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Mars OASIS (Mars Operational Agricultural System for In-Situ Specialization) System Reference Manual

In order to enable long term habitation on planetary surfaces, a means of sustainable food production must be developed. Addressing this need for surface habitats on Mars, the MarsOASIS team has developed a concept for a Martian surface greenhouse for unmanned crop production research as a proof of concept for larger scale food production facilities for manned surface missions. Utilizing in-situ resources such as the Martian atmosphere, sunlight, and UV-C radiation, the greenhouse aims to provide a sustainable method of long-term food production requiring minimal consumable resources. The MarsOASIS system is capable of growing a full life cycle of Outredgeous lettuce with its autonomous control system designed for a unmanned environment, only requiring teleoperation in extreme circumstances. A reduced-scope prototype of MarsOASIS is being developed to test technologies such as a natural/artificial hybrid lighting system, a closed water recycling system, remote teleoperation, and fully autonomous monitoring and control of the greenhouse. The prototype is currently in the final stages of design, with a full demonstration of plant life cycle testing set to occur in summer 2015. Results from this prototype demonstration will help quantify the feasibility of the innovative approaches seen in the MarsOASIS design.

Asa Darnell↗

Tropical Convection Through the Lens of the INCUS Mission

The overarching goal of the recently selected NASA INvestigation of Convective UpdraftS (INCUS) mission is to enhance our understanding of why, when and where tropical convective storms form, and why only some of these storms produce extreme weather. Convective storms provide an important pathway for the transport of air and water between Earth’s surface and the upper troposphere. This vertical transport of air and water, often referred to as convective mass flux (CMF), plays a critical role in Earth’s weather and climate system through its impacts on microphysical and precipitation rates, detrainment and upper tropospheric moistening, high cloud feedbacks, and the large-scale circulation. Potential changes to the CMF as a function of the local environment or with changing climates may also have significant implications for severe weather such as flood-producing rainfall, damaging hail and lightning. In spite of the critical role of this vertical transport of water and air, representation of CMF remains a major source of error in weather and climate models, thereby limiting our ability to accurately predict convective storms and their impacts. The tropics-wide observations from INCUS will enhance our understanding of tropical convective storm processes and will provide guidance for representing these processes in numerical models across scales. INCUS is comprised of three SmallSat platforms each carrying a RainCube-heritage Ka-band 7-beam scanning radar. The satellite platforms will be 30 and 90 seconds apart, thus providing three time intervals (30, 90 and 120 seconds) over which observations will be made. INCUS will investigate CMF using a novel time-differenced radar reflectivity profile approach. In addition to the Ka-band radar, a single TEMPEST-D-heritage cross-track-scanning passive microwave radiometer will be housed on the middle SmallSat. The radiometer will provide extensive storm context for the radar observations, as well as observations of the convective anvils. The combination of the radars and radiometer on INCUS will deliver unprecedented three-dimensional views of tropical convective storms. INCUS is the first systematic investigation of the rapidly evolving CMF within tropical convective storms, the observations of which are expected to significantly enhance both our understanding and prediction of storm structure, their dynamics and microphysical processes, and the ways in which these evolve over storm lifetimes. This presentation will highlight the observational capabilities and scientific approach of the INCUS mission.

Susan C. van den Heever↗

In-Space Transportation Sensitivity to Roundtrip Mission Duration and Mars Vicinity Stay Time

The National Aeronautics and Space Administration’s Exploration Systems Development Mission Directorate has been developing architecture concepts for human missions to Mars in alignment with the agency’s Moon-to-Mars Strategy & Objectives. One of the key components of a human Mars mission is the in-space transportation system that delivers crew and cargo to Mars vicinity and returns the crew safely back to Earth. The Mars Architecture Team within ESDMD’s Strategy and Architecture Office has been evaluating multiple in-space transportation options to satisfy this functional need. The first step of this evaluation is to understand key architectural drivers for in-space transportation systems. Lunar and Mars missions have unique challenges, and systems designed for one may not be directly applicable to the other as they have different energy and mission needs. In addition, the time and distance for a Mars mission will be drastically different from the historical and current programs, requiring a new paradigm for mission architects. This paper investigates the impact of mission duration on a variety of different transportation options. As mission duration decreases, the total energy required to perform a roundtrip Mars mission increases exponentially, significantly increasing the required Earth departure mass. Sensitivity analyses of various in-space transportation system concepts were shown in this paper to begin mapping out the in-space transportation trade space. Each of the transportation systems has its own strengths and weaknesses, especially in the context of the continuous mission duration and vicinity stay time trade space. Although mission duration and Mars vicinity stay time may be key architecture drivers from an in-space transportation perspective, the decision of acceptable mission duration cannot be made solely from this perspective. Mission duration also has tangible impacts to crew health and performance, as well as system reliability and other key architecture considerations. The integrated nature of the architecture decision road map will be the primary focus of the Mars Architecture Team in the coming analysis cycle. This in-space transportation analysis will serve as the first guidepost of this critical activity that will guide the Moon-to-Mars Architecture into the humans to Mars segment.

Mars↗

In-Space Transportation Sensitivity to Roundtrip Mission Duration and Mars Vicinity Stay Time

The National Aeronautics and Space Administration’s Exploration Systems Development Mission Directorate has been developing architecture concepts for human missions to Mars in alignment with the agency’s Moon-to-Mars Strategy & Objectives. One of the key components of a human Mars mission is the in-space transportation system that delivers crew and cargo to Mars vicinity and returns the crew safely back to Earth. The Mars Architecture Team within ESDMD’s Strategy and Architecture Office has been evaluating multiple in-space transportation options to satisfy this functional need. The first step of this evaluation is to understand key architectural drivers for in-space transportation systems. Lunar and Mars missions have unique challenges, and systems designed for one may not be directly applicable to the other as they have different energy and mission needs. In addition, the time and distance for a Mars mission will be drastically different from the historical and current programs, requiring a new paradigm for mission architects. This paper investigates the impact of mission duration on a variety of different transportation options. As mission duration decreases, the total energy required to perform a roundtrip Mars mission increases exponentially, significantly increasing the required Earth departure mass. Sensitivity analyses of various in-space transportation system concepts were shown in this paper to begin mapping out the in-space transportation trade space. Each of the transportation systems has its own strengths and weaknesses, especially in the context of the continuous mission duration and vicinity stay time trade space. Although mission duration and Mars vicinity stay time may be key architecture drivers from an in-space transportation perspective, the decision of acceptable mission duration cannot be made solely from this perspective. Mission duration also has tangible impacts to crew health and performance, as well as system reliability and other key architecture considerations. The integrated nature of the architecture decision road map will be the primary focus of the Mars Architecture Team in the coming analysis cycle. This in-space transportation analysis will serve as the first guidepost of this critical activity that will guide the Moon-to-Mars Architecture into the humans to Mars segment.

Mars↗

Analysis of a Bank Control Guidance for Aerocapture at Uranus

We apply the Fully Numerical Predictor-corrector Aerocapture Guidance to capture a vehicle into orbit for a mission at Uranus. Using the Genesis flight mechanics simulation, we analyze both undispersed and dispersed trajectories in order to tune the guidance parameters. We then assess the performance of the guidance using Monte Carlo analyses. Properly accounting for the oblateness of Uranus within the guidance proves to be critical. We identify high-to-low density gradients as the cause of large target orbit misses. Intentionally targeting a steeper flight-path angle at entry interface mitigates the risk of exiting the atmosphere on a hyperbolic orbit. Finally, We deliver the guidance code and tuned parameters for integration into the Program to Optimize Simulated Trajectories II.

Daniel A Matz↗

Uranus Flagship-class Orbiter and Probe Using Aerocapture

Exploration of the Ice Giants, especially Uranus, via orbiter and atmospheric probes, is required to answer pressing science questions that have been raised in the latest National Academies of Sciences Planetary Decadal Survey. Since the Ice Giants are the farthest planets from Earth, traditional fully-propulsive orbit insertion missions have transit times to the planetary bodies bordering 13-15 years and require a large amount of propellant (wet mass percentages of around 60-70%) for the orbit insertion maneuver, leaving less mass for the scientific payload and a planetary probe. Aerocapture uses aerodynamic forces generated by flight within a planetary atmosphere to decelerate and achieve orbit insertion. Aerocapture has been considered for several past missions but it has not been demonstrated. However, recent developments in thermal protection systems (TPS), guidance and control (G&C), and interplanetary navigation capabilities show the potential for using rigid, heritage entry vehicle configurations already flown at other planetary bodies for Ice Giants aerocapture. Aerocapture can robustly deliver spacecraft to Ice Giant orbits, while substantially increasing on-orbit payload mass (more than 40%) that can be used for a robust atmospheric entry probe. Additionally, the aerocapture maneuver would reduce the interplanetary transit time by 2-5 years (15-30%) relative to fully-propulsive orbit insertion. Recent work has shown that a flagship-class mission can be conducted in a shorter time than fully-propulsive missions if using aerocapture. This paper will consider the merits of including aerocapture as the orbit-insertion mechanism for a Uranus mission. Specifically, the implications of aerocapture orbit insertion for in-situ atmospheric probes will be discussed. The Uranus Orbiter and Probe concept mission study [3] is considered as the potential payload. Results from a recent NASA Space Technology Mission Directorate (STMD)-funded activity that is designing an aerocapture mission for a Uranus orbiter will be presented.

Soumyo Dutta↗

DAVINCI: Venus Atmospheric Model Comparisons

The Deep Atmosphere Venus Investigation of Noble gases, Chemistry, and Imaging(DAVINCI) mission aims to answer long-standing questions regarding Venus’ origin using Zephyr, an atmospheric descent probe. Zephyr will be the first probe to take high-resolution aerial photographs of a mountainous tesserae surface as it descends over the Alpha Regio highlands region, which has the oldest surfaces of Venus. The Zephyr’s descent trajectory that determines the touchdown in the Alpha Regio, which is crucial for the DAVINCI mission, depends on Venus’ atmospheric properties and winds. Unfortunately, the atmospheric data for Venus from previous missions is sparse. Therefore, it is essential to consider various atmospheric models and scenarios from past flight data to predict Zephyr’s flight performance, specifically landing ellipse. To this end, this work compares three atmospheric models: the Venus Global Reference Atmospheric Model (Venus-GRAM), the Venus Climate Database(VCD), and an empirical wind model developed by Ralph Lorenz for the DAVINCI trajectory simulation and modeling. This paper compares the mean and variations of different atmospheric properties and winds from these atmospheric models. In addition, this work combines the atmospheric properties and the wind variability from the Venus-GRAM with the winds from the Lorenz-based model to have more stressing Venus wind dispersions that allow for more conservative trajectory analysis. Furthermore, this work relies on the DAVINCI landing ellipse size as a metric to measure how robust the trajectory analysis will be to the change in the atmospheric properties and winds of the Venus atmosphere.

Pardha Sai Chadalavada↗

Performance Analysis of Aerocapture Systems for Uranus Orbiters

A Uranus orbiter and probe mission is the highest priority science mission of the current decade. Aerocapture can be employed to support these missions by enabling shorter interplanetary trajectories and requiring less fuel for orbit insertion. This paper investigates the trajectory design and performance analysis of Uranus aerocapture using an MSL-derived aeroshell design. The trajectory tradespace for Uranus aerocapture is investigated to understand the relationship between interplanetary arrival speed and aeroshell aerodynamics to controllability. A 3 degree-of-freedom simulation framework is developed to assess the performance of bank angle fully numerical predictor-corrector aerocapture guidance. A series of Monte Carlo sensitivity studies are conducted to assess the effects that arrival navigation, arrival speeds, and atmosphere knowledge have on the aerocapture robustness and performance. The results suggest that bank angle modulation is a feasible option for Uranus orbit insertion where aerocapture can reduce transit times by 40% and save 1950 kg in propellant mass.

Rohan G. Deshmukh↗

Sustainable Crop Cultivation in Space Analogs: A BRIDGES Methodology Perspective Through SpaCEA

Sustainable crop cultivation in space holds paramount significance for the support of life in future long-duration missions. This research explores the development and integration of innovative low-cost proof-of-concept (LC-POC) plant growth cabinets tailored for use in space analog missions. By outlining past and current efforts in space farming, this study introduces the SpaCEA Cabinet using BRIDGES framework, establishing a context for reproducible experiments and innovation in plant growth systems. The SpaCEA cabinets can either be delivered in flat packs or assembled on-site, employing cutting-edge methods like 3-D printing and laser cutting. The main objective is to assess how effectively these structures foster crop growth within analog environments while replicating conditions crucial for space exploration. Employing a multi-faceted approach encompassing technical and qualitative dimensions, this project integrates a qualitative investigation where representatives managing analog stations and analog astronauts will partake in interviews and questionnaires to discern specific requirements and challenges within these environments. Insights gained from these engagements will significantly define the final design parameters of updated SpaCEA plant growth cabinets. The practical applicability of these cabinets emphasizes ease of assembly and transportation, addressing the inherent spatial and logistical constraints associated with space missions. Furthermore, the BRIDGES framework ensures the standardization of hardware, software, and data-gathering elements within a unified structure, which utilizes cutting-edge manufacturing technologies for the prototyping and deployment of these cabinets. The anticipated outcomes of this research include the identification of key design considerations and technical specifications for plant growth cabinets tailored to space farming analog systems. This research is poised to contribute valuable knowledge to sustainable space exploration through the development of interoperable plant growth systems for analog environments, advancing research in space crop cultivation which will make up part of a larger bioregenerative life support system.

Advanced Life Support↗

Performance Analysis of Aerocapture Systems for Uranus Orbiters

A Uranus orbiter and probe mission is the highest priority science mission of the current decade. Aerocapture can be employed to support these missions by enabling shorter interplanetary trajectories and requiring less fuel for orbit insertion. This paper investigates the trajectory design and performance analysis of Uranus aerocapture using an MSL-derived aeroshell design. The trajectory tradespace for Uranus aerocapture is investigated to understand the relationship between interplanetary arrival speed and aeroshell aerodynamics to controllability. A 3 degree-of-freedom simulation framework is developed to assess the performance of bank angle fully numerical predictor-corrector aerocapture guidance. A series of Monte Carlo sensitivity studies are conducted to assess the effects that arrival navigation, arrival speeds, and atmosphere knowledge have on the aerocapture robustness and performance. The results suggest that bank angle modulation is a feasible option for Uranus orbit insertion where aerocapture can reduce transit times by 40% and save 1950 kg in propellant mass.

Rohan Deshmukh↗

Sustainable Crop Cultivation in Space Analogs: A BRIDGES Methodology Perspective Through SpaCEA

Sustainable crop cultivation in space holds paramount significance for the support of life in future long-duration missions. This research explores the development and integration of innovative low-cost proof-of-concept (LC-POC) plant growth cabinets tailored for use in space analog missions. By outlining past and current efforts in space farming, this study introduces the SpaCEA Cabinet using BRIDGES framework, establishing a context for reproducible experiments and innovation in plant growth systems. The SpaCEA cabinets can either be delivered in flat packs or assembled on-site, employing cutting-edge methods like 3-D printing and laser cutting. The main objective is to assess how effectively these structures foster crop growth within analog environments while replicating conditions crucial for space exploration. Employing a multi-faceted approach encompassing technical and qualitative dimensions, this project integrates a qualitative investigation where representatives managing analog stations and analog astronauts will partake in interviews and questionnaires to discern specific requirements and challenges within these environments. Insights gained from these engagements will significantly define the final design parameters of updated SpaCEA plant growth cabinets. The practical applicability of these cabinets emphasizes ease of assembly and transportation, addressing the inherent spatial and logistical constraints associated with space missions. Furthermore, the BRIDGES framework ensures the standardization of hardware, software, and data-gathering elements within a unified structure, which utilizes cutting-edge manufacturing technologies for the prototyping and deployment of these cabinets. The anticipated outcomes of this research include the identification of key design considerations and technical specifications for plant growth cabinets tailored to space farming analog systems. This research is poised to contribute valuable knowledge to sustainable space exploration through the development of interoperable plant growth systems for analog environments, advancing research in space crop cultivation which will make up part of a larger bioregenerative life support system.

Advanced Life Support↗

Calculating the High-Latitude Ionospheric Electrodynamics Using A Machine Learning-Based Field-Aligned Current Model

We introduce a new framework called Machine Learning (ML) based Auroral Ionospheric electrodynamics Model (ML-AIM). ML-AIM solves a current continuity equation by utilizing the ML model of Field Aligned Currents of Kunduri et al. (2020, https://doi.org/10.1029/2020JA027908), the FAC-derived auroral conductance model of Robinson et al. (2020, https://doi.org/10.1029/2020JA028008), and the solar irradiance conductance model of Moen and Brekke (1993, https://doi.org/10.1029/92gl02109). The ML-AIM inputs are 60-min time histories of solar wind plasma, interplanetary magnetic fields (IMF), and geomagnetic indices, and its outputs are ionospheric electric potential, electric fields, Pedersen/Hall currents, and Joule Heating. We conduct two ML-AIM simulations for a weak geomagnetic activity interval on 14 May 2013 and a geomagnetic storm on 7–8 September 2017. ML-AIM produces physically accurate ionospheric potential patterns such as the two-cell convection pattern and the enhancement of electric potentials during active times. The cross polar cap potentials (ΦPC) from ML-AIM, the Weimer (2005, https://doi.org/10.1029/2004ja010884) model, and the Super Dual Auroral Radar Network (SuperDARN) data-assimilated potentials, are compared to the ones from 3204 polar crossings of the Defense Meteorological Satellite Program F17 satellite, showing better performance of ML-AIM than others. ML-AIM is unique and innovative because it predicts ionospheric responses to the time-varying solar wind and geomagnetic conditions, while the other traditional empirical models like Weimer (2005, https://doi.org/10.1029/2004ja010884) designed to provide a quasi-static ionospheric condition under quasi-steady solar wind/IMF conditions. Plans are underway to improve ML-AIM performance by including a fully ML network of models of aurora precipitation and ionospheric conductance, targeting its characterization of geomagnetically active times.

auroral electrodynamics↗

Rolling Horizon with K-Position Search Method for Strategic Deconfliction of Package Delivery UAS

In this research, the strategic deconfliction of unmanned aircraft systems for an urban package delivery environment with two depots and multiple drop-off locations is studied. This research aims to formulate a mathematical model to compute both the departure sequence and scheduled time of departure for each unmanned aircraft system at a depot, considering temporal constraints at en-route crossing waypoints and depots for strategic deconfliction. However, the problem formulation results in an NP-hard mixed-integer nonlinear programming problem for the global optimal solution, so instead, a "rolling horizon with𝑘-position search"heuristic method is developed. The simulation studies show that an increase in the value of𝑘(the parameter used to determine the size of the local neighborhood) reduces the average ground delay at the cost of an increase in the computation time for a given problem size. The study also shows an order of magnitude increase in the maximum number of flights scheduled with the integration of rolling horizon (time decomposition) compared to those without the integration of rolling horizon in the heuristic algorithm for a given computation time cut off.

UTM↗

Rolling Horizon with K-Position Search Method for Strategic Deconfliction of Package Delivery UAS

This research focuses on the strategic deconfliction of unmanned aircraft systems (UAS) in an urban package delivery environment with two depots and multiple drop-off locations. Since the formulated mixed-integer nonlinear programming (MINLP) problem is non-deterministic polynomial-time (NP) hard, a heuristic algorithm called "rolling horizon with k-position search (KPS)" is used to compute the departure sequence and scheduled time of departure (STD) of each UAS at a depot, considering temporal constraints at en-route crossing waypoints and depots for strategic deconfliction. The simulation studies show that an increase in the value of k (local neighborhood search) in the KPS reduces the average ground delay at the cost of an increase in the computation time for a given number of UAS, size of the rolling horizon window, and number of depots involved in the local neighborhood search. The studies also show that for a given rolling horizon window, the computation time increases exponentially with an increase in the total number of UAS flights when serial processing the local neighborhood search of KPS (with k > 1) and drops by an order of magnitude upon performing the local neighborhood search of KPS using parallel processing instead of serial processing. The computation time drops with the reduction in air traffic complexity of a scenario for a given number of flights, k (local neighborhood search), and rolling horizon window.

UTM↗