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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.

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).

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.

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.

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 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.

Two concepts for large-scale, complex, robotic missions to search for frozen water at the lunar South Pole are systematically analyzed to determine their relative productivity and investment requirements. The Strategic Assessment of Risk and Technology (START) methodology and tool are utilized to determine temporal R&D-investment recommendations to optimize mission performance goals subject to budget, workforce, and other non-technical constraints. Explicit distinction is made between enabling and enhancing technologies. Uncertainties and dependencies are included within the optimization framework. This study determined that given the constraints used in this analysis, the longer mission would return 12 times the value of the shorter mission for roughly an 11% increase in cost, and would be enabled with the recommended temporal technology portfolio.

This paper discusses the process and results of technology assessment in support of the United States vision for space exploration of the Moon, Mars and beyond. The paper begins by reviewing the presidential vision: a major endeavor in building systems of systems. It discusses why we wish to return to the Moon, and the exploration architecture for getting there safely, sustaining a presence, and safely returning. Next, a methodology for optimal technology investment is proposed with discussion of inputs including a capability hierarchy, mission importance weightings, available resource profiles as a function of time, likelihoods of development success, and an objective function. A temporal optimization formulation is offered, and the investment recommendations presented along with sensitivity analyses. Key questions addressed are sensitivity of budget allocations to cost uncertainties, reduction in available budget levels, and shifting funding within constraints imposed by mission timeline.

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.