temperature with Alabovskii’s equation, which provides a correction factor for interface temperatures. Analysis tasks are focused on determining rates of depressurization within the tank during active cooling operation. To maintain net positive suction head at the pump inlet, the tank pressure cannot fall faster than the saturation pressure associated with the temperature of the bulk liquid. Additionally, there is interest in analyzing the performance of the loop at different pump speeds and cryocooler input powers. Adjusting the flowrate affects both the performance of the heat exchanger between the cryocooler and pumped liquid, and the heat transfer between the droplet spray and the ullage. Ideally, a pump speed and cryocooler power can be selected that will allow the tank to operate in zero-boil-off mode with a very narrow range of storage pressure.

zero boil-off↗
NASA NTRSDate not supplied

Modeling and Simulation of Tank Pressure Control using Zero-Boil Off Active Thermal Control for LOXSAT Technology Demonstration Mission

To-date, research and modeling of cryogenic fluid management technologies (CFM) for spaceflight has been limited to ground tests, short-duration zero-g simulations (e.g. drop towers), and small-scale experiments on-orbit. There has not been a large-scale flight demonstration of a flight-like system. As future NASA missions to take humans further from Earth will require large, in-space cryogenic propulsion vehicles, it is imperative to begin collecting flight data for these systems to accurately model and design future vehicles. To meet this goal, NASA awarded tipping point technology demonstration awards to Eta Space, Lockheed Martin, Space Exploration Technologies (SpaceX), and United Launch Alliance (ULA) to demonstrate on-orbit storage and transfer of cryogenic propellant. For its award, Eta Space is developing LOXSAT-1. It is a small satellite that will be launched on a Rocket Lab Electron rocket. The spacecraft consists of a Rocket Lab Photon spacecraft bus with a primary payload of a spherical liquid oxygen (LOX) storage tank with thermodynamic control systems. The primary objective of the mission is to demonstrate zero-boil-off storage of liquid oxygen. To accomplish this objective, the payload is equipped with an active thermal control system fluid loop that consists of propellant management device (PMD), positive-displacement pump, heat exchanger connected to a cryocooler, and a spray bar mixing injector. When the fluid loop is operating, fluid is drawn from the tank by the PMD and pumped through the heat exchanger, lowering the fluid temperature below the fluid temperature in the tank. This subcooled liquid is then injected back into the tank through the spray bar. The subcooled injected liquid has two effects. If it is sprayed into the ullage space, the injected liquid will form into jets or droplets and exchange heat with the ullage gas. This will cool and condense the gas, reducing the pressure in the tank. Additionally, the liquid that is not sprayed through the ullage, as well as any remaining liquid spray from the ullage, will rejoin the liquid mass of the tank, lowering the bulk temperature of the liquid. These combines effects provide for zero-boil off pressure control by lowering the tank pressure and the liquid saturation pressure simultaneously, ensuring the liquid stays subcooled. To model these complex mechanics and predict the performance of the active thermal control system, NASA is providing Eta Space with 3 parallel models of the tank. The approach of providing 3 different models allows for cross-checking and comparisons between the three to better understand how different modeling assumptions and selection semi-empirical factors affects the modeling result. Additionally, developing 3 models provides three different schemes for numerical simulation, providing confidence that results depict real physical phenomenon and not numerical quirks of the program. Within the tank thermodynamics, there are two primary areas of heat transfer we concern ourselves with: the heat transfer between the ullage space and the droplet spray, and between the ullage space and bulk liquid. For the droplet heat transfer, there are multiple sets of assumptions that can be made and correlations that can be used. Currently, two working models - the TankSIM model and Easy5 model – provide for an overview of the different approaches available. The TankSIM model and Easy5 model use two different models for droplet heating and evaporation that illustrate how the models use different types of mechanisms to arrive at the same answer. For the TankSIM model, droplets are treated as spheres of constant radius. Heat is transferred from the ullage to the droplet and warms the droplet until it reaches saturation, then the droplet begins evaporating and reducing its radius and mass. To calculate the heat transfer coefficient between the droplet and ullage, the Ranz-Marshall correlation is used. To determine the number of droplets in the ullage, a resident mass approach is used. This approach averages the number of droplets such that residuals at the start-up and shut-off of the spray bar cancel out. This same approach is used in the Easy5 model. The GFSSP model implements a linked list to track individual droplet “nodes” within the model. For the Easy5 model, the droplet is assumed to have an interface at a temperature equal to the saturation temperature corresponding to the pressure of the gas phase. The heat transfer from the gas to the interface and the interface to the droplet bulk is then calculated, and the net mass transfer between the droplet and interface is determined by performing an energy balance across the interface. For the gas side of the interface, the Ranz-Marshall correlation is used. For the liquid side of the interface, a variety of correlations were tried, including Kronig and Brink (1950) and effective conductivity models. As a result of these assumptions, the Easy5 model currently predicts faster depressurization, as at saturated vapor conditions, the heat transfer coeffect on the liquid side for the Easy5 model is greater than the heat transfer coefficient predicted by Ranz-Marshall used in the TankSIM code. This greater heat flux translates into faster condensation of the saturated ullage gas. At the bulk liquid to ullage interface, the models are in much closer agreement. Both models model the ullage as a sphere centered within the bulk liquid in the tank, and both use the energy-jumping boundary condition to model heat and mass transfer across the interface. There are slight differences in how the interface temperature is calculated, however. The Easy5 model assumes the temperature of the interface is equal to the saturation temperature associated with the pressure of the gas phase. The TankSIM model calculates this temperature with Alabovskii’s equation, which provides a correction factor for interface temperatures. Analysis tasks are focused on determining rates of depressurization within the tank during active cooling operation. To maintain net positive suction head at the pump inlet, the tank pressure cannot fall faster than the saturation pressure associated with the temperature of the bulk liquid. Additionally, there is interest in analyzing the performance of the loop at different pump speeds and cryocooler input powers. Adjusting the flowrate affects both the performance of the heat exchanger between the cryocooler and pumped liquid, and the heat transfer between the droplet spray and the ullage. Ideally, a pump speed and cryocooler power can be selected that will allow the tank to operate in zero-boil-off mode with a very narrow range of storage pressure.

zero boil-off↗
NASA NTRSDate not supplied

Modeling and Simulation of Tank Pressure Control using Zero-Boiloff Active Thermal Control for LOXSAT Technology Demonstration Mission

To-date, research and modeling of cryogenic fluid management technologies (CFM) for spaceflight has been limited to ground tests, short-duration zero-g simulations (e.g. drop towers), and small-scale experiments on-orbit. There has not been a large-scale flight demonstration of a flight-like system. As future NASA missions to take humans further from Earth will require large, in-space cryogenic propulsion vehicles, it is imperative to begin collecting flight data for these systems to accurately model and design future vehicles. To meet this goal, NASA awarded tipping point technology demonstration awards to Eta Space, Lockheed Martin, Space Exploration Technologies (SpaceX), and United Launch Alliance (ULA) to demonstrate on-orbit storage and transfer of cryogenic propellant. For its award, Eta Space is developing LOXSAT-1. It is a small satellite that will be launched on a Rocket Lab Electron rocket. The spacecraft consists of a Rocket Lab Photon spacecraft bus with a primary payload of a spherical liquid oxygen (LOX) storage tank with thermodynamic control systems. The primary objective of the mission is to demonstrate zero-boil-off storage of liquid oxygen. To accomplish this objective, the payload is equipped with an active thermal control system fluid loop that consists of propellant management device (PMD), positive-displacement pump, heat exchanger connected to a cryocooler, and a spray bar mixing injector. When the fluid loop is operating, fluid is drawn from the tank by the PMD and pumped through the heat exchanger, lowering the fluid temperature below the fluid temperature in the tank. This subcooled liquid is then injected back into the tank through the spray bar. The subcooled injected liquid has two effects. If it is sprayed into the ullage space, the injected liquid will form into jets or droplets and exchange heat with the ullage gas. This will cool and condense the gas, reducing the pressure in the tank. Additionally, the liquid that is not sprayed through the ullage, as well as any remaining liquid spray from the ullage, will rejoin the liquid mass of the tank, lowering the bulk temperature of the liquid. These combines effects provide for zero-boil off pressure control by lowering the tank pressure and the liquid saturation pressure simultaneously, ensuring the liquid stays subcooled. To model these complex mechanics and predict the performance of the active thermal control system, NASA is providing Eta Space with 3 parallel models of the tank. The approach of providing 3 different models allows for cross-checking and comparisons between the three to better understand how different modeling assumptions and selection semi-empirical factors affects the modeling result. Additionally, developing 3 models provides three different schemes for numerical simulation, providing confidence that results depict real physical phenomenon and not numerical quirks of the program. Within the tank thermodynamics, there are two primary areas of heat transfer we concern ourselves with: the heat transfer between the ullage space and the droplet spray, and between the ullage space and bulk liquid. For the droplet heat transfer, there are multiple sets of assumptions that can be made and correlations that can be used. Currently, two working models - the TankSIM model and Easy5 model – provide for an overview of the different approaches available. The TankSIM model and Easy5 model use two different models for droplet heating and evaporation that illustrate how the models use different types of mechanisms to arrive at the same answer. For the TankSIM model, droplets are treated as spheres of constant radius. Heat is transferred from the ullage to the droplet and warms the droplet until it reaches saturation, then the droplet begins evaporating and reducing its radius and mass. To calculate the heat transfer coefficient between the droplet and ullage, the Ranz-Marshall correlation is used. To determine the number of droplets in the ullage, a resident mass approach is used. This approach averages the number of droplets such that residuals at the start-up and shut-off of the spray bar cancel out. This same approach is used in the Easy5 model. The GFSSP model implements a linked list to track individual droplet “nodes” within the model. For the Easy5 model, the droplet is assumed to have an interface at a temperature equal to the saturation temperature corresponding to the pressure of the gas phase. The heat transfer from the gas to the interface and the interface to the droplet bulk is then calculated, and the net mass transfer between the droplet and interface is determined by performing an energy balance across the interface. For the gas side of the interface, the Ranz-Marshall correlation is used. For the liquid side of the interface, a variety of correlations were tried, including Kronig and Brink (1950) and effective conductivity models. As a result of these assumptions, the Easy5 model currently predicts faster depressurization, as at saturated vapor conditions, the heat transfer coeffect on the liquid side for the Easy5 model is greater than the heat transfer coefficient predicted by Ranz-Marshall used in the TankSIM code. This greater heat flux translates into faster condensation of the saturated ullage gas. At the bulk liquid to ullage interface, the models are in much closer agreement. Both models model the ullage as a sphere centered within the bulk liquid in the tank, and both use the energy-jumping boundary condition to model heat and mass transfer across the interface. There are slight differences in how the interface temperature is calculated, however. The Easy5 model assumes the temperature of the interface is equal to the saturation temperature associated with the pressure of the gas phase. The TankSIM model calculates this temperature with Alabovskii’s equation, which provides a correction factor for interface temperatures. Analysis tasks are focused on determining rates of depressurization within the tank during active cooling operation. To maintain net positive suction head at the pump inlet, the tank pressure cannot fall faster than the saturation pressure associated with the temperature of the bulk liquid. Additionally, there is interest in analyzing the performance of the loop at different pump speeds and cryocooler input powers. Adjusting the flowrate affects both the performance of the heat exchanger between the cryocooler and pumped liquid, and the heat transfer between the droplet spray and the ullage. Ideally, a pump speed and cryocooler power can be selected that will allow the tank to operate in zero-boil-off mode with a very narrow range of storage pressure.

zero boil-off↗
NASA NTRS2004

Buoyancy Effects on Flow Structure and Instability of Low-Density Gas Jets

A low-density gas jet injected into a high-density ambient gas is known to exhibit self-excited global oscillations accompanied by large vortical structures interacting with the flow field. The primary objective of the proposed research is to study buoyancy effects on the origin and nature of the flow instability and structure in the near-field of low-density gas jets. Quantitative rainbow schlieren deflectometry, Computational fluid dynamics (CFD) and Linear stability analysis were the techniques employed to scale the buoyancy effects. The formation and evolution of vortices and scalar structure of the flow field are investigated in buoyant helium jets discharged from a vertical tube into quiescent air. Oscillations at identical frequency were observed throughout the flow field. The evolving flow structure is described by helium mole percentage contours during an oscillation cycle. Instantaneous, mean, and RMS concentration profiles are presented to describe interactions of the vortex with the jet flow. Oscillations in a narrow wake region near the jet exit are shown to spread through the jet core near the downstream location of the vortex formation. The effects of jet Richardson number on characteristics of vortex and flow field are investigated and discussed. The laminar, axisymmetric, unsteady jet flow of helium injected into air was simulated using CFD. Global oscillations were observed in the flow field. The computed oscillation frequency agreed qualitatively with the experimentally measured frequency. Contours of helium concentration, vorticity and velocity provided information about the evolution and propagation of vortices in the oscillating flow field. Buoyancy effects on the instability mode were evaluated by rainbow schlieren flow visualization and concentration measurements in the near-field of self-excited helium jets undergoing gravitational change in the microgravity environment of 2.2s drop tower at NASA John H. Glenn Research Center. The jet Reynolds number was varied from 200 to 1500 and jet Richardson number was varied from 0.72 to 0.002. Power spectra plots generated from Fast Fourier Transform (FFT) analysis of angular deflection data acquired at a temporal resolution of 1000Hz reveal substantial damping of the oscillation amplitude in microgravity at low Richardson numbers (~0.002). Quantitative concentration data in the form of spatial and temporal evolutions of the instability data in Earth gravity and microgravity reveal significant variations in the jet flow structure upon removal of buoyancy forces. Radial variation of the frequency spectra and time traces of helium concentration revealed the importance of gravitational effects in the jet shear layer region. Linear temporal and spatio-temporal stability analyses of a low-density round gas jet injected into a high-density ambient gas were performed by assuming hyper-tan mean velocity and density profiles. The flow was assumed to be non parallel. Viscous and diffusive effects were ignored. The mean flow parameters were represented as the sum of the mean value and a small normal-mode fluctuation. A second order differential equation governing the pressure disturbance amplitude was derived from the basic conservation equations. The effects of the inhomogeneous shear layer and the Froude number (signifying the effects of gravity) on the temporal and spatio-temporal results were delineated. A decrease in the density ratio (ratio of the density of the jet to the density of the ambient gas) resulted in an increase in the temporal amplification rate of the disturbances. The temporal growth rate of the disturbances increased as the Froude number was reduced. The spatio-temporal analysis performed to determine the absolute instability characteristics of the jet yield positive absolute temporal growth rates at all Fr and different axial locations. As buoyancy was removed (Fr . 8), the previously existing absolute instability disappeared at all locations establhing buoyancy as the primary instability mechanism in self-excited low-density jets.

Pasumarthi, Kasyap Sriramachandra↗
NASA NTRS1998

The Athena Mars Rover Science Payload

The Mars Surveyor missions that will be launched in April of 2001 will include a highly capable rover that is a successor to the Mars Pathfinder mission's Sojourner rover. The design goals for this rover are a total traverse distance of at least 10 km and a total lifetime of at least one Earth year. The rover's job will be to explore a site in Mars' ancient terrain, searching for materials likely to preserve a record of ancient martian water, climate, and possibly biology. The rover will collect rock and soil samples, and will store them for return to Earth by a subsequent Mars Surveyor mission in 2005. The Athena Mars rover science payload is the suite of scientific instruments and sample collection tools that will be used to perform this job. The specific science objectives that NASA has identified for the '01 rover payload are to: (1) Provide color stereo imaging of martian surface environments, and remotely-sensed point discrimination of mineralogical composition. (2) Determine the elemental and mineralogical composition of martian surface materials. (3) Determine the fine-scale textural properties of these materials. (4) Collect and store samples. The Athena payload has been designed to meet these objectives. The focus of the design is on field operations: making sure the rover can locate, characterize, and collect scientifically important samples in a dusty, dirty, real-world environment. The topography, morphology, and mineralogy of the scene around the rover will be revealed by Pancam/Mini-TES, an integrated imager and IR spectrometer. Pancam views the surface around the rover in stereo and color. It uses two high-resolution cameras that are identical in most respects to the rover's navigation cameras. The detectors are low-power, low-mass active pixel sensors with on-chip 12-bit analog-to-digital conversion. Filters provide 8-12 color spectral bandpasses over the spectral region from 0.4 to 1.1 micron Narrow-angle optics provide an angular resolution of 0.28 mrad/pixel, nearly a factor of four higher than that of the Mars Pathfinder and Mars Surveyor '98 cameras. Image compression will be performed using a wavelet compression algorithm. The Mini-Thermal Emission Spectrometer (Mini-TES) is a point spectrometer operating in -the thermal IR. It produces high spectral resolution (5 /cm) image cubes with a wavelength range of 5-40 gm, a nominal signal/noise ratio of 500:1, and a maximum angular resolution of 7 mrad (7 cm at a distance of 10 in). The wavelength region over which it operates samples the diagnostic fundamental absorption features of rockforming minerals, and also provides some capability to see through dust coatings that could tend to obscure spectral features. The mineralogical information that Mini-TES provides will be used to select from a distance the rocks and soils that will be investigated in more detail and ultimately sampled. Mini-TES is derived from the MO/MGS TES instrument, but is significantly smaller and simpler. The instrument uses an 8-cm Cassegrain telescope, a Michelson interferometer, and uncooled pyroelectric detectors. Along with its mineralogical capabilities, Mini-TES can provide information on the thermophysical properties of rocks and soils. Viewing upward, it can also provide temperature profiles through the martian atmospheric boundary layer. Elemental and Mineralogical Composition: Once promising samples have been identified from a distance using Pancam/Mini-TES, they will be studied in detail using up to three compositional sensors that can be placed directly against them by an Instrument Arm. The two compositional sensors, presently on the payload are an Alpha-Proton-X-Ray Spectrometer (APXS), and a Mossbauer Spectrometer. The APXS is derived closely from the instrument that flew on Mars Pathfinder. Radioactive alpha sources and three detection modes (alpha, proton, and x-ray) provide elemental abundances of rocks and soils to complement and constrain mineralogical data. The Athena APXS will have a revised mechanical design that will cut down significantly on backscattering of alpha particles from martian atmospheric carbon. It will also include a target of known elemental composition that will be used for calibration purposes. The Athena Mossbauer Spectrometer is a diagnostic instrument for the mineralogy and oxidation state of Fe-bearing phases, which are particularly important on Mars. The instrument measures the resonant absorption of gamma rays produced by a Co-57 source to determine splitting of nuclear energy levels in Fe atoms that is related to the electronic environment surrounding them. It has been under development for space flight for many years at the Technical University of Darmstadt. The Mossbauer Spectrometer (and the other arm instruments) will be able to view a small permanent magnet array that will attract magnetic particles in the martian soil. The payload may also include a Raman Spectrometer. If included, the Raman Spectrometer will provide precise identification of major and minor mineral phases. It requires no sample preparation, and is also sensitive to organics. Fine-Scale Texture: The Instrument Arm a also carries a Microscopic Imager that will obtain high-resolution monochromatic images of the same materials for which compositional data will be obtained. Its spatial resolution is 20 micron/pixel over a 1 cm depth of field, and 40 micron/pixel over a 1-cm depth of field. Like Pancam, it uses the same active pixel sensor detectors and electronics as the rover's navigation cameras. The Instrument Arm is a three degree-of-freedom arm that uses designs and components from the Mars Pathfinder and Mars Surveyor '98 projects. Its primary function is instrument positioning. Along with the instruments noted above, it also carries a brush that can be used to remove dust and other loose coatings from rocks. Sample Collection and Storage: Martian rock and soil samples will be collected using a low-power rotary coring drill called the Mini-Corer. An important characteristic of this device is that it can obtain intact samples of rock from up to 5 cm within strong boulders and bedrock, Nominal core dimensions are 8xl7 mm. The Mini-Corer drills a core to the commanded depth in a rock, shears it off, retains it, and extracts it. It can also acquire samples of loose soil, using soil sample cups that are pressed downward into loose material. The Mini-Corer can drill at angles from vertical to 45' off vertical. It has six interchangeable bits for long life. Mechanical damage to the sample during drilling is minimal, and heating is negligible. After acquisition, the sample may be viewed by the arm instruments, and/or placed in one of 104 compartments in the Sample Container. A subset of the acquired samples may be replaced with other samples obtained later if desired. The Sample Container has no moving parts, and is mounted external to the rover for easy removal by the Mars Surveyor 2005 flight system. Operation of the rover will make extensive use of automated onboard navigation and hazard avoidance capabilities. Otherwise, use of onboard autonomy is minimal. Data downlink capability is about 40 Mbit/sol, and the use of the Mars Surveyor '01 orbiter for data relay imposes a limit of at most two command cycles per sol. Because of the significant amount of time available between command cycles, all payload elements will be operated sequentially, rather than in parallel.; this approach also significantly simplifies operations and minimizes peak power usage. The landing site for the '01 rover has not been selected yet. Site selection will make as full use as possible of Mars Global Surveyor data, and will involve substantial input from the broad Mars science community. Summary: The following table describes the mass, power, providers, and key scientific objectives of all the major elements of the Athena payload. Additional Athena payload information may be found at: http://astrosun.tn.cornell.edu/athena/index.html. Additional information contained in the original.

Squyes, S. W.↗
NASA NTRS2019

A Mixed Integer Efficient Global Optimization Algorithm with Multiple Infill Strategy - Applied to a Wing Topology Optimization Problem

With the advancement in high performance computing and numerical optimization techniques,engineering design optimization problems are becoming more complex, larger scale,higher fidelity, and computationally more demanding, requiring longer run times than ever before. There exists methodologies and techniques that can address some of these challenges but very few can address all, and most are limited in the extent that these concerns can be addressed. With the goal of addressing such challenging engineering problems, we developed anew optimization framework, named AMIEGO, that combines concepts from surrogate-based optimization approaches, gradient-based numerical methods, Partial Least Squares, evolutionary algorithms, and Branch-and-Bound, providing newer capabilities that were not previouslyperceived. However, the original version of this framework, in the process of adaptive samplingto explore and exploit the design space, finds only a single sample point per iteration. The efforthere builds upon this previously developed optimization framework to include multiple infillsampling capability that combines the concept of generalized expected improvement function,unsupervised learning, and multi-objective evolutionary technique. To demonstrate, AMIEGOwith the multiple infill capability (called AMIEGO-MIMOS) solves a series of increasingly difficultengineering design optimization problems. The results reveal the performance of the newapproach is problem dependent. When applied to a ten-bar truss problem, the newly proposedmultiple infill strategy consistently leads to a better design solutions when compared to theexisting CPTV method (implemented with the context of the AMIEGO framework). On theother hand, when applied to a mixed-integer high fidelity wing topology optimization problem- MIMOS, despite showing a steeper convergence at the start, eventually leads to an inferiorsolution as compared to CPTV approach. These results also reveal that a small number ofstarting points, in general, are sufficient to lead to a good overall solution.

Mixed-integer optimization↗
NASA NTRS2008

Spiking Neurons for Analysis of Patterns

Artificial neural networks comprising spiking neurons of a novel type have been conceived as improved pattern-analysis and pattern-recognition computational systems. These neurons are represented by a mathematical model denoted the state-variable model (SVM), which among other things, exploits a computational parallelism inherent in spiking-neuron geometry. Networks of SVM neurons offer advantages of speed and computational efficiency, relative to traditional artificial neural networks. The SVM also overcomes some of the limitations of prior spiking-neuron models. There are numerous potential pattern-recognition, tracking, and data-reduction (data preprocessing) applications for these SVM neural networks on Earth and in exploration of remote planets. Spiking neurons imitate biological neurons more closely than do the neurons of traditional artificial neural networks. A spiking neuron includes a central cell body (soma) surrounded by a tree-like interconnection network (dendrites). Spiking neurons are so named because they generate trains of output pulses (spikes) in response to inputs received from sensors or from other neurons. They gain their speed advantage over traditional neural networks by using the timing of individual spikes for computation, whereas traditional artificial neurons use averages of activity levels over time. Moreover, spiking neurons use the delays inherent in dendritic processing in order to efficiently encode the information content of incoming signals. Because traditional artificial neurons fail to capture this encoding, they have less processing capability, and so it is necessary to use more gates when implementing traditional artificial neurons in electronic circuitry. Such higher-order functions as dynamic tasking are effected by use of pools (collections) of spiking neurons interconnected by spike-transmitting fibers. The SVM includes adaptive thresholds and submodels of transport of ions (in imitation of such transport in biological neurons). These features enable the neurons to adapt their responses to high-rate inputs from sensors, and to adapt their firing thresholds to mitigate noise or effects of potential sensor failure. The mathematical derivation of the SVM starts from a prior model, known in the art as the point soma model, which captures all of the salient properties of neuronal response while keeping the computational cost low. The point-soma latency time is modified to be an exponentially decaying function of the strength of the applied potential. Choosing computational efficiency over biological fidelity, the dendrites surrounding a neuron are represented by simplified compartmental submodels and there are no dendritic spines. Updates to the dendritic potential, calcium-ion concentrations and conductances, and potassium-ion conductances are done by use of equations similar to those of the point soma. Diffusion processes in dendrites are modeled by averaging among nearest-neighbor compartments. Inputs to each of the dendritic compartments come from sensors. Alternatively or in addition, when an affected neuron is part of a pool, inputs can come from other spiking neurons. At present, SVM neural networks are implemented by computational simulation, using algorithms that encode the SVM and its submodels. However, it should be possible to implement these neural networks in hardware: The differential equations for the dendritic and cellular processes in the SVM model of spiking neurons map to equivalent circuits that can be implemented directly in analog very-large-scale integrated (VLSI) circuits.

Huntsberger, Terrance↗