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The Microwave Radiometer (MWR), Juno’s remote-sensing experiment, captures the thermal and non-thermal radiation emitted by the atmosphere and the magnetosphere, which is present in the Jovian orbital environment. Other scientific instruments on the spacecraft record the signatures of space-charged particles and the planet’s magnetic field. To retrieve the atmospheric composition values from MWR’s low-frequency radiative observation, the contributions from three existing emission sources (the cosmic microwave background (CMB), the planet, and synchrotron radiation belts) must be untangled numerically. The multi-parameter, multi-zonal model of Levin et al. (2001) for synchrotron emission employs an empirical electron-energy distribution. Initially, this distribution has been adjusted exclusively from Very Large Array (VLA) observations made from Earth before the Juno mission. This is a report on the recent model update based on a subset of MWR in-situ data. The approaches considered, challenges confronted, and the latest results are discussed here.

Jupiter has ubiquitous clouds and enormous surface structures shrouding the planet. Juno MWR provides the unprecedented chance to answer remaining major questions about the composition and dynamical properties of the great bulk of the atmosphere that lies beneath. Since the launch of Juno, there has been a large effort to collect complementary ground- and space-based observations to help interpret the MWR data. The Jovian Infrared Auroral Mapper (JIRAM) onboard Juno complements the observations of MWR, by giving alternative and reference tropospheric measurements that provides the boundary condition for the interpretation of the MWR data [Adriani et al 2014]. Similarly, HST has a 6-month overlap with 13 Juno orbits and color images were constructed from images of Jupiter in red, green, and blue filters by JunoCam [Hansen et al., 2014]. We study the dynamics within the atmosphere by relating the exterior information provided by these surface maps to the deep interior detected by MWR.Since Aug 27, 2016, MWR has obtained over 40 perijoves, all scanning Jupiter’s atmosphere from North to South, covering various longitudes. We extend our calibration stability investigation to cover 6 years of observations, using our error analysis process. After removing the calibration drift, we combine observations from all perijoves to study the global-averaged atmosphere and the discrete features. We compare them with Jupiter’s surface atmosphere images taken by JunoCam, HST and JIRAM, and retrieve the corresponding NH3 volume mixing ratio from surface to over 100 bars.

In Jupiter’s vicinity, Juno’s remote-sensing experiment, the Microwave Radiometer (MWR), captures thermal and non-thermal emissions from the atmosphere and magnetosphere. Furthermore, other scientific instruments on the spacecraft register the signatures of space charged particles and the planet’s magnetic field. The separation of contributions from several existing emission sources (cosmic microwave background, galactic emission, planetary thermal emission and synchrotron radiation belts) is a necessary step in the retrieval of atmospheric composition values from MWR’s low-frequency radiative observations. The ad hoc multi-parameter, multi-zonal model of Levin et al. (2001) for synchrotron emission has been updated based on a subset of the MWR in-situ data. This model employs an empirical electron-energy distribution, which originally has been adjusted exclusively from Very Large Array (VLA) observations made prior to the Juno mission. The approaches considered and challenges confronted are discussed here. The model will be updated frequently as additional observations from the MWR and magnetometer instruments are taken into account.

Jupiter has ubiquitous clouds and enormous surface structures shrouding the planet. Juno MWR provides the unprecedented chance to answer remaining major questions about the composition and dynamical properties of the great bulk of the atmosphere that lies beneath. Since the launch of Juno, there has been a large effort to collect complementary ground- and space-based observations to help interpret the MWR data. The Jovian Infrared Auroral Mapper (JIRAM) onboard Juno complements the observations of MWR, by giving alternative and reference tropospheric measurements that provides the boundary condition for the interpretation of the MWR data [Adriani et al 2014]. Similarly, HST has a 6-month overlap with 13 Juno orbits and color images were constructed from images of Jupiter in red, green, and blue filters by JunoCam [Hansen et al., 2014]. We study the dynamics within the atmosphere by relating the exterior information provided by these surface maps to the deep interior detected by MWR.During Aug 27, 2016 to October 24, 2017, MWR obtained 8 perijoves (PJ1, 3, 4, 5, 6, 7, 8, 9), all scanning Jupiter’s atmosphere from North to South, covering various longitudes. By combing observations from these perijoves, we are able to study the global-averaged atmosphere and the anomalies to be compared with top atmosphere maps. The success of such a study depends on the stability of calibration between different perijoves. In order to combine those data, we investigate and remove the calibration drift with respect to time using our error analysis process. We report two outcomes from the error analysis: 1) The atmosphere stability with respect to longitude and time, as compared to the latitudinal belt and zone structures. 2) The spotted points-of-interest which lie 2 standard deviations away from the global-averaged atmosphere. We compare them with Jupiter’s surface atmosphere images taken by JunoCam, HST and JIRAM, and retrieve the corresponding NH3 volume mixing ratio from surface to over 100 bars.

The Juno spacecraft provides unique close‐up views of Jupiter underneath the synchrotron radiation belts while circling Jupiter in its 53‐day orbits. The microwave radiometer (MWR) onboard measures Jupiter thermal radiation at wavelengths between 1.37 and 50 cm, penetrating the atmosphere to a pressure of a few hundred bars and greater. The mission provides the first measurements of Jupiter's deep atmosphere, down to ~250 bars in pressure, constraining the vertical distributions of its kinetic temperature and constituents. As a result, vertical structure models of Jupiter's atmosphere may now be tested by comparison with MWR data. Taking into account the MWR beam patterns and observation geometries, we test several published Jupiter atmospheric models against MWR data. Our residual analysis confirms Li et al.'s (2017, https://doi.org/10.1002/2017GL073159) result that ammonia depletion persists down to 50–60 bars where ground‐based Very Large Array was not able to observe. We also present an extension of the study that iteratively improves the input model and generates Jupiter brightness temperature maps which best match the MWR data. A feature of Juno's north‐to‐south scanning approach is that latitudinal structure is more easily obtained than longitudinal, and the creation of optimum two‐dimensional maps is addressed in this approach.

Oxygen is the most common element after hydrogen and helium in Jupiter's atmosphere, and may have been the primary condensable (as water ice) in the protoplanetary disk. Prior to the Juno mission, in situ measurements of Jupiter's water abundance were obtained from the Galileo Probe, which dropped into a meteorologically anomalous site. The findings of the Galileo Probe were inconclusive because the concentration of water was still increasing when the probe died. Here, we initially report on the water abundance in the equatorial region, from 0 to 4 degrees north latitude, based on 1.25 to 22 GHz data from Juno Microwave radiometer probing approximately 0.7 to 30 bars pressure. Because Juno discovered the deep atmosphere to be surprisingly variable as a function of latitude, it remains to confirm whether the equatorial abundance represents Jupiter's global water abundance. The water abundance at the equatorial region is inferred to be $2.5_{-1.6}^{+2.2}\times10^3$ ppm, or $2.7_{-1.7}^{+2.4}$ times the protosolar oxygen elemental ratio to H (1$\sigma$ uncertainties). If reflective of the global water abundance, the result suggests that the planetesimals formed Jupiter are unlikely to be water-rich clathrate hydrates., Comment: 27 pages, 7 figures

Since August 2016, measurements of Jupiter's microwave emissions at six wavelengths ranging from 1.3 cm to 50 cm have been made with the Juno Microwave Radiometer (MWR). In this paper, we introduce the first systematic set of in-situ observations of synchrotron radiation in a polar plane while describing the modeling approach we use to analyze this data (collected August 27th, 2016). Time series of brightness profiles at all six frequencies present similarities that are explained by the presence of known regions of intense synchrotron radiation. Our model predictions, though limited for now to the total intensity of the radiation, reproduce (qualitatively) the observation of temporal variations and allow to disentangle the synchrotron emission from the atmospheric emission. The discrepancies seen between the data and simulations confirm that physical conditions close to Jupiter affecting synchrotron emission (electron energy spectra, pitch-angle distributions, and the magnetic environment) are different than we anticipated.

Juno swoops around giant Jupiter Jupiter is the largest and most massive planet in our solar system. NASA's Juno spacecraft arrived at Jupiter on 4 July 2016 and made its first close pass on 27 August 2016. Bolton et al. present results from Juno's flight just above the cloud tops, including images of weather in the polar regions and measurements of the magnetic and gravitational fields. Juno also used microwaves to peer below the visible surface, spotting gas welling up from the deep interior. Connerney et al. measured Jupiter's aurorae and plasma environment, both as Juno approached the planet and during its first close orbit. Science , this issue p. 821 , p. 826

The Juno Microwave Radiometer (MWR) is a six-frequency scientific instrument designed and built to investigate the deep atmosphere of Jupiter. It is one of a suite of instruments on NASA’s New Frontiers Mission Juno launched to Jupiter on August 5, 2011. The focus of this paper is the description of the scientific objectives of the MWR investigation along with the experimental design, observational approach, and calibration that will achieve these objectives, based on the Juno mission plan up to Jupiter orbit insertion on July 4, 2016. With frequencies distributed approximately by octave from 600 MHz to 22 GHz, the MWR will sample the atmospheric thermal radiation from depths extending from the ammonia cloud region at around 1 bar to pressure levels as deep as 1000 bars. The primary scientific objectives of the MWR investigation are to determine the presently unknown dynamical properties of Jupiter’s subcloud atmosphere and to determine the global abundance of oxygen and nitrogen, present in the atmosphere as water and ammonia deep below their respective cloud decks. The MWR experiment is designed to measure both the thermal radiation from Jupiter and its emission-angle dependence at each frequency relative to the atmospheric local normal with high accuracy. The antennas at the four highest frequencies (21.9, 10.0, 5.2, and 2.6 GHz) have ∼12° beamwidths and will achieve a spatial resolution approaching 600 km near perijove. The antennas at the lowest frequencies (0.6 and 1.25 GHz) are constrained by physical size limitations and have 20° beamwidths, enabling a spatial resolution of as high as 1000 km to be obtained. The MWR will obtain Jupiter’s brightness temperature and its emission-angle dependence at each point along the subspacecraft track, over angles up to 60° from the normal over most latitudes, during at least six perijove passes after orbit insertion. The emission-angle dependence will be obtained for all frequencies to an accuracy of better than one part in 10^3, sufficient to detect small variations in atmospheric temperature and absorber concentration profiles that distinguish dynamical and compositional properties of the deep Jovian atmosphere.

Goldstone Apple Valley Radio Telescope (GAVRT) is a science education partnership among NASA, the Jet Propulsion Laboratory (JPL), and the Lewis Center for Educational Research (LCER), offering unique opportunities for K -12 students and their teachers. As part of a long-term Jupiter synchrotron radiation (JSR) flux density monitoring program, LCER has been carrying out Jupiter observations with some student participation. In this paper we present the results of processed data sets observed between March 6, 2015 and April 6 2018. The data are divided into 5 epochs, grouped by time. We derive JSR beaming curves at different epochs and Earth declinations. We present a comparison of the observed beaming curves with those derived from most recent models for the radiation belts. Our results show an increasing trend of the JSR flux density which seem consistent with the models for the magnetospheric solar wind interactions., Comment: 24 pages; 9 figures To be published in PASP

The Juno spacecraft arrived at Jupiter July 4, 2016 and is now in a 53.5-day polar orbit. Synchrotron radiation generated by ultra-relativistic electrons trapped in Jupiter's magnetosphere is detected and measured by the MWR Radiometer over a range of wavelengths from 2 cm to 50 cm. An extension of the Levin et al. (2001)multi-zonal, multi-parameter model to simulate synchrotron emission using assumed electron distributions and Jovian magnetic field models (VIP4 and the latest incarnation, JRM09)generates the four Stokes parameters of the synchrotron emission. The model depends on magnetic-field-derived quantities such as L-shell and B critical, the minimum magnetic field amplitude for a given L-shell at which electrons that mirror at or below the upper boundary of the atmosphere are lost. This study describes the modeling issues associated with aforementioned derived parameters and results for VIP4 and JRM09 models.

Visible to the naked eye, the gas giants Jupiter and Saturn have been known to astronomers since antiquity. In the modern times much was learned about them, and yet so much remains to be learned. They are made almost entirely of hydrogen and helium, they have no hard surface to land to; their low temperature atmospheres are characterized by strong winds, at least in the observed upper atmosphere. What we know about them comes from remote sensing—yet their clouds impede deeper observation through remote sensing. We also have, in a singular case, data transmitted by a robotic probe that descended through the Jovian atmosphere. We need more of these probes, to confirm the models we formed about these planets, and to discover new phenomena below their clouds. This chapter examines mission concept alternatives in which robotic craft operate in the atmospheres of gas giants, for long duration, and using energy derived from local sources. In a preferred scenario these Wind Robots (WBs), with high mobility and autonomy compared to passive balloons, would operate in the Jovian atmosphere above and below the region of clouds, between 0.3 and 10 bar, for a year-long duration mission, in strong (potentially turbulent) winds. In an example, notional mission, a WB would operate in the eyewall of the Great Red Spot, using the high wind and updrafts of the anticyclone, as well as horizontal gusts. Both naturally buoyant and winged solutions, as well as hybrids of the two, are determined possible. A Network of WBs could measure wind speeds, temperatures, and atmospheric composition simultaneously, at multiple locations.

Lightning has been detected on Jupiter by all visiting spacecraft through night-side optical imaging and whistler (lightning-generated radio waves) signatures1–6. Jovian lightning is thought to be generated in the mixed-phase (liquid–ice) region of convective water clouds through a charge-separation process between condensed liquid water and water-ice particles, similar to that of terrestrial (cloud-to-cloud) lightning7–9. Unlike terrestrial lightning, which emits broadly over the radio spectrum up to gigahertz frequencies10,11, lightning on Jupiter has been detected only at kilohertz frequencies, despite a search for signals in the megahertz range 12 . Strong ionospheric attenuation or a lightning discharge much slower than that on Earth have been suggested as possible explanations for this discrepancy13,14. Here we report observations of Jovian lightning sferics (broadband electromagnetic impulses) at 600 megahertz from the Microwave Radiometer 15 onboard the Juno spacecraft. These detections imply that Jovian lightning discharges are not distinct from terrestrial lightning, as previously thought. In the first eight orbits of Juno, we detected 377 lightning sferics from pole to pole. We found lightning to be prevalent in the polar regions, absent near the equator, and most frequent in the northern hemisphere, at latitudes higher than 40 degrees north. Because the distribution of lightning is a proxy for moist convective activity, which is thought to be an important source of outward energy transport from the interior of the planet16,17, increased convection towards the poles could indicate an outward internal heat flux that is preferentially weighted towards the poles9,16,18. The distribution of moist convection is important for understanding the composition, general circulation and energy transport on Jupiter. Observations of broadband emission from lightning on Jupiter at 600 megahertz show a lightning discharge mechanism similar to that of terrestrial lightning and indicate increased moist convection near Jupiter’s poles.

The purpose of this paper is to investigate robotic mobility solutions for long-duration (∼years), in-situ scientific missions to the Jupiter atmosphere. In particular, this paper is focused on aerostatic-based mechanisms, utilizing buoyancy principles to maintain flight. Three primary aerostat types were investigated; Charliere (light-gas), Montgolfier (heated gas), and Vacuum aerostats. Supplemental systems to the aerostats were also investigated to assist with mobility control within the Jupiter atmosphere. The systems include the Balloon Guidance System (BGS) previously investigated for planetary balloons, and buoyancy controlled gliders. A Charliere would provide the most reliable lift, however one needs to ensure 13 kg of H 2 for every 1 kg of payload. A Montgolfier would not require supplemental hydrogen; further analysis is needed to evaluate flight equilibrium dynamics. A BGS would provide the increased mobility otherwise unachievable with a conventional aerostat, offering steering ability (given wind gradients) between Jupiter belts and zones. Buoyancy controlled gliding is a potential solution which if executed correctly may bridge the functionality gap between traditional aerostats (with the benefits of reliable lift), and gliders (with maneuverability and navigational abilities).

Juno’s Radiation Monitoring (RM) Investigation profiles Jupiter’s >10-MeV electron environment throughout unexplored regions of the Jovian magnetosphere. RM’s measurement approach involves active retrieval of the characteristic noise signatures from penetrating radiation in images obtained by Juno’s heavily shielded star cameras and science instruments. Collaborative observation campaigns of “radiation image” collection and penetrating particle counts are conducted at targeted opportunities within the magnetosphere during each of Juno’s perijove passes using the spacecraft Stellar Reference Unit, the Magnetic Field Investigation’s Advanced Stellar Compass Imagers, and the JIRAM infrared imager. Simultaneous observations gathered from these very different instruments provide comparative spectral information due to substantial differences in instrument shielding. Juno’s orbit provides a unique sampling of energetic particles within Jupiter’s innermost radiation belts and polar regions. We present a survey of observations of the high energy radiation environment made by Juno’s SRU and ASC star cameras and the JIRAM infrared imager during Juno’s early perijove passes on August 27 and December 11, 2016; and February 2 and March 27, 2017. The JPL author’s copyright for this publication is held by the California Institute of Technology. Government Sponsorship acknowledged.

START is a tool to optimize research and development primarily for NASA missions. It was developed within the Strategic Systems Technology Program Office, a division of the Office of the Chief Technologist at NASA's Jet Propulsion Laboratory. START is capable of quantifying and comparing the risks, costs, and potential returns of technologies that are candidates for funding. START can be enormously helpful both in selecting technologies for development – within the constraints of budget, schedule, and other resources – and in monitoring their progress. START's methods are applicable to everything from individual tasks to multiple projects comprising entire programs of investigation. They can address virtually any technology assessment and capability prioritization issue. In this report, START is used to analyze the capability needs using data from NASA's Exploration Systems Architecture Study (ESAS).

Gas giant planet atmospheres are composed primarily of hydrogen and helium along with trace constituents including methane, ammonia, water vapor, hydrogen sulfide, phosphine and others. Since the seminal work of Lewis (1969), many researchers have used 1-D adiabatic atmospheric models to calculate solid and liquid cloud structures in the giant planets. In this contribution, traditional cloud modeling approaches for liquid clouds are reconsidered with respect to state-of-the-art techniques derived from fundamental principles governing the vapor-liquid equilibrium (VLE) conditions. The technique is discussed from the perspective of binary mixtures with the provision that it can be generalized for multi-component mixtures. As a purposeful illustration, up-to-date thermodynamic properties of water and ammonia mixtures are used to investigate the aqueous ammonia clouds on Jupiter. Comparisons with the traditional approach are presented, as methodologies applied in constructing Jupiter's atmosphere. This work is related to the Microwave Radiometer (MWR) Experiment on the Juno spacecraft, which has the capability of sensing the brightness temperature of Jupiter in the vicinity of the cloud structures, from 0.5 atm to over 300 atm pressure.

A closure for the compressible portion of the pressure-strain covariance is developed. It is shown that, within the context of a pressure-strain closure assumption linear in the Reynolds stresses, an expression for the pressure-dilatation can be used to construct a representation for the pressure-strain. Additional closures for the unclosed terms in the Favre–Reynolds stress equations involving the mean acceleration are also constructed. The closures accommodate compressibility corrections depending on the magnitude of the turbulent Mach number, the mean density gradient, the mean pressure gradient, the mean dilatation, and, of course, the mean velocity gradients. The effects of the compressibility corrections on the Favre–Reynolds stresses are consistent with current DNS results. Using the compressible pressure-strain and mean acceleration closures in the Favre–Reynolds stress equations an algebraic closure for the Favre–Reynolds stresses is constructed. Noteworthy is the fact that, in the absence of mean velocity gradients, the mean density gradient produces Favre–Reynolds stresses in accelerating mean flows. Computations of the mixing layer using the compressible closures developed are described. Favre–Reynolds stress closure and two-equation algebraic models are compared to laboratory data for the mixing layer. Experimental data from diverse laboratories for the Favre–Reynolds stresses appears inconsistent and, as a consequence, comparison of the Reynolds stress predictions to the data is not conclusive. Reductions of the kinetic energy and the spread rate are consistent with the sizable decreases seen in these classes of flows.

Explicit algebraic scalar-flux models that are valid for three-dimensional turbulent flows are derived from a hierarchy of second-order moment closures. The mathematical procedure is based on the Cayley–Hamilton theorem and is an extension of the scheme developed by Taulbee. Several closures for the pressure–scalar gradient correlations are considered and explicit algebraic relations are provided for the velocity–scalar correlations in both nonreacting and reacting flows. In the latter, the role of the Damkohler number is exhibited in isothermal turbulent flows with nonpremixed reactants. The relationship between these closures and traditional models based on the linear gradientdiffusion approximation is theoretically established. The results of model predictions are assessed by comparison with available laboratory data in turbulent jet flows.

Results are presented for three‐dimensional direct numerical simulations of nonhelical magnetohydrodynamic (MHD) turbulence for both stationary isotropic and homogeneous shear flow configurations with zero mean induction and unity magnetic Prandtl number. Small scale dynamo action is observed in both flows, and stationary values for the ratio of magnetic to kinetic energy are shown to scale nearly linearly with the Taylor microscale Reynolds numbers above a critical value of Reλ≊30. The presence of the magnetic field has the effect of decreasing the kinetic energy of the flow, while simultaneously increasing the Taylor microscale Reynolds number due to enlargement of the hydrodynamic length scales. For shear flows, both the velocity and the magnetic fields become increasingly anisotropic with increasing initial magnetic field strength. The kinetic energy spectra show a relative increase in high wave‐number energy in the presence of a magnetic field. The magnetic field is found to portray an intermittent b...

With the goal of facilitating communication and cooperation between NASA’s scientific and engineering/design communities, a tool (in the form of a table) is developed which displays the majority of the architectural-parameter trade space under consideration for a given mission, enabling all interested parties to see which sets of constraints would be acceptable for a desired level of science or any other objective. A combination of computer optimization runs and interpolation is employed to enable calculation of the table within a reasonable period of time. Three alternative interpolation methods (radial basis function (RBF), kriging, and regression) are investigated. A hypothetical mission to the Moon’s Schrodinger crater serves as a test case. Kriging, with the lowest average error rate, is judged to be the best interpolation method for this case study, but the more consistent results of the regression method may be preferable in certain other circumstances.

Complex technology investment decisions within NASA are increasingly difficult to make such that the end results are satisfying the technical objectives and all the organizational constraints. Due to a restricted science budget environment and numerous required technology developments, the investment decisions need to take into account not only the functional impact on the program goals, but also development uncertainties and cost variations along with maintaining a healthy workforce. This paper1,2 reviews a utility-based approach for optimizing and qualifying technology investment portfolios from the perspective of an integrated system model. The methodology encompasses multi-attribute decision theory elements and sensitivity analysis. The evaluation of the degree of robustness of the recommended portfolio provides the decision-maker with an array of viable selection alternatives, which take into account input uncertainties and possibly satisfy non-technical constraints. The methodology is presented in the context of assessing capability development portfolios for NASA technology programs.

We formulate, model and analyze two proposed missions near the lunar south pole of different durations and scientific emphasis. Each mission is conducted by two teams of two astronauts riding in two pressurized rovers. Each team must remain within the same locality as the other team in case there is need for a rescue. Our analytical approach combines the best features of two analytic techniques, SciMax and HURON, to overcome difficulties of combinatorial explosiveness of the trade space, and to enable scheduling of “as much science as possible” rather than an inflexible set of experiments that may not make optimal use of available time. Weighting of individual science goals leads to different sets of scientific investigations and different amounts of time to be spent at the various sites. We demonstrate that increased rover driving speeds increases the amount of time available to spend at sites, and thus increases science productivity dramatically up to a point. Beyond that point, increasing driving speed improves productivity marginally due to the lack of availability of EVA time.

The productivity of scientific exploration of the Moon and Mars has been significantly improved through the mobility of roving vehicles (rovers) since these vehicles allow scientists to conduct operations well beyond the immediate vicinity of the landing area. This paper reports on a quantitative approach developed to evaluate the productivity of alternative human and robot work-system alternatives for a lunar science mission. A graph-search approach for task planning was used for assigning human and robotic work systems to scientific tasks in order to evaluate the productivity of different mobility options. The results were used to identify the benefits and costs of alternative rover combinations in order to establish guidelines for the roles of the different vehicle types. Pressurized rovers displayed advantages over unpressurized rovers due to enhanced range and duration yielding more science productivity. Multiple pressurized rovers were found to be more productive than multiple unpressurized rovers.

In a restricted science budget environment and increasingly numerous required technology developments, the technology investment decisions within NASA are objectively more and more difficult to make such that the end results are satisfying the technical objectives and all the organizational constraints. Under these conditions it is rationally desirable to build an investment portfolio, which has the highest possible technology infusion rate into flight missions. Arguably the path to infusion is subject to many influencing factors, but here only the challenges associated with the very initial stages are addressed: defining the needs and the subsequent investment decision-support process. It is conceivable that decision consistency and possibly its quality suffer when the decision-making process has limited or no traceability. This paper presents a structured decision-support framework aiming to provide traceable, auditable, infusion-driven recommendations towards a selection process in which these recommendations are used as reference points in further discussions among stakeholders. In this framework addressing well-defined requirements, different measures of success can be defined based on traceability to specific selection criteria. As a direct result, even by using simplified decision models the likelihood of infusion can be probed and consequently improved.

A series of studies is conducted to develop a systematic approach to optimizing, both in terms of the distribution and scheduling of tasks, scenarios in which astronauts and robots accomplish a group of activities on the Moon, given an objective function (OF) and specific resources and constraints. An automated planning tool is developed as a key element of this optimization system.

A study is conducted to determine the relative productivity of employing two pressurized or two unpressurized robotic rovers with two teams of astronauts to accomplish a group of activities on the Moon. An automated planning tool is used to calculate the optimal sequence of events, given an objective function and sets of assumptions and constraints. For the mission scenario studied, a pair of pressurized rovers is shown to be about 7 times as productive as a pair of unpressurized rovers when calculating benefits divided by marginal operational costs. This is primarily due to a constraint that limits astronauts to a maximum of 8 hours per day in space suits. The unpressurized rovers require the astronauts to wear space suits at all times, severely limiting the distance they can travel from the lander-habitat; the pressurized rovers permit the astronauts to remove their suits while driving, monitoring robotic activities, and resting between work periods.

The Jet Propulsion Laboratory (JPL) formulates and conducts deep space missions for NASA (the National Aeronautics and Space Administration). The Chief Technologist of JPL has responsibility for strategic planning of the laboratory's advanced technology program to assure that the required technological capabilities to enable future missions are ready as needed. The responsibilities include development of a Strategic Plan (Antonsson, E., 2005). As part of the planning effort, a structured approach to technology prioritization, based upon the work of the START (Strategic Assessment of Risk and Technology) (Weisbin, C.R., 2004) team, was developed. The purpose of this paper is to describe this approach and present its current status relative to the JPL technology investment.

As part of a multi-agency effort to improve America's air transportation system, NASA has undertaken a study to develop and demonstrate a systematic method for selecting capability investments based on their projected return on investment.

Large Eddy Simulations and RANS predictions have been carried out for a generic primary zone type jet configuration, for which significant LDA experimental data is available. It consists of an annular passage feeding a row of ports that issue jets into a confined crossflow. A bleed flow of 50% past the ports in the feed annulus and a jet to cross flow ratio of 5 are set-up in order to be representative of annulus fed primary jets. Time averaged inlet boundary conditions have been taken from experimental data and have had time-correlated fluctuations with the correct RMS values and time scales imposed on them. Calculations have been performed on a modest PC cluster using the CFD-ACE+ flow solver package. Results show that LES is able to surpass RANS quantitatively and qualitatively. At the time-average impingement point of the jets the LES predicted normal stresses are in considerably better agreement with experimental data than is RANS, which is to be expected considering the limitations of k-e models relying upon linear stress-strain relationships. Phenomena impossible to capture using RANS are also well predicted by LES, such as bimodal pdf’s that have been witnessed at the time average stagnation point where the cross flow and jet back flow meet. By solving for a conserved scalar it has also been possible to examine mixing rates within the recirculation zone.Copyright © 2003 by ASME

Application and testing of the new combustion Large Eddy Simulation (LES) code for the design of advanced gaseous combustion systems is described in this 12th quarterly report. In this quarter, continued validation and testing of the combustion LES code was performed for the DOE-SimVal combustor. Also, beta testing by six consortium members was performed for various burner and combustor configurations. A list of suggested code improvements by the beta testers was itemized. Work will continue in FY04. A conditional modification to the contract will be granted. The additional work will focus on modeling/analyzing the SimVal experiments.

Further development of a combustion Large Eddy Simulation (LES) code for the design of advanced gaseous combustion systems is described in this fifth quarterly report. CFD Research Corporation (CFDRC) is developing the LES module within the parallel, unstructured solver included in the commercial CFD-ACE+ software. In this quarter, in-situ adaptive tabulation (ISAT) for efficient chemical rate storage and retrieval was further tested in the LES code. The use of multiple trees and periodic tree dumping was investigated. Implementation of the Linear Eddy Model (LEM) for subgrid chemistry was finished for serial applications. Validation of the model on a backstep reacting case was performed. Initial calculations of the SimVal experiment were performed for various barrel lengths, equivalence ratio, combustor shapes, and turbulence models. The effects of these variables on combustion instability was studied. Georgia Tech continues the effort to parameterize the LEM over composition space so that a neural net can be used efficiently in the combustion LES code. Next quarter, the 2nd consortium meeting will be held at CFDRC. LES software development and testing will continue. Alpha testing of the code will be performed on cases of interest to the industrial consortium. Optimization of subgrid models will be pursued, particularly with the ISAT approach. Also next quarter, the demonstration of the neural net approach, for chemical kinetics speed-up in CFD-ACE+, should be accomplished.

Vision 21 combustion systems will require innovative low emission designs and low development costs if Vision 21 goals are to be realized. In this three-year project, an advanced computational software tool will be developed for the design of low emission combustion systems required for Vision 21 clean energy plants. The combustion Large Eddy Simulation (LES) software will be able to accurately simulate the highly transient nature of gaseous-fueled turbulent combustion so that innovative concepts can be assessed and developed with fewer high-cost experimental tests. During the first year, the project included the development and implementation of improved chemistry (reduced GRI mechanism), subgrid turbulence (localized dynamic), and subgrid combustion-turbulence interaction (Linear Eddy) models into the CFDACE+ code. University expertise (Georgia Tech and UC Berkeley) was utilized to help develop and implement these advanced submodels into the unstructured, parallel CFD flow solver, CFD-ACE+. Efficient numerical algorithms that rely on in situ look-up tables or artificial neural networks were implemented for chemistry calculations. In the second year, the combustion LES software was evaluated and validated using experimental data from lab-scale and industrial test configurations. This code testing (i.e., alpha testing) was performed by CFD Research Corporation's engineers. During the third year, six industrial and academic partners used the combustion LES code and exercised it on problems of their choice (i.e., beta testing). Final feedback and optimizations were then be implemented in the final release version of the combustion LES software that will be licensed to the general public. An additional one-year task was added for the fourth year of this program entitled, ''LES Simulations of SIMVAL Results''. For this task, CFDRC performed LES calculations of selected SIMVAL cases, and compared predictions with measurements. In addition to comparisons with NO{sub x} and CO exit measurements, comparisons were made to measured pressure oscillations. Possible gaps in the data sets were identified, as well as potential areas of improvement for combustion and turbulence models. Work in this seventeenth quarter (October-December 2004) consisted of writing the draft final report for review by DOE. The report was delivered to DOE in January, 2005.

A lean premixed fuel injector/combustor typical of industrial gas turbine combustors has been analyzed using 3D Large Eddy Simulation (LES) methods. The objective of the study was to evaluate the 3D LES modeling approach for predicting combustion dynamics and compare it with simpler unsteady Reynolds Averaged Navier Stokes (RANS) methods using 2D and 3D analyses. Large amplitude pressure oscillations were observed experimentally at the modeled operating conditions, and previous 2D axisymmetric unsteady RANS analysis has shown reasonable, but not perfect, engineering agreement with pressure measurements. Although the pressure amplitude was accurately predicted, the frequency was substantially in error. This study sought to see if 3D modeling would improve the agreement. 2D axisymmetric and full 3D calculations were performed with a state-of-the-art, unstructured-grid, parallel (domain decomposition) CFD code. For the unsteady RANS calculations, the RNG k-ε turbulence model was employed, while for the LES calculation the Smagorinsky subgrid turbulence model was employed. Surprisingly, the 2D unsteady RANS, 3D unsteady RANS, and 3D LES calculations gave nearly identical pressure oscillation predictions, and all calculations had the oscillation frequency around 280 Hertz. This work has shown that smaller turbulent structures captured with 3D LES have very little effect on capturing combustion instability driven primarily by a fuel time-lag.