An Experimental Approach to Inform Venus Astrobiology Mission Design and Science Objectives
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Daniel Duzdevich↗
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Rapid sterilizing strategies for N95 respirators to design mission ready PPE for first responders.
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Biological Science↗
Automatic Design of Missions to Small Bodies
The new JPL Small-Body Automatic Mission-Design System comprises two main elements: a database of pre-computed mission options to all known asteroids and comets, and an interactive web interface that can be used to design transfers to each small body. The system is kept current with the JPL Small Body orbit catalog, is publicly available, and can be accessed from the JPL Solar System Dynamics Group website. The missions computed by the automatic system are impulsive. However, a low-thrust v estimate is also provided. The database of pre-computed missions can be filtered to find potential targets with certain orbital and physical properties, and that meet specific mission-design constraints. In addition to describing the system in detail, this paper presents empirical analytic expressions to approximate the impulsive v requirements of missions to comets and to each family of asteroids, obtained by fitting statistical data. To show how the interactive interface works, we consider mission options to asteroid 99942 Apophis. We also include optimal mission opportunities to other selected small bodies.
Farnocchia, Davide↗
Human Health and Performance Aspects of Mars Design Reference Mission of July, 1997
The human element is the most complex element of the mission design Mars missions will pose significant physiological and psychological challenges to crew members Some challenges (human engineering, life support) must be overcome (potential "non-starters") Some challenges (bone, radiation) may be show-stoppers ISS will only Indirectly address Mars questions before any "Go/No Go" decision Significant amount of ground-based and specialized flight research will be required -- Critical Path Roadmap project will direct HSLSPO's research toward Mars exploration objectives
Charles, John B.↗
Space Mission Concept Design at the NASA Ames Mission Design Center (MDC)
No abstract available
Mauro, David↗
Space Mission Concept Design at the NASA Ames Mission Design Center (MDC)
No abstract available
Mauro, David↗
Guidelines and Capabilities for Designing Human Missions
The human element is likely the most complex and difficult one of mission design; it significantly influences every aspect of mission planning, from the basic parameters like duration to the more complex tradeoffs between mass, volume, power, risk, and cost. For engineers who rely on precise specifications in data books and other such technical references, dealing with the uncertainty and the variability of designing for human beings can be frustrating. When designing for the human element, questions arise more often than definitive answers. Nonetheless, we do not doubt that the most captivating discoveries in future space missions will necessitate human explorers. These guidelines and capabilities are meant to identify the points of intersection between humans and mission considerations such as architecture, vehicle design, technologies, operations, and science requirements. We seek to provide clear, top-level guidelines for human-related exploration studies and technology research that address common questions and requirements. As a result, we hope that ongoing mission trade studies consider common, standard, and practical criteria for human interfaces.
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Distributed Spacecraft Mission (DSM) Plume Design Reference Mission (DRM) Inter-Satellite Link Modeling, Analysis and Simulation
NASA Goddard Space Flight Center (GSFC) Radical Innovation Initiative (RI2) plans to focus intently on DSM capability advancements in FY22-24. A DSM mission involves multiple spacecraft, arranged in a constellation, to achieve one or more common goals via the use of inter-satellite links (ISL) between the satellites. Recently, the GSFC Internal Research & Development (IRAD) program established Enceladus as a design reference mission (DRM) for the current DSM effort to foster the conceptual development of communication architecture, requirements, and solutions for future DSM ISL, as well as being able to push other research areas of interest. Enceladus is an icy moon of the planet Saturn. The DRM Enceladus mission concept involves a constellation of 24 small satellites, orbiting Enceladus around 100 km altitude in 3 planes, as observing nodes for science measurement. The mission science data will be sent back to Earth through a relay orbiting Saturn, using the constellation’s inter-satellite links. A QualNet/STK simulation model of the Relay and constellation ISL optical and RF links is developed for the design and optimization of the link and orbital parameters, as well as the inter-networking protocols. Delay Tolerant Networking (DTN) is utilized in the application layer modeling. This paper describes the plume DRM mission concept of an Enceladus constellation to relay science data to Earth and includes the proposed communication architecture and operation concepts. We present details of the QualNet/STK engineering model for this communication scenario to simulate the end-to-end data traffic through multiple layers (physical, data link, networking, transport and application). A link analysis for the constellation’s ISL, constellation to Relay and Direct to Earth (DTE) optical link is provided and discussed. The results of end-to-end traffic simulation for the data throughout/latency evaluation and assessment of the communication architecture are presented. The investigation of the concept of optical multiple access (OMA) for the Plume DRM is discussed. The modeling and simulation methodology developed in this paper is applicable to other DSMs in near Earth and deep space such as Earth-Moon L1/L2 and Lunar regions.
Distributed Spacecraft Mission (DSM) Inter-satelli↗
Mission Concept Design for Autonomous Space Missions using Mission-Level Modeling and Simulation
NASA’s Europa Lander mission is to search for biosignatures on Europa based on in-situ science using a lander architecture. This mission presents a set of challenges that requires a high level of autonomy on the lander system, leading to the need for a new operational paradigm that supports better collaboration and coordination between the lander and the ground operations team. M\&S is used for both designing the onboard system-level autonomy and the ground operations paradigm that allows effective and efficient collaboration and coordination between the lander and the ground operations team. In this paper, M\&S as applied to the design of new mission and operational concepts will be discussed. At its current early stage of the mission development for Europa Lander, the M\&S is used to explore different mission concepts and gain insights for design (formative) rather than to verify and validate fully designed mission concepts quantitatively (summative). Organically, we established a new approach to mission and operational concept exploration using high-fidelity modeling and simulation. M\&S has been an integral part of the approach of defining constraints and assertions, designing mission concepts, assessing (i.e., simulating them), and discovering insights, which feeds back to the definition an design steps. This organically-established approach provided important benefits to the project at its early phase of the development by enabling the project team to be able to build shared understanding of impacts from design characteristics, constraints, and their interactions on the mission performance.
Ye, Sean↗
Exploration-Related Research on the International Space Station: Connecting Science Results to the Design of Future Missions
In January, 2004, the US President announced a vision for space exploration, and charged NASA with utilizing the International Space Station (ISS) for research and technology targeted at supporting the US space exploration goals. This paper describes: 1) what we have learned from the first four years of research on ISS relative to the exploration mission, 2) the on-going research being conducted in this regard, 3) our current understanding of the major exploration mission risks that the ISS can be used to address, and 4) current progress in realigning NASA s research portfolio for ISS to support exploration missions. Specifically, we discuss the focus of research on solving the perplexing problems of maintaining human health on long-duration missions, and the development of countermeasures to protect humans from the space environment, enabling long duration exploration missions. The interchange between mission design and research needs is dynamic, where design decisions influence the type of research needed, and results of research influence design decisions. The fundamental challenge to science on ISS is completing experiments that answer key questions in time to shape design decisions for future exploration. In this context, exploration-relevant research must do more than be conceptually connected to design decisions-it must become a part of the mission design process.
Rhatigan, Jennifer L.↗
Design Reference Missions (DRM): Integrated ODM 'Air-Taxi' Mission Features
Design Reference Missions (DRM): Integrated ODM Air-Taxi Mission Features, Hybrid Electric Integrated System Testbed (HEIST) flight control. Structural Health, Energy Storage, Electric Components, Loss of Control, Degraded Systems, System Health, Real-Time IO Operator Geo-Fencing, Regional Noise Abatement and Trusted Autonomy Inter-operability.
Kloesel, Kurt↗
Trajectory Design Considerations for Exploration Mission 1
Exploration Mission 1 (EM-1) will be the first mission to send an uncrewed Orion Multi-Purpose Crew Vehicle (MPCV) to cislunar space in the fall of 2019. EM-1 was originally conceived as a lunar free-return mission, but was later changed to a Distant Retrograde Orbit (DRO) mission as a precursor to the Asteroid Redirect Mission. To understand the required mission performance (i.e., propellant requirement), a series of trajectory optimization runs was conducted using JSC's Copernicus spacecraft trajectory optimization tool. In order for the runs to be done in a timely manner, it was necessary to employ a parallelization approach on a computing cluster using a new trajectory scan tool written in Python. Details of the scan tool are provided and how it is used to perform the scans and post-process the results. Initially, a scan of daily due east launched EM-1 DRO missions in 2018 was made. Valid mission opportunities are ones that do not exceed the useable propellant available to perform the required burns. The initial scan data showed the propellant and delta-V performance patterns for each launch period. As questions were raised from different subsystems (e.g., power, thermal, communications, flight operations, etc.), the mission parameters or data that were of interest to them were added to the scan output data file. The additional data includes: (1) local launch and landing times in relation to sunrise and sunset, (2) length of eclipse periods during the in-space portion of the mission, (3) Earth line of sight from cislunar space, (4) Deep Space Network field of view looking towards cislunar space, and (5) variation of the downrange distance from Earth entry interface to splashdown. Mission design trades can also be performed based on the information that the additional data shows. For example, if the landing is in darkness, but the recovery operations team desires a landing in daylight, then an analysis is performed to determine how to change the mission design to meet this request. Also, subsystems request feasibility of alternate or contingency mission designs, such as adding an Orion main engine checkout burn or Orion completing all of its burns using only its auxiliary thrusters. This paper examines and presents the evolving trade studies that incorporate subsystem feedback and demonstrate the feasibility of these constrained mission trajectory designs and contingencies.
Dawn, Timothy F.↗
DUKSUP - A high thrust trajectory optimization code
Designing missions on expendable launch vehicles (ELV's) includes determining launch vehicle performance capabilities and trajectory characteristics over the range of mission requirements for suitable launch periods. This analysis depends on mathematically modeling both the launch vehicle and the mission requirements. Generally the result is a mathematical model that is described by an objective function to be optimized subject to an assortment of algebraic and dynamic constraints. About 30 years ago, engineers at Lewis Research Center (LeRC) undertook the task of creating a software code to solve 3D versions of such problems and based it on the Calculus of Variations/Optimal Control Theory. One of these codes, DUKSUP, has been in use at LeRC for nearly 25 years, during which time it has played an important role in a large number of studies and actual missions. Currently it is being used by about 12 analysts in the Center's Advanced Space Analysis Office (ASAO) to do mission design, feasibility studies, corroboration of contractor data and planning studies for the Space Exploration Initiative (SEI). Today, it is one of the few ELV mission analysis production codes based on variational methods. With future ELV missions in mind, ASAO is presently creating a new code to upgrade DUKSUP's capabilities.
Balkanyi, Leslie R.↗
Safety Goals at NASA: How Safe is Safe Enough and How to Get There
NASA is developing and implementing safety improvements in all its activities including mission design, mission operations, and occupational safety. Decisions regarding where and how improvements are implemented to optimally enhance safety are discussed.
Stamatelatos, Michael↗
NASA Readies Two Ranger Spacecraft for Moon Missions
Design and mission analysis of Ranger C and D lunar probes
MISSION PLANNING↗
Relevant Parameter Evolution in Team X Mission Concept Designs
The Advanced Projects Design Team, also known as Team X, is a concurrent engineering team that quickly and cheaply designs space mission architectures including the flight system and subsystems, the trajectory, and ground system. Through the use of ICEMaker, an Excel spreadsheet database, the parameters from each subsystem can be shared and used among the other subsystems. This allows for entire missions to be planned with only a few short design team sessions. Based on the results, the feasibility of the mission concept can be determined. Over the Years since the team was created, the amount of information being shared among subsystems on the database has increased, however many of the parameters are now obsolete. Removal of these unused parameters Will clean UP the database and help to streamline the mission design process. By comparing parameter files from previous Team X mission studies, the parameter usage can be determined. As was initially suspected there are more unused parameters on the database than parameters that are actually used.
Huelman, Brandon N.↗
Cloud Computing Methods for Near Rectilinear Halo Orbit Trajectory Design
Complicated mission design problems require innovative computational solutions. As spacecraft depart from a proposed Gateway in a Near Rectilinear Halo Orbit (NRHO), recontact analysis is required to avoid risk of collision and ensure safe operations. Escape dynamics from NRHOs are governed by multiple gravitational bodies, yielding a trajectory design space that is exhaustively large. This paper summarizes the recontact analysis for departure from the NRHO and describes how the Deep Space Trajectory Explorer (DSTE) trajectory design software incorporates high performance cloud computing to compute and visualize the orbit design space. Recent focus on exploration missions to cislunar space has kindled accelerated interest in multibody orbit solutions. Trajectory analysis in the presence of multiple gravity fields is complex, and innovative computational tools are needed to simplify complicated design spaces, to generate large quantities of data quickly, and to visualize the output for user accessibility. The Gateway mission is a prime example. The Gateway1 is proposed as a human outpost in deep space. The current baseline orbit for the Gateway is a Near Rectilinear Halo Orbit (NRHO) near the Moon.2 The NRHO exists in a regime that experiences the gravitational effects of the Earth and the Moon simultaneously, complicating orbit analysis. The mission design process benefits greatly from updated computational tools for multibody missions like the Gateway. As an example, consider the problem of assessing the risk of collision in an NRHO. As a staging location to missions to the lunar surface and beyond the Earth-Moon system, the Gateway will experience spacecraft and other objects regularly arriving and departing. Departing objects potentially include spent logistics modules, visiting crew vehicles, debris objects, wastewater particles, and cubesats. Each departure is governed by the dynamics of the Gateway orbit and the surrounding dynamical environment. Over time, any unmaintained object in such an orbit eventually departs due to the small instabilities associated with the NRHOs. A separation maneuver speeds the departure from the NRHO, but the effects of the maneuver on the spacecraft behavior depend on the location, magnitude, and direction of the burn. Escape dynamics from the NRHO with regard to these maneuver options open up an enormous potential trajectory design space where subtle changes in input can produce dramatically large changes in the results. Any departing object must avoid recontacting the Gateway as it leaves the lunar vicinity, and a recontact analysis thus involves a significant number of computations and extensive output data. To explore the dynamics of this extensive design space, the Deep Space Trajectory Explorer3 (DSTE) trajectory design software incorporates new High Performance Computing (HPC) services and novel interactive visualizations. This paper details the HPC and cloud infrastructure techniques that are implemented in the DSTE, applying the new capabilities to analysis of recontact risk with the Gateway in NRHO. NEAR RECTILINEAR HALO ORBITS The Gateway is planned to fly in a lunar NRHO as its baseline orbit. The NRHO families of orbits are subsets of the larger halo families, which originate from planar orbits near the L1 and L2 libration points; the Earth-Moon L2 halo family appears in Figure 1. Each halo orbit is perfectly periodic in the Circular Restricted 3-Body Problem (CR3BP) and becomes a quasi-periodic orbit in a higher fidelity ephemeris force model. The NRHOs are defined as those members of the halo family with bounded stability properties;2 they pass near the Moon at perilune and are nearly polar. Families exist with apolunes located both above the lunar north pole and above the lunar south pole; the Gateway is planned to reside in a southern L2 NRHO in a 9:2 resonance with the lunar synodic period. The 9:2 NRHO is characterized by a period of about 6.5 days, a perilune radius of about 3,500 km, and an apolune radius of about 71,000 km; it is strongly affected by the gravity of both the Earth and the Moon simultaneously. This NRHO offers extended communications with assets on the south pole of the Moon,4 as well as low-cost orbit maintenance and attitude control,5 favorable eclipse avoidance properties,6 and inexpensive transfers from Earth and to other destinations.5,7 The NRHO portion of the southern L2 halo family is highlighted in black in Figure 1, and the 9:2 NRHO appears in blue.
Phillips, Sean M.↗
A Probabilistic Approach of Incorporating Safety and Reliability in System Designs for a Manned Mission to Mars
Conceptual stages in mission design often lack the input of quantitative safety and reliability assessments, simply because failure rates or other data are not yet available for systems that have not yet been designed. Absence of such data should not, however, prevent the development of a quantitative risk models with placeholders for missing data. Functions (that is, actions the systems must perform) in mission design will eventually require system probabilities of success, and there could be much learned from surrogate data, adequately bounded in uncertainty, used in a large event tree model of a complex mission.
Railsback, Jan W.↗