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NASA NTRS2014

Launch Vehicle Production and Operations Cost Metrics

Traditionally, launch vehicle cost has been evaluated based on $/Kg to orbit. This metric is calculated based on assumptions not typically met by a specific mission. These assumptions include the specified orbit whether Low Earth Orbit (LEO), Geostationary Earth Orbit (GEO), or both. The metric also assumes the payload utilizes the full lift mass of the launch vehicle, which is rarely true even with secondary payloads.1,2,3 Other approaches for cost metrics have been evaluated including unit cost of the launch vehicle and an approach to consider the full program production and operations costs.4 Unit cost considers the variable cost of the vehicle and the definition of variable costs are discussed. The full program production and operation costs include both the variable costs and the manufacturing base. This metric also distinguishes operations costs from production costs, including pre-flight operational testing. Operations costs also consider the costs of flight operations, including control center operation and maintenance. Each of these 3 cost metrics show different sensitivities to various aspects of launch vehicle cost drivers. The comparison of these metrics provides the strengths and weaknesses of each yielding an assessment useful for cost metric selection for launch vehicle programs.

Watson, Michael D.↗

NASA NTRS2014

Multi Purpose Crew Vehicle Active Thermal Control and Environmental Control and Life Support Development Status

The Orion Multi Purpose Crew Vehicle (MPCV) is the first crew transport vehicle to be developed by the National Aeronautics and Space Administration (NASA) in the last thirty years. Orion is currently being developed to transport the crew safely beyond Earth orbit. This year, the vehicle focused on building the Exploration Flight Test 1 (EFT1) vehicle to be launched in September of 2014. The development of the Orion Active Thermal Control (ATCS) and Environmental Control and Life Support (ECLS) System, focused on the integrating the components into the EFT1 vehicle and preparing them for launch. Work also has started on preliminary design reviews for the manned vehicle. Additional development work is underway to keep the remaining component progressing towards implementation on the flight tests of EM1 in 2017 and of EM2 in 2020. This paper covers the Orion ECLS development from April 2013 to April 2014

Lewis, John F.↗

NASA NTRS2015

A Vehicle Management End-to-End Testing and Analysis Platform for Validation of Mission and Fault Management Algorithms to Reduce Risk for NASA's Space Launch System

The development of the Space Launch System (SLS) launch vehicle requires cross discipline teams with extensive knowledge of launch vehicle subsystems, information theory, and autonomous algorithms dealing with all operations from pre-launch through on orbit operations. The characteristics of these systems must be matched with the autonomous algorithm monitoring and mitigation capabilities for accurate control and response to abnormal conditions throughout all vehicle mission flight phases, including precipitating safing actions and crew aborts. This presents a large complex systems engineering challenge being addressed in part by focusing on the specific subsystems handling of off-nominal mission and fault tolerance. Using traditional model based system and software engineering design principles from the Unified Modeling Language (UML), the Mission and Fault Management (M&FM) algorithms are crafted and vetted in specialized Integrated Development Teams composed of multiple development disciplines. NASA also has formed an M&FM team for addressing fault management early in the development lifecycle. This team has developed a dedicated Vehicle Management End-to-End Testbed (VMET) that integrates specific M&FM algorithms, specialized nominal and off-nominal test cases, and vendor-supplied physics-based launch vehicle subsystem models. The flexibility of VMET enables thorough testing of the M&FM algorithms by providing configurable suites of both nominal and off-nominal test cases to validate the algorithms utilizing actual subsystem models. The intent is to validate the algorithms and substantiate them with performance baselines for each of the vehicle subsystems in an independent platform exterior to flight software test processes. In any software development process there is inherent risk in the interpretation and implementation of concepts into software through requirements and test processes. Risk reduction is addressed by working with other organizations such as S&MA, Structures and Environments, GNC, Orion, the Crew Office, Flight Operations, and Ground Operations by assessing performance of the M&FM algorithms in terms of their ability to reduce Loss of Mission and Loss of Crew probabilities. In addition, through state machine and diagnostic modeling, analysis efforts investigate a broader suite of failure effects and detection and responses that can be tested in VMET and confirm that responses do not create additional risks or cause undesired states through interactive dynamic effects with other algorithms and systems. VMET further contributes to risk reduction by prototyping and exercising the M&FM algorithms early in their implementation and without any inherent hindrances such as meeting FSW processor scheduling constraints due to their target platform - ARINC 653 partitioned OS, resource limitations, and other factors related to integration with other subsystems not directly involved with M&FM. The plan for VMET encompasses testing the original M&FM algorithms coded in the same C++ language and state machine architectural concepts as that used by Flight Software. This enables the development of performance standards and test cases to characterize the M&FM algorithms and sets a benchmark from which to measure the effectiveness of M&FM algorithms performance in the FSW development and test processes. This paper is outlined in a systematic fashion analogous to a lifecycle process flow for engineering development of algorithms into software and testing. Section I describes the NASA SLS M&FM context, presenting the current infrastructure, leading principles, methods, and participants. Section II defines the testing philosophy of the M&FM algorithms as related to VMET followed by section III, which presents the modeling methods of the algorithms to be tested and validated in VMET. Its details are then further presented in section IV followed by Section V presenting integration, test status, and state analysis. Finally, section VI addresses the summary and forward directions followed by the appendices presenting relevant information on terminology and documentation.

Trevino, Luis↗

NASA NTRS2014

Crewed Space Vehicle Battery Safety Requirements

This requirements document is applicable to all batteries on crewed spacecraft, including vehicle, payload, and crew equipment batteries. It defines the specific provisions required to design a battery that is safe for ground personnel and crew members to handle and/or operate during all applicable phases of crewed missions, safe for use in the enclosed environment of a crewed space vehicle, and safe for use in launch vehicles, as well as in unpressurized spaces adjacent to the habitable portion of a space vehicle. The required provisions encompass hazard controls, design evaluation, and verification. The extent of the hazard controls and verification required depends on the applicability and credibility of the hazard to the specific battery design and applicable missions under review. Evaluation of the design and verification program results shall be completed prior to certification for flight and ground operations. This requirements document is geared toward the designers of battery systems to be used in crewed vehicles, crew equipment, crew suits, or batteries to be used in crewed vehicle systems and payloads (or experiments). This requirements document also applies to ground handling and testing of flight batteries. Specific design and verification requirements for a battery are dependent upon the battery chemistry, capacity, complexity, charging, environment, and application. The variety of battery chemistries available, combined with the variety of battery-powered applications, results in each battery application having specific, unique requirements pertinent to the specific battery application. However, there are basic requirements for all battery designs and applications, which are listed in section 4. Section 5 includes a description of hazards and controls and also includes requirements.

Jeevarajan, Judith A.↗

NASA NTRS2016

Characterizing Epistemic Uncertainty for Launch Vehicle Designs

NASA Probabilistic Risk Assessment (PRA) has the task of estimating the aleatory (randomness) and epistemic (lack of knowledge) uncertainty of launch vehicle loss of mission and crew risk, and communicating the results. Launch vehicles are complex engineered systems designed with sophisticated subsystems that are built to work together to accomplish mission success. Some of these systems or subsystems are in the form of heritage equipment, while some have never been previously launched. For these cases, characterizing the epistemic uncertainty is of foremost importance, and it is anticipated that the epistemic uncertainty of a modified launch vehicle design versus a design of well understood heritage equipment would be greater. For reasons that will be discussed, standard uncertainty propagation methods using Monte Carlo simulation produce counter intuitive results, and significantly underestimate epistemic uncertainty for launch vehicle models. Furthermore, standard PRA methods, such as Uncertainty-Importance analyses used to identify components that are significant contributors to uncertainty, are rendered obsolete, since sensitivity to uncertainty changes are not reflected in propagation of uncertainty using Monte Carlo methods. This paper provides a basis of the uncertainty underestimation for complex systems and especially, due to nuances of launch vehicle logic, for launch vehicles. It then suggests several alternative methods for estimating uncertainty and provides examples of estimation results. Lastly, the paper describes how to implement an Uncertainty-Importance analysis using one alternative approach, describes the results, and suggests ways to reduce epistemic uncertainty by focusing on additional data or testing of selected components.

Novack, Steven D.↗

NASA NTRS2016

Characterizing Epistemic Uncertainty for Launch Vehicle Designs

NASA Probabilistic Risk Assessment (PRA) has the task of estimating the aleatory (randomness) and epistemic (lack of knowledge) uncertainty of launch vehicle loss of mission and crew risk and communicating the results. Launch vehicles are complex engineered systems designed with sophisticated subsystems that are built to work together to accomplish mission success. Some of these systems or subsystems are in the form of heritage equipment, while some have never been previously launched. For these cases, characterizing the epistemic uncertainty is of foremost importance, and it is anticipated that the epistemic uncertainty of a modified launch vehicle design versus a design of well understood heritage equipment would be greater. For reasons that will be discussed, standard uncertainty propagation methods using Monte Carlo simulation produce counter intuitive results and significantly underestimate epistemic uncertainty for launch vehicle models. Furthermore, standard PRA methods such as Uncertainty-Importance analyses used to identify components that are significant contributors to uncertainty are rendered obsolete since sensitivity to uncertainty changes are not reflected in propagation of uncertainty using Monte Carlo methods.This paper provides a basis of the uncertainty underestimation for complex systems and especially, due to nuances of launch vehicle logic, for launch vehicles. It then suggests several alternative methods for estimating uncertainty and provides examples of estimation results. Lastly, the paper shows how to implement an Uncertainty-Importance analysis using one alternative approach, describes the results, and suggests ways to reduce epistemic uncertainty by focusing on additional data or testing of selected components.

Novack, Steven D.↗

NASA NTRS2016

Modeling, Simulation, and Control of a Solar Electric Propulsion Vehicle in Near-Earth Vicinity Including Solar Array Degradation

Modeling and control software that integrates the complexities of solar array models, a space environment, and an electric propulsion system into a rigid body vehicle simulation and control model is provided. A rigid body vehicle simulation of a solar electric propulsion (SEP) vehicle may be created using at least one solar array model, at least one model of a space environment, and at least one model of a SEP propulsion system. Power availability and thrust profiles may be determined based on the rigid body vehicle simulation as the SEP vehicle transitions from a low Earth orbit (LEO) to a higher orbit or trajectory. The power availability and thrust profiles may be displayed such that a user can use the displayed power availability and thrust profiles to determine design parameters for an SEP vehicle mission.

Witzberger, Kevin↗

NASA NTRS2016

Launch Vehicle Selection and the Implementation of the Soil Moisture Active Passive Mission

Soil Moisture Active Passive (SMAP) is a NASA-developed Earth science satellite currently mapping the soil moisture content and freeze/thaw state of Earth's land mass from a 685km, near-polar, sun-synchronous orbit. It was launched on January 31, 2015 from Vandenberg AFB upon a Delta II 7320 launch vehicle. Due to external considerations, SMAP's launch vehicle selection remained an open item until Project Critical Design Review (CDR). Thus, certain key aspects of the spacecraft design had to accommodate a diverse range of candidate launch vehicle environments, performance envelopes, interfaces and operational scenarios. Engineering challenges stemmed from two distinct scenarios: decisions that had to be made prior to launch vehicle selection to accommodate all possible outcomes, and post-selection changes constrained by schedule and the existing spacecraft configuration. The effects of the timing of launch vehicle selection reached virtually every aspect of the Observatory's design and development. Physical environments, mass allocations, material selections, propulsion system performance, dynamic response, launch phase and mission planning, overall size and configuration, and of course all interfaces to the launch vehicle were heavily dependent on this outcome. This paper will discuss the resolution of these technical challenges.

Sherman, Sarah↗

NASA NTRS2017

Vented Launch Vehicle Adaptor for a Manned Spacecraft with "Pusher" Launch Abort System

A system, method, and apparatus for a vented launch vehicle adaptor (LVA) for a manned spacecraft with a "pusher" launch abort system are disclosed. The disclosed LVA provides a structural interface between a commercial crew vehicle (CCV) crew module/service module (CM/SM) spacecraft and an expendable launch vehicle. The LVA provides structural attachment of the module to the launch vehicle. It also provides a means to control the exhaust plume from a pusher-type launch abort system that is integrated into the module. In case of an on-pad or ascent abort, which requires the module to jettison away from the launch vehicle, the launch abort system exhaust plume must be safely directed away from critical and dangerous portions of the launch vehicle in order to achieve a safe and successful jettison.

Vandervort, Robert E.↗

NASA NTRS2017

Application of GPS to Enable Launch Vehicle Upper Stage Heliocentric Disposal

To properly dispose of the upper stage of the Space Launch System, the vehicle must perform a burn in Earth orbit to perform a close flyby of the Lunar surface to gain adequate energy to enter into heliocentric space. This architecture was selected to meet NASA requirements to limit orbital debris in the Earth-Moon system. The choice of a flyby for heliocentric disposal was driven by mission and vehicle constraints. This paper describes the SLS mission for Exploration Mission -1, a high level overview of the Block 1 vehicle, and the various disposal options considered. The research focuses on this analysis in terms of the mission design and navigation problem, focusing on the vehicle-level requirements that enable a successful mission. An inertial-only system is shown to be insufficient for heliocentric flyby due to large inertial integration errors from launch through disposal maneuver while on a trans-lunar trajectory. The various options for aiding the navigation system are presented and details are provided on the use of GPS to bound the state errors in orbit to improve the capability for stage disposal. The state estimation algorithm used is described as well as its capability in determination of the vehicle state at the start of the planned maneuver. This data, both dispersions on state and on errors, is then used to develop orbital targets to use for meeting the required Lunar flyby for entering onto a heliocentric trajectory. The effect of guidance and navigation errors on this capability is described as well as the identified constraints for achieving the disposal requirements. Additionally, discussion is provided on continued analysis and identification of system considerations that can drive the ability to integrate onto a vehicle intended for deep space.

Anzalone, Evan J.↗

NASA NTRS2018

Air Launched Vehicle Exergy Analysis During Aircraft Boost Phase

The analysis of air launched vehicles carrying payloads to low earth orbit is complex. The integration of the aircraft flight phase and the launch vehicle flight phase requires the integration of systems functioning from different energy relationships. System exergy balance provides a relationship to integrate the efficiency of the aircraft launcher and the efficiency of the launch vehicle in a single, integrated system assessment. The exergy balance of the aircraft flight phase can be calculated with the launch vehicle included as part of the vehicle mass. As exergy balance allows for separate of the masses, different velocities, and different propulsion systems to continue the mission analysis after separation through payload orbital insertion and aircraft landing. This paper presents the initial assessment of the aircraft launch phase up to separation of the launch vehicle. Showing the method of integration afforded by the system exergy balance relationship.

Lane, Joshua↗

NASA NTRS2018

An Examination of Launch Vehicle Loads Reanalysis Techniques

The typical approach to calculating dynamic launch loads in aerospace applications is coupled loads analysis (CLA). A component mode model of the launch vehicle is coupled with a component mode model of a payload, system modes are calculated, forcing functions are applied, and the dynamic responses are computed. This approach requires the explicit knowledge of the component models for the launch vehicle and payload, as well as the forcing functions. In many situations, the launch vehicle and forcing functions do not change from one analysis to the next only the payload is different. For this type of application, a method called reanalysis was developed to compute the response of a modified payload on the same launch vehicle. If the launch forcing functions are also the same, the approach eliminates the need for the launch vehicle model and the forcing functions and dramatically reduces the computation time. This work investigates the application and accuracy of three previously developed reanalysis methods using a typical launch vehicle and two different payloads. All three methods are based on knowledge of system modes from the original CLA, and Hurty/Craig-Bampton (HCB) models of the original and new payloads. The first method was developed at JPL (Jet Propulsion Lab) and is often referred to as substitution. It is a frequency-domain method, which requires transformation of time signals to and from the frequency domain. The other two methods are time-domain methods that more closely mimic the CLA process. The three methods were applied to two simple examples and a more complex one. The results indicate that the time-domain methods are considerably more robust with respect to modal truncation and other numerical errors than the frequency-domain JPL method.

Reanalysis↗

NASA NTRS2016

Feasibility of Varying Geo-Fence Around an Unmanned Aircraft Operation Based on Vehicle Performance and Wind

Managing trajectory separation is critical to ensuring accessibility, efficiency, and safety in the unmanned airspace. The notion of geo-fences is an emerging concept, where distance buffers enclose individual trajectories and areas of operation in order to manage the airspace. Currently, the Air Traffic Management system for commercial travel defines static distance buffers around the aircraft; however, commercial UASs are envisioned to operate in significantly closer proximity to other UAS requiring a geo-fence for spacing operations. The geo-fence size can be determined based on vehicle performance characteristics, state of the airspace, weather, and other unforeseen events such as emergency or disaster response. Calculation of the geo-fence size could be determined as part of pre-flight planning and during real-time operations. A largely non-homogeneous fleet of UASs will be operating in low altitude and will likely be commercially developed. Due to intellectual property concerns, the operators may not provide detailed specifications of the control system to UTM. In addition, the huge variety of UAS makes modeling each control system prohibitive and flight data for these vehicles may not exist. Therefore, a generalized, simple geo-fence sizing algorithm must be developed such that it does not rely on detailed knowledge of the vehicle control system, accounts for the presence of urban winds, and is sufficiently accurate. In this work, two simple models are investigated to determine its feasibility as an adequate means for calculating the geo-fence size. The vehicle data used in this work are provided by UAS manufactures who have partnered with NASA's UTM project and some publicly available websites. The first model utilizes wind data processed from the NOAA HRRR (Hourly Rapid Refresh) product and Sonar Annemometer data provided by San Jose State. The second model utilizes OpenFOAM which is a CFD code used to generate a wind field for flow around a single building. The key vehicle performance parameters can include UAS response time to disturbances, command to actuation latency, control system rate limits, time to recovery to desired path, and aerodynamics. It was found that the first model provides an initial understanding of geo-fence sizing, but does not provide enough accuracy to provide UTM with an efficient means of scheduling vehicles. The results of the second model reveal that modeling UAS controls systems with a linearized plant and gain scheduled PID controller does not allow capture the UAS flight dynamics within a significant envelope of the wind disturbances.

uncertainty↗

NASA NTRS2019

Update to Mars Ascent Vehicle Design for Human Exploration

Astronauts on a mission to Mars will require several vehicles working together to get to Mars orbit, descend to the surface of Mars, support them while they’re there, and return them to Earth. The Mars Ascent Vehicle (MAV) transports the crew off the surface of Mars to a waiting Earth return vehicle in Mars orbit and is a particularly influential part of the mission architecture because it sets performance requirements for the lander and in-space transportation vehicles. With this in mind, efforts have been made to minimize the MAV mass, and its impact on the other vehicles. A minimal mass MAV design using methane and in situ generated oxygen propellants was presented in 2015. Since that time, refinements have been made in most subsystems to incorporate findings from ongoing research into key technologies, improved understanding of environments and further analysis of design options. This paper presents an overview of the current MAV reference design used in NASA’s human Mars mission studies, and includes a description of the operations, configuration, subsystem design, and a vehicle mass summary.

propulsion↗

NASA NTRS2019

Small Launch Vehicle Sizing Analysis with Solid Rocket Examples

Small launch vehicles are governed by the same physics as large launch vehicles of course, but due to their small size, some aspects and sensitivities become more important and others less. This paper shows semi-empirical correlations to quantify dry mass fraction for both stage and whole vehicle optimization: mass fraction due to density, mass fraction due to thrust-to-weight, and mass fraction due to size reduction. For single-stage optimizations, a stage performance requirement can be met by a locus of mass fraction vs. specific impulse. Based on the above correlations, this alone can recommend a solid or liquid rocket for a stage. Rocket designs of similar technology levels are compared, focusing on where stages become less mass-efficient as they get smaller. The Mars Ascent Vehicle is shown to exemplify a trade between a two-stage solids vehicle and a one- or two-stage liquids vehicle.

Kibbey, Tim↗

NASA NTRS2019

Small Launch Vehicle Sizing Analysis With Solid Rocket Examples

Kibbey, Tim↗

NASA NTRS2020

Mid Lift-to-Drag Ratio Rigid Vehicle 6-DoF Performance for Human Mars Entry, Descent, and Landing: A Fractional Polynomial Powered Descent Guidance Approach

Defining a feasible vehicle design and mission architecture capable of reliably delivering apayload of 20 metric tons (mt) or more is a great challenge for landing humans on Mars. TheMid Lift-to-Drag Rigid Vehicle (MRV), a rigid decelerator studied in NASA’s Entry, Descent,and Landing Architecture Study (EDLAS), has shown to be a viable vehicle candidate forfuture human Mars missions. As the vehicle concept matures, models of increasing fidelity areadded to the six-degree-of-freedom (6DoF) EDL simulation. This paper presents 6DoFsimulation results using model updates for vehicle mass properties, fineness ratio, andaerodynamic-propulsive interactions. Additionally, an assessment of the Fractional-Polynomial Powered Descent Guidance (FP2DG) performance is presented, and the vehicleperformance is compared with the Tunable Apollo Powered Descent Guidance (TAPDG).Finally, Monte Carlo results of the vehicle design trades are presented.

Johnson, Breanna J.↗

NASA NTRS2020

Pterodactyl: Development and Comparison of Control Architectures for a Mechanically Deployed Entry Vehicle

The Pterodactyl project, seeks to advance the current state-of-the-art for entry vehicles by developing novel guidance and control technologies for Deployable Entry Vehicles (DEVs) that can be applied to various entry vehicle configurations. This paper details the efforts on the NASA-funded Pterodactyl project to investigate and implement multiple control techniques for an asymmetric mechanical DEV. We design multiple control architectures for a Pterodactyl Baseline Vehicle (PBV) and evaluate their performance in achieving varying guidance commands during entry. The control architectures studied are (i) propulsive control systems such as reaction control systems and (ii) non-propulsive control systems such as aerodynamic control surfaces and internal moving masses. For each system, state-feedback integral controllers based on linear quadratic regulator (LQR) optimal control methods are designed to track guidance commands of either (i) bank angle or (ii) angle of attack and sideslip angle as determined by the desired guidance trajectory. All control systems are compared for a lunar return reference mission and by providing a comparative analysis of these systems, configurations, and performance, the efforts detailed in this paper and the Pterodactyl project as a whole will help entry vehicle system designers determine suitable control architectures for integration with DEVs and other entry vehicle types.

Okolo, Wendy A.↗