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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
NASA NTRS2005

Chemistry, Dynamics, and Radiation of Ozone Loss: Airborne Measurements of OH, HO2, NO2, ClO, BrO, IO, ClONO2, BrONO2, ClOOCl, and H2O

This grant continued the research initially funded under NAG1-01095. This research addresses, through a combination of in situ and remote aircraft-borne instruments, the following scientific questions: Which mechanisms are responsible for the continuing erosion of ozone over midlatitudes of the Northern Hemisphere? Will the rapid loss of ozone over the Arctic in late winter continue to worsen over the next two decades? Are these large losses dynamically coupled to midlatitudes? Which mechanisms dictate the rate of exchange of material between the troposphere and stratosphere? How will these processes change in response to changes in climate? Will regional scale pollution episodes, that are emerging as predictable seasonal events, significantly affect the middle-to-upper troposphere chemical composition. If so, how will these changes alter the chemical composition of the middle world? What changes are predicted for the overworld? Why has the arctic stratosphere become colder in the late winter phase in recent years? Have increases in tropical upper troposphere temperatures increased the temperature gradient such as to change the trajectories of vertically propagating waves, thus reducing the effectiveness of the meridional circulation for transport of heat, momentum and ozone from the tropics to high latitudes?

Anderson, James G.↗
NASA NTRSDate not supplied

Thermal Analysis of an In-Space Heat Shield Exposed to a Rocket Plume During Stage Separation

Thermal analyses were conducted to evaluate the thermal response of various individual materials and multi-layer configurations for an in-space heat shield exposed to a rocket plume during stage separation. Frequently used, readily available thermal protection materials consisting of cork, carbon cloth phenolic (CCP), and silica cloth phenolic (SCP) were selected for an initial screening analysis. SCP was chosen as the primary material for further evaluation using an updated thermal environment calculated using computational fluid dynamics (CFD) results. A multi-layer configuration consisting of SCP providing erosion resistance and a Nomex honeycomb providing thermal protection was then evaluated as a solution for more mass-efficient performance. Pyrolysis depth, bondline temperature, back-side temperature, and a thermal factor of safety were used to define the necessary material thickness profile. Adhesives were included in the analyses with considerations for maximum temperature and application method. One dimensional thermal analyses at several stations along the heat shield surface were performed for the initial screening and follow-on analyses. The methodology used standard processes and computer programs applicable to solid rocket motor internal insulation and nozzle thermal analysis such as Chemical Equilibrium and Applications (CEA), Aerotherm Chemical Equilibrium (ACE), Momentum/Energy Integral Technique (MEIT), and Insulation Thermal Response and Ablation Code (ITRAC). The baseline SCP/Nomex honeycomb multi-layer configuration thermal performance predictions satisfied the objectives with an acceptable mass estimate for the design maturity. The EA9673 film adhesive and SCP resin were the best performing bonding agents considered for the SCP/Nomex honeycomb and Nomex honeycomb/structural substrate interfaces. The baseline mass estimate was lowest when the resin was the bonding agent due to the higher maximum service temperature. These thermal analyses evaluated typical internal and external nozzle materials using a calculated thermal environment and heat loads that were lower than a typical rocket motor internal environment but greater than standard external aeroheating.

Andrew T Hiatt↗
NASA NTRS1991

Supernova remnants in dense clouds. I - Blast-wave dynamics and X-ray irradiation

Simplified models of cooling SNRs in uniform media together with an idealized emission spectrum are used to investigate the X-ray irradiation of the surrounding gas. The radiative transfer of the emitted X-rays through both the dense cooling shell and the unshocked cloud is calculated, with a simplified treatment to allow for an ionized zone surrounding the SNR. Numerical results are presented for SN energy of 10 exp 51 ergs and ambient densities ranging from 100 to 1,000,000 cu cm. It is found that an appreciable fraction of the X-ray energy is absorbed in regions where the X-ray energy deposited per H nucleon is between 1 and 30 eV; if the gas is initially molecular, the X-ray irradiation will result in warm molecular gas in which endothermic chemical reactions may proceed, and from which there may be strong emission in rotation-vibration transitions of H2 and other molecular species.

Draine, B. T.↗
NASA NTRSDate not supplied

Predicting Char Yield of High-Temperature Resins

A simulation technique has been developed for predicting the char yield of organic resins during high-temperature processing. In silico methods can aid in the screening of new advanced materials for a number of important properties, but no chemistry-sensitive protocol currently exists for predicting the important experimental value of char yield. The proposed method utilizes a reactive force field (ReaxFF) to model the chemical transformation of precursor monomers into carbonized structures during three processing stages: ramp-up to pyrolysis temperatures (~3000 K), pyrolysis, and quenching. Achieving good agreement with experimental char yields requires continuous removal of small by-product molecules to mimic outgassing, and the application of high pressure to encourage the formation of a dense, glassy network. Six different resin chemistries were investigated: an ethynyl, a phenylethynyl, a cyanate ester, a phthalonitrile, acrylonitrile, and adamantane. These candidates represent a diverse group of precursors with respect to initial cyclic content, presence of heteroatoms, and types of reactive groups. The protocol developed accurately predicts the relative char yield between the investigated chemistries and provides quantitative agreement with experimental values, especially for high char yield resins. Several simulated properties of the carbonized structures are compared with experimental results, including outgassing products, morphology of the final chemical configurations, cyclic content, and mechanical properties.

polymer simulations, molecular dynamics↗
NASA NTRS2020

Description and Evaluation of the Specified-Dynamics Experiment in the Chemistry-Climate Model Initiative

We provide an overview of the REF-C1SD specified-dynamics experiment that was conducted as part of phase 1 of the Chemistry-Climate Model Initiative (CCMI). The REF-C1SD experiment, which consisted of mainly nudged general circulation models (GCMs) constrained with (re)analysis fields, was designed to examine the influence of the large-scale circulation on past trends in atmospheric composition. The REF-C1SD simulations were produced across various model frameworks and are evaluated in terms of how well they represent different measures of the dynamical and transport circulations. In the troposphere there are large (~40 %) differences in the climatological mean distributions, seasonal cycle amplitude, and trends of the meridional and vertical winds. In the stratosphere there are similarly large (~50 %) differences in the magnitude, trends and seasonal cycle amplitude of the transformed Eulerian mean circulation and among various chemical and idealized tracers. At the same time, interannual variations in nearly all quantities are very well represented, compared to the underlying reanalyses. We show that the differences in magnitude, trends and seasonal cycle are not related to the use of different reanalysis products; rather, we show they are associated with how the simulations were implemented, by which we refer both to how the large-scale flow was prescribed and to biases in the underlying free-running models. In most cases these differences are shown to be as large or even larger than the differences exhibited by free-running simulations produced using the exact same models, which are also shown to be more dynamically consistent. Overall, our results suggest that care must be taken when using specified-dynamics simulations to examine the influence of large-scale dynamics on composition.

Clara Orbe↗
NASA NTRSDate not supplied

Bioreactor Development for CO2-Based In Situ Resource Utilization Manufacturing

Sustainable long-duration manned missions on both the Moon and Mars will require in situ resource utilization (ISRU). Carbon dioxide (CO2) has great potential as a harvestable resource, making up 95% of the atmosphere on Mars and being produced as respiratory waste in spacecraft and future planetary habitats. Through ISRU, biomanufacturing has the capability to produce a near limitless array of products from local space resources, which include pharmaceuticals, bioplastics, chemical feedstocks, and industrial enzymes. Here, a CO2-based ISRU recombinant protein bioreactor and associated biomanufacturing organisms were designed to produce a highly stable carbonic anhydrase (CA). Initial work characterized candidate organisms for growth on acetate and formic acid, carbon substrates that can be synthesized via electrochemical conversion of CO2. To improve growth on the CO2 producing substrate formic acid and for direct integration of ISRU CO2, a synthetic Calvin-Benson-Bassam cycle was designed for use in Cyberlindnera jadinii and Escherichia coli. Genetic modifications in E. coli will be facilitated by a tailored CRISPR/Cas9 and λ red recombineering two-vector system. For expression of CA, a blue light regulated T7 promoter was employed for dynamic and small molecule free induction. Efficient bioproduction through a fed-batch exponential feeding strategy was determined via mass balance calculations from ISRU substrates to biomass and CA yield. Flux balance analysis was used to model ISRU substrate metabolism and metabolic pathway engineering in candidate organisms under cultivation strategy conditions for both metabolism reconstruction and pathway design optimization. Finally, a small-scale, disposable bag bioreactor concept for use in the NASA Bioculture System infrastructure was designed to enable CO2-based CA production in reduced-gravity environments.

Biomanufacturing, Pathway Engineering, Flux Balanc↗
NASA NTRS1999

Computation of Steady and Unsteady Laminar Flames: Theory

In this paper we describe the numerical analysis underlying our efforts to develop an accurate and reliable code for simulating flame propagation using complex physical and chemical models. We discuss our spatial and temporal discretization schemes, which in our current implementations range in order from two to six. In space we use staggered meshes to define discrete divergence and gradient operators, allowing us to approximate complex diffusion operators while maintaining ellipticity. Our temporal discretization is based on the use of preconditioning to produce a highly efficient linearly implicit method with good stability properties. High order for time accurate simulations is obtained through the use of extrapolation or deferred correction procedures. We also discuss our techniques for computing stationary flames. The primary issue here is the automatic generation of initial approximations for the application of Newton's method. We use a novel time-stepping procedure, which allows the dynamic updating of the flame speed and forces the flame front towards a specified location. Numerical experiments are presented, primarily for the stationary flame problem. These illustrate the reliability of our techniques, and the dependence of the results on various code parameters.

Hagstrom, Thomas↗
NASA NTRS2022

Understanding Structure in Line-Driven Stellar Winds Using Ultraviolet Spectropolarimetry in the Time Domain

The most massive stars are thought to lose a significant fraction of their mass in a steady wind during the main-sequence and blue supergiant phases. This in turn sets the stage for their further evolution and eventual supernova, and preconditions the surrounding medium for all following events, with consequences for ISM energization, chemical enrichment, and dust formation. Understanding these processes requires accurate observational constraints on the mass-loss rates of the most luminous stars, which can also be used to test theories of stellar wind driving. In the past, mass-loss rates have been characterized via collisional emission processes such as optical Hα and free-free radio emission, but these so-called “density squared” diagnostics require correction in the presence of widespread clumping. Recent observational and theoretical evidence points to the likelihood of a ubiquitously high level of such clumping in hot-star winds, but quantifying its effects requires a deeper understanding of the complex dynamics of radiatively driven winds and their stochastic instabilities. Furthermore, large-scale structures initiating in surface anisotropies and propagating throughout the wind can also affect wind driving and alter mass-loss diagnostics. Time series spectroscopy of high resonance-line opacity in the UV, capable of high resolution and high signal-to-noise, are required to better understand these complex dynamics, and more accurately determine mass-loss rates. The proposed Polstar mission (Scowen et al. 2022, this volume) provides the necessary resolution at the Sobolev (∼10 km s −1 ) or sound-speed (∼20 km s −1 ) scale, for over three dozen bright galactic massive stars with signal-to noise an order of magnitude above that of the celebrated MEGA campaign (Massa et al. 1995) of the International Ultraviolet Explorer (IUE), via continuous observations that track propagating structures through the winds in real time. Supporting geometric constraints are provided by the polarimetric capabilities present in all the datasets of such a mission.

Polstar – NASA MIDEX↗
NASA NTRS2011

Detailed Modeling of Distillation Technologies for Closed-Loop Water Recovery Systems

Detailed chemical process simulations are a useful tool in designing and optimizing complex systems and architectures for human life support. Dynamic and steady-state models of these systems help contrast the interactions of various operating parameters and hardware designs, which become extremely useful in trade-study analyses. NASA?s Exploration Life Support technology development project recently made use of such models to compliment a series of tests on different waste water distillation systems. This paper presents efforts to develop chemical process simulations for three technologies: the Cascade Distillation System (CDS), the Vapor Compression Distillation (VCD) system and the Wiped-Film Rotating Disk (WFRD) using the Aspen Custom Modeler and Aspen Plus process simulation tools. The paper discusses system design, modeling details, and modeling results for each technology and presents some comparisons between the model results and recent test data. Following these initial comparisons, some general conclusions and forward work are discussed.

Allada, Rama Kumar↗
NASA NTRS1992

NASA's upper atmosphere research satellite: A program to study global ozone change

The Upper Atmosphere Research Satellite (UARS) is a major initiative in the NASA Office of Space Science and Applications, and is the prototype for NASA's Earth Observing System (EOS) planned for launch in the 1990s. The UARS combines a balanced program of experimental and theoretical investigations to perform diagnostic studies, qualitative model analysis, and quantitative measurements and comparative studies of the upper atmosphere. UARS provides theoretical and experimental investigations which pursue four specific research topics: atmospheric energy budget, chemistry, dynamics, and coupling processes. An international cadre of investigators was assembled by NASA to accomplish those scientific objectives. The observatory, its complement of ten state of the art instruments, and the ground system are nearing flight readiness. The timely UARS program will play a major role in providing data to understand the complex physical and chemical processes occurring in the upper atmosphere and answering many questions regarding the health of the ozone layer.

Luther, Michael R.↗
NASA NTRSDate not supplied

TPSAS-NF1676L-27509-DND

The information about composition of aerosols has a great importance for monitoring and understanding of climate and environment dynamics. Such information can be obtained using situ measurements or chemical transport models. However, in situ sampling has limited spatial and temporal coverage, while estimations have large uncertainties. The present work enables the monitoring of aerosol chemical species from space-borne observations, providing observationally-based results with spatial and temporal coverage. Following the ideas of Schuster et al.(2005, 2009, 2016), we retrieve chemical composition directly from satellite observations without intermediate retrieval of the refractive index (in contrast with Schuster's approach). This approach is expected to reduce the influence of modeling uncertainties, and to provide additional constraints in situations where remote sensing observations do not have enough spectral sensitivity to refractive index. One of principal difficulties is the identification of an adequate model for linking refractive index to chemical composition. Therefore, the initial effort of this work has focused on identifying an optimal physico-chemistry to refractive index conversion model. With that purpose, we first tested the retrieval approach using a simplified volume-weighting model and updated by the Maxwell Garnett mixing model. This concept was incorporated into the GRASP algorithm designed to retrieve an extended set of atmospheric parameters from remote sensing observations. Then a series of sensitivity tests using synthetic data of POLDER/PARASOL were conducted, and followed by inversion of real PARASOL observations over Africa. The sensitivity tests showed that these two models allow the retrieval to distinguish amongst the assumed chemical species. Results obtained from real PARASOL data demonstrated good agreement with the optical characteristics provided by AERONET. In addition, the obtained patterns of chemical component distribution agreed with known physical expectations. We also compared the chemical composition retrievals to GOCART model simulations and obtained good consistencies.

Lei Li↗
NASA NTRS1992

Application of computational fluid dynamics to the design of the film cooled STME subscale nozzle for the National Launch System

The status of computational fluid dynamics (CFD) calculations for the Space Transportation Main Engine (STME) film/dump cooled nozzle design is presented, with an emphasis on the timely impact of CFD on the design of the sub-scale nozzle coolant system. The following aspects of the sub-scale coolant delivery system were analyzed with CFD: 1) a design trade study of a mechanical flow splitting device for uniform distribution of the subsonic cavity flow, 2) a design trade study of the subsonic cavity lip to achieve film integrity, and 3) an analysis of the primary flow interaction with the core/secondary coolant streams. All design calculations were performed with the Generalized Aerodynamic Simulation Program (GASP), a 3-D, multi-block, generalized Navier-Stokes code capable of solving with frozen, finite-rate or equilibrium chemical kinetics. The initial design of the subsonic cavity flow used square posts to distribute the sonic orifice jets into a uniform flow. Calculations for this design indicated that an unacceptable mal-distribution of film occurred. Design modifications involving curved and slotted posts were computed in an effort to uniformly distribute the secondary coolant flow. Analysis of these configurations showed that although the flowfield improved in uniformity, it was still unacceptable, especially at higher feed pressures. Results from these studies were then incorporated into a design that resulted in the insertion of a porous metal ring into the subsonic cavity. Subsequent water flow model studies showed that this concept was successful in uniformly distributing flow exiting the cavity. In addition to the design of the subsonic cavity, CFD was also used to analyze the secondary coolant lip and the primary flow interaction with the core/secondary coolant streams. A series of calculations were first performed to modify the subsonic cavity lip contour. The flow over the modified lip was then computed simultaneously with the primary injectors to determine the impact of the subsonic coolant stream on the primary slot jets. Pressure, temperature, velocity, and coolant mass fraction contours are presented for these configurations. Information is given in viewgraph form.

Garrett, Joseph L.↗
NASA NTRS1972

Moments of inertia of the lunar globe, and their bearing on chemical differentiation of its outer layers.

It is pointed out that the observed moments of inertia of the moon, disclosed by its librations, are influenced mainly by the distribution of mass in the outer zone in which the lithostatic pressure is less than 10 kb (i.e., in the outer shell not more than 200 km deep); a conspicuous departure of such moments from those expected in hydrostatic equilibrium disclosed that these layers could never have been fluid. In the same way, the actual shape of the lunar surface cannot represent a solidified surface of a fluid, petrified at any distance from the earth. The shape of the moon and differences of its moments of inertia must reflect the way in which the initial process of cold accretion fell short of producing a globe with strictly spherically-symmetrical stratification of material. Such melting or lava flows as may have occurred at the moon's surface from time to time must have remained localized, and without much effect on the dynamical properties of the moon.

Kopal, Z.↗
NASA NTRS1998

Time-Resolved O3 Chemical Chain Reaction Kinetics Via High-Resolution IR Laser Absorption Methods

Excimer laser photolysis in combination with time-resolved IR laser absorption detection of OH radicals has been used to study O3/OH(v = 0)/HO2 chain reaction kinetics at 298 K, (i.e.,(k(sub 1) is OH + 03 yields H02 + 02 and (k(sub 2) is H02 + 03 yields OH + 202). From time-resolved detection of OH radicals with high-resolution near IR laser absorption methods, the chain induction kinetics have been measured at up to an order of magnitude higher ozone concentrations ([03] less than or equal to 10(exp 17) molecules/cu cm) than accessible in previous studies. This greater dynamic range permits the full evolution of the chain induction, propagation, and termination process to be temporally isolated and measured in real time. An exact solution for time-dependent OH evolution under pseudo- first-order chain reaction conditions is presented, which correctly predicts new kinetic signatures not included in previous OH + 03 kinetic analyses. Specifically, the solutions predict an initial exponential loss (chain "induction") of the OH radical to a steady-state level ([OH](sub ss)), with this fast initial decay determined by the sum of both chain rate constants, k(sub ind) = k(sub 1) + k(sub 2). By monitoring the chain induction feature, this sum of the rate constants is determined to be k(sub ind) = 8.4(8) x 10(exp -14) cu cm/molecule/s for room temperature reagents. This is significantly higher than the values currently recommended for use in atmospheric models, but in excellent agreement with previous results from Ravishankara et al.

Kulcke, Axel↗
NASA NTRSDate not supplied

Quantum Hardware-Enabled Molecular Dynamics via Transfer Learning

The ability to perform ab initio molecular dynamics simulations using potential energy surfaces provided by quantum computers would open the door to virtually exact dynamics for a variety of chemical and biochemical systems, with impacts on catalysis and biophysics. Nonetheless, performing molecular dynamics on surfaces produced by quantum hardware has been hampered by the noisy energies typically produced by quantum computers and challenges associated with computing gradients and scaling to large systems interest. A recent set of advances in machine learning, known as transfer learning, provides a new path forward for molecular dynamics simulations on quantum hardware. Transfer learning offers a workaround, where one first trains models on larger, less accurate classical datasets and then refines them on smaller, more accurate quantum datasets. We explore this approach by training machine learning models to predict a molecule's potential energy based on its geometric structure using Behler-Parrinello neural networks. When successfully trained, the model enables energy gradient predictions necessary for dynamic simulations. To reduce the quantum resources needed, the model is initially trained with data derived from classical density functional theory and subsequently refined with a smaller dataset obtained from a variational quantum eigensolver optimization of the unitary coupled cluster ansatz. We show that this approach significantly reduces the size of the needed quantum training dataset while capturing the high accuracies needed within quantum chemistry simulations. The success of this two-step training method opens more opportunities to apply machine learning models on quantum data, a significant stride towards efficient quantum-classical hybrid computational models.

quantum computing↗
NASA NTRS2007

Automated Knowledge Discovery From Simulators

A computational method, SimLearn, has been devised to facilitate efficient knowledge discovery from simulators. Simulators are complex computer programs used in science and engineering to model diverse phenomena such as fluid flow, gravitational interactions, coupled mechanical systems, and nuclear, chemical, and biological processes. SimLearn uses active-learning techniques to efficiently address the "landscape characterization problem." In particular, SimLearn tries to determine which regions in "input space" lead to a given output from the simulator, where "input space" refers to an abstraction of all the variables going into the simulator, e.g., initial conditions, parameters, and interaction equations. Landscape characterization can be viewed as an attempt to invert the forward mapping of the simulator and recover the inputs that produce a particular output. Given that a single simulation run can take days or weeks to complete even on a large computing cluster, SimLearn attempts to reduce costs by reducing the number of simulations needed to effect discoveries. Unlike conventional data-mining methods that are applied to static predefined datasets, SimLearn involves an iterative process in which a most informative dataset is constructed dynamically by using the simulator as an oracle. On each iteration, the algorithm models the knowledge it has gained through previous simulation trials and then chooses which simulation trials to run next. Running these trials through the simulator produces new data in the form of input-output pairs. The overall process is embodied in an algorithm that combines support vector machines (SVMs) with active learning. SVMs use learning from examples (the examples are the input-output pairs generated by running the simulator) and a principle called maximum margin to derive predictors that generalize well to new inputs. In SimLearn, the SVM plays the role of modeling the knowledge that has been gained through previous simulation trials. Active learning is used to determine which new input points would be most informative if their output were known. The selected input points are run through the simulator to generate new information that can be used to refine the SVM. The process is then repeated. SimLearn carefully balances exploration (semi-randomly searching around the input space) versus exploitation (using the current state of knowledge to conduct a tightly focused search). During each iteration, SimLearn uses not one, but an ensemble of SVMs. Each SVM in the ensemble is characterized by different hyper-parameters that control various aspects of the learned predictor - for example, whether the predictor is constrained to be very smooth (nearby points in input space lead to similar output predictions) or whether the predictor is allowed to be "bumpy." The various SVMs will have different preferences about which input points they would like to run through the simulator next. SimLearn includes a formal mechanism for balancing the ensemble SVM preferences so that a single choice can be made for the next set of trials.

Burl, Michael↗
NASA NTRSDate not supplied

VALENTInE: A Concept for a New Frontiers Class Long Duration In-Situ Balloon Mission to Venus

Venus and Earth are similar in bulk composition, size, density, and approximate distance from the Sun, yet Venus’s modern-day climate and surface geology is distinctly different [1]. Previous missions to Venus revealed unusual volcanic features, possible continental crust, widespread volcanic plains, a weak magnetic field [2], and insights into the Venusian atmosphere [3,4]. Unfortunately, data from these missions were limited in spatial and temporal resolution and global extent. A future mission to Venus is critical to address fundamental questions surrounding the chemical composition and dynamics of the Venusian atmosphere [5], its geologic history [6,7], its internal structure [8,9], and its habitability throughout time [10,11]. We present the Venus Air and Land Expedition: a Novel Trailblazer for In situ Exploration (VALENTInE) mission to meet this need. VALENTInE is a variable altitude balloon that will passively float in Venus’s atmosphere between 45 and 55 km altitude. VALENTInE will acquire atmospheric data at varying latitudes and longitudes in addition to mapping the surface geomorphology and mineralogy across multiple terrains. Mission Objectives: The VALENTInE mission concept is driven by four main science objectives: 1. Determine whether the driving force of the superrotation of Venus’s atmosphere is caused by horizontal or vertical momentum transport. 2. Determine whether the atmospheric composition and noble gas inventory of the Venusian atmosphere is a product of outgassing from the initial protoplanetary source or if there are significant contributions from exogenic sources. 3. Determine whether the tesserae regions (particularly Aphrodite Terra) are felsic and relatively older than surrounding regions. 4. Determine if there is any evidence of a recent dynamo preserved in the rock record of Venus. Mission Overview: A balloon architecture provides a robust system that can survive long-term in the Venusian environment while taking accurate measurements of the lower cloud deck and surface. Two prior balloon missions to Venus, VEGA 1 and VEGA 2 in 1984, have demonstrated the potential for such planetary exploration; however, these missions were short-lived (46 hr), with limited range (54 km). Our spacecraft concept consists of a battery powered balloon with a gondola and flyby carrier stage (Fig. 1). Our novel design allows for at least 15 days of atmospheric exploration, including multiple ascents and descents in the Venus atmosphere. VALENTInE is baselined to launch in 2032, cruise on solar power for 128 days, enter, descend, and inflate (EDI) into Venus’s atmosphere above Aphrodite Terra, and float in Venus’s atmosphere for a total nominal mission duration of 15 days. The balloon, able to control its altitude by changing its buoyancy, will make one full circumnavigation every 4–8 days and move poleward ~1 o latitude per day; it will be passively directed by the horizontal air currents on Venus. The balloon can only be controlled in the z direction, and the expected latitude range is ±10° from EDI. The balloon itself will be a tracer for atmospheric structures such as zonal winds [5, 12]. During the 15-day operational period, there will be five dips to 45 km for a compositional study of the lower atmosphere and geological and magnetic mapping of the surface. Dips are used to take images and measurements closer to the surface and to obtain in situ vertical atmospheric profiles between 45 and 55 km. Instruments: The VALENTInE instrument payload will allow for extensive study of the geology, atmosphere, and interior of Venus. The instrument suite consists of six instruments. The mission profile for each instrument is shown in Fig. 2. Lower Atmosphere Meteorology Analyzer (LAMA) is an atmospheric structure instrument consisting of a thermometer, barometer, and accelerometer to continuously measure temperature and pressure as a function of altitude, longitude, and latitude. TracE and Noble Gas Investigator (TENGI) is aneutral mass spectrometer used to sample the dense atmosphere. TENGI will operate continuously at 45 km and 55 km and will measure D/H ratios, as well as Ne, Ar, and O isotopic ratios. Kilometer Scale Spectral Imager (KSSI) is amultispectral imager (850-1150 nm) used to resolve surface features on the order of km. Near InfraRed Multispectral Photometer (NIRMP) is an Infrared (IR) photometer used to image the surface through the clouds to characterize mineral assemblages at five different areas of the surface. NIRMP will be operated during dwell. ELevation REConnaissance (ELREC) is a light detection and ranging (LIDAR) instrument used for measuring topography at five different areas of the surface. The ELREC data will be combined with those of NIRMP to determine mineral assemblages and how they correlate to topography. Magnetic Exploration and Interior Detective (MEID) is a magnetometer used to detect any near-surface magnetic anomalies. The magnetometer will continuously operate at all altitudes. Mission Design: The spacecraft’s propulsion system will have a wet mass of 930 kg and will be launched on an Atlas V rocket. The spacecraft will jettison the payload upon arrival in Venus’s atmosphere before decelerating to orbital velocity. Figure 2. Notional power-dip profile while the balloon is on the dayside. Risks and Challenges: Raising and lowering the spacecraft to dip beneath the haze layer require a large amount of energy. This issue was partly compensated by limiting the number of dips over the 15 day prime mission. Power needs for pumping helium are reduced by slowing the descent speed, which consequently increases spatial resolution of in situ measurements between 45 and 55 km. The main limitation for the duration of the mission is the need to carry 15 days’ worth of batteries. The bus experiences external Venusian temperatures ranging from ~27°C at 55 km altitude to ~110°C at 45 km altitude. These high atmospheric temperatures require thermal protection for the bus (instruments, electronics, and flight systems) during its descent, dwell at 45 km, and ascent. The bus is maintained at a mechanically safe temperature range of -10°C to 50°C using white external paint, multi-layer insulation (MLI), mechanical/thermal isolation (e.g. Ti, composites), and ~57 kg of Phase Change Materials (PCM). Images and spectra taken below the haze dominate the available data transmission regardless of the time spent at 45 km. Therefore, less time at the lower altitude mainly reduces the coverage of in situ measurements there. Further, we assumed an unrealistically low-density material for the helium storage tanks on the gondola. However, this issue is partially resolved if we were to jettison 75% of the spent helium storage tanks. After the entry process, the balloon volume remains mostly inflated and storage tanks are required only for reducing balloon volume in dipping to 45 km. This mission was planned against an expected New Frontiers 5 (NF5) cost cap of $1B, as the NF5 call had not yet been released. The mission we describe fits within the predicted cost cap if the flyby carrier stage, responsible for powering the spacecraft during cruise and for relaying in situ measurements back to Earth, can be contributed by another space agency. Acknowledgments: We thank the JPL Planetary Science Summer School, especially A. Nash, J. Scully, K. Mitchell, L. Lowes, and J. Armijo, and our mentors from JPL Team X. Thank you to our review panel for their insightful review. References: [1] Kane, S. et al. (2019) JGR:Ps, 124 , 2015–2028. [2] Phillips, J. L., & Russell, C. T. (1987). JGR: Space Physics , 92 (A3), 2253-2263. [3] Nakamura, M. et al. (2018) Earth Planets Space, 70 (1), 144. [4] Svedhem, H. et al. (2009) JGR:P 114 (E5). [5] Limaye et al. (2009) Decadal Survey White Paper . [6] Ivanov, M. and Head, J. (2011) PSS, 59 (13) , 1559-1600. [7] Smrekar, S. et al. (2018) Space Sci Rev, 214 (5), 88. [8] O’Rourke, J. et al. (2018) EPSL, 502 , 46-56. [9] O’Rourke J. et al. (2019) GRL , (46), 5768–5777 [10] Way, M. et al. (2016) GRL, 43 (16), 8376-8383. [11] Way, M. et al. (2020) JGR:P, 125 (5), e2019JE006276. [12] Preston, R. A. et al. (1986) Science, 231 (4744), 1414-1416.

Mission Concept↗
NASA NTRS1991

From wind to superwind - The evolution of mass-loss rates for Mira models

Dynamical atmosphere models were calculated for a large grid of variables with Mira-like properties satisfying the Iben radius-luminosity-mass relationship for evolving AGB stars. Their masses ranged from 0.7 to 2.4 solar masses, and their periods from 150 to 800 days. All were fundamental-mode pulsators, had solar metallicity, and included effects of dust. The mass-loss rate increases as an approximately exponential function of time, reaching 0.00001-0.0001 solar masses/yr. Further evolution is dominated by the powerful wind, which strips the star's envelope from the core. This 'superwind', a remarkably robust effect, occurs for all initial stellar masses and all modeling parameters that have been tested. Models with very low metallicity also show the effect, but at higher luminosities, which has intriguing implications for the number of supernovae in early low-metallicity populations and for the chemical evolution of galaxies.

Bowen, G. H.↗