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At least 55 records · Page 3

Resilience Enhancements through Deep Learning Yields

This report documents the Resilience Enhancements through Deep Learning Yields (REDLY) project, a three-year effort to improve electrical grid resilience by developing scalable methods for system operators to protect the grid against threats leading to interrupted service or physical damage. The computational complexity and uncertain nature of current real-world contingency analysis presents significant barriers to automated, real-time monitoring. While there has been a significant push to explore the use of accurate, high-performance machine learning (ML) model surrogates to address this gap, their reliability is unclear when deployed in high-consequence applications such as power grid systems. Contemporary optimization techniques used to validate surrogate performance can exploit ML model prediction errors, which necessitates the verification of worst-case performance for the models.

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Scalable Unit Commitment with Security Constrained AC Power Flow via ADMM and Hybrid Modeling Strategies

This research introduces a more efficient way to optimize power grid operations, breaking the problem into manageable steps and using advanced mathematical techniques to speed up calculations. By incorporating smart heuristics, improved preprocessing, and contingency analysis, the approach allows operators to make better decisions faster. These innovations enhance our understanding of how to optimize energy generation, making it possible to anticipate failures before they happen, reduce system costs, and improve overall grid performance. Ultimately, this research helps bridge the gap between theoretical models and real-world applications, paving the way for a smarter, more resilient power grid. This research directly benefits the public by making electricity more affordable, reliable, and sustainable. By improving how power grids schedule and distribute electricity, the project helps energy providers reduce operational costs, which can lead to lower electricity prices for consumers. Additionally, the ability to predict and prevent power system failures enhances grid reliability, reducing the likelihood of blackouts that can disrupt homes, businesses, and critical infrastructure such as hospitals. From an environmental perspective, optimizing power generation reduces energy waste and lowers carbon emissions, contributing to cleaner air and a more sustainable energy system. Furthermore, with extreme weather events becoming more frequent, these advancements make the power grid more resilient, ensuring communities are better prepared for emergencies and natural disasters. By strengthening the nation's energy infrastructure, this research plays a crucial role in improving economic stability, public safety, and environmental sustainability.

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Active rendezvous between a low-earth orbit user spacecraft and the Space Transportation System (STS) shuttle

Active rendezvous of an unmanned spacecraft with the Space Transportation System (STS) Shuttle is considered. The various operational constraints facing both the maneuvering spacecraft and the Shuttle during such a rendezvous sequence are discussed. Specifically, the actively rendezvousing user spacecraft must arrive in the generic Shuttle control box at a specified time after Shuttle launch. In so doing it must at no point violate Shuttle separation requirements. In addition, the spacecraft must be able to initiate the transfer sequence from any point in its orbit. The four-burn rendezvous sequence incorporating two Hohmann transfers and an intermediate phasing orbit as a low-energy solution satisfying the above requirements are discussed. The general characteristics of the four-burn sequence are discussed, with emphasis placed on phase orbit altitude and delta-velocity requirements. The planning and execution of such a sequence in the operational environment are then considered. Factor crucial in maintaining the safety of both spacecraft, such as spacecraft separation and contingency analysis, are considered in detail.

Hooper, H. L.↗

Testing of the on-board attitude determination and control algorithms for SAMPEX

Algorithms for on-board attitude determination and control of the Solar, Anomalous, and Magnetospheric Particle Explorer (SAMPEX) have been expanded to include a constant gain Kalman filter for the spacecraft angular momentum, pulse width modulation for the reaction wheel command, an algorithm to avoid pointing the Heavy Ion Large Telescope (HILT) instrument boresight along the spacecraft velocity vector, and the addition of digital sun sensor (DSS) failure detection logic. These improved algorithms were tested in a closed-loop environment for three orbit geometries, one with the sun perpendicular to the orbit plane, and two with the sun near the orbit plane - at Autumnal Equinox and at Winter Solstice. The closed-loop simulator was enhanced and used as a truth model for the control systems' performance evaluation and sensor/actuator contingency analysis. The simulations were performed on a VAX 8830 using a prototype version of the on-board software.

Mccullough, Jon D.↗

Operational Experience with Long Duration Wildfire Mapping: UAS Missions Over the Western United States

The National Aeronautics and Space Administration, United States Forest Service, and National Interagency Fire Center have developed a partnership to develop and demonstrate technology to improve airborne wildfire imaging and data dissemination. In the summer of 2007, a multi-spectral infrared scanner was integrated into NASA's Ikhana Unmanned Aircraft System (UAS) (a General Atomics Predator-B) and launched on four long duration wildfire mapping demonstration missions covering eight western states. Extensive safety analysis, contingency planning, and mission coordination were key to securing an FAA certificate of authorization (COA) to operate in the national airspace. Infrared images were autonomously geo-rectified, transmitted to the ground station by satellite communications, and networked to fire incident commanders within 15 minutes of acquisition. Close coordination with air traffic control ensured a safe operation, and allowed real-time redirection around inclement weather and other minor changes to the flight plan. All objectives of the mission demonstrations were achieved. In late October, wind-driven wildfires erupted in five southern California counties. State and national emergency operations agencies requested Ikhana to help assess and manage the wildfires. Four additional missions were launched over a 5-day period, with near realtime images delivered to multiple emergency operations centers and fire incident commands managing 10 fires.

Hall, Philip↗

Flight Dynamics Planning and Operations Support for the JWST Mission

The James Webb Space Telescope (JWST) was launched from Kourou Spaceport on December 25, 2021, at 12:20 UTC on an Ariane 5 launch vehicle. The launch vehicle inserted JWST into a 30-day transfer trajectory to the Sun-Earth-Moon (SEM) Lagrange point L2 region. JWST executed three mid-course correction maneuvers (MCCs) to insert the spacecraft into a quasi-halo orbit about SEM L2; JWST will maintain its trajectory about L2 for at least 5.5 years, with a goal of at least 10.5 years. This paper summarizes the flight dynamics support for JWST, including the prelaunch nominal trajectory design, the launch window analysis, contingency planning for trajectory-related anomalies, mission operations support for the first 6 months, and a comparison of the planned and achieved actual JWST trajectory results. The orbit determination strategy, both planned and executed, will be summarized, and the method of addressing the anomalies as they occurred will be included.

Space Operations↗

Flight Dynamics Planning and Operations Support for the JWST Mission

The James Webb Space Telescope (JWST) was launched from Kourou Spaceport on December 25, 2021, at 12:20 UTC on an Ariane 5 launch vehicle. The launch vehicle inserted JWST into a 30-day transfer trajectory to the Sun-Earth-Moon (SEM) Lagrange point L2 region. JWST executed three mid-course correction maneuvers (MCCs) to insert the spacecraft into a quasi-halo orbit about SEM L2; JWST will maintain its trajectory about L2 for at least 5.5 years, with a goal of at least 10.5 years. This paper summarizes the flight dynamics support for JWST, including the prelaunch nominal trajectory design, the launch window analysis, contingency planning for trajectory-related anomalies, mission operations support for the first 6 months, and a comparison of the planned and achieved actual JWST trajectory results. The orbit determination strategy, both planned and executed, will be summarized, and the method of addressing the anomalies as they occurred will be included.

Karen Richon↗

Cyber risk assessment and investment optimization using game theory and ML-based anomaly detection and mitigation for wide-area control in smart grids

The electric power grid is increasingly becoming susceptible to cyber attacks that exploit vulnerabilities in the smart grid control, information, and physical layers. Successful cyber attacks can have catastrophic impacts on the social and economic well-being of any nation all over the globe. It has, thus, become imperative to secure the smart grid against such adversarial actions to ensure stable, secure, and reliable operation of the grid. The existing research and industry practices prove to be inadequate in terms of providing pragmatic and effective defense methodologies and measures for long-term cybersecurity planning and real-time cybersecurity for grid operation. For example, existing works lack models that incorporate uncertain behavior of cyber-attackers and pragmatic defense measures for cyber risk assessment and cybersecurity investment optimization which often provide unreliable and strictly qualitative solutions to these problems. At the same time, with the growing number of cyber incidents in the grid, there still exists a need to develop attack-resilient algorithms for wide-area monitoring, protection, and control (WAMPAC) applications like the wide-area voltage control systems (WAVCS) for Flexible AC Transmissions Systems (FACTS) that lack in scalable and feasible solutions from the cybersecurity perspective. This dissertation proposes novel models and methodologies for: (1) Cybersecurity planning, and (2) Cybersecurity for system operation. The cybersecurity planning is achieved through cyber risk assessment and cybersecurity resource investment optimization for long-term cybersecurity of the grid using game theory and attack-defense trees. Cybersecurity for system operation consists of development of cyber anomaly detection and mitigation algorithms for flexible AC transmission system (FACTS) controller-based wide-area voltage control systems (WAVCS) using machine learning (ML), and software defined networking-based moving target defense network routing for achieving real-time cyber-physical security for grid operations. This is followed by hardware-in-the-loop (HIL) implementation and evaluation of these attack prevention, detection, and mitigation algorithms and methodologies showcasing their feasibility in a close to real-world environment. For cybersecurity planning, a novel approach involving a combination of game theory and attack defense trees (ADT) for optimal cybersecurity resource allocation in the smart grid is proposed. This methodology involves modeling of the cyber-physical smart grid substations as ADTs, defining attacker costs, defense costs, and attack probabilities for attack access points. Using game theoretical formulation, optimal defense strategies for the defender of the system to invest cybersecurity resources in the grid are obtained. Additionally, a game-theoretic framework is developed for quantitative cyber-physical risk assessment of the grid under a dynamically changing cyber threat space and uncertain behavior of cyber attackers which is further used to optimize investments in the smart grid's cybersecurity resources. The attacker, defender, and the smart grid system are modeled while incorporating attacker-stochasticity and federal guidelines for smart grid cybersecurity. This allows quantification of threat, vulnerabilities, and attack impact of the grid for quantitative risk assessment. The defender's budget to invest in the security resources in the grid is optimized based on the strategies leading to minimum system risk. The evaluation of the proposed solutions highlight the feasibility for practical implementation of these methodologies and algorithms in the smart grid, while taking the federal requirements and guidelines for smart grid security into consideration. For achieving cybersecurity for system operation, attack prevention, detection, and mitigation algorithms and methodologies are developed specifically for FACTS-based WAVCS. Anomaly detection and mitigation in the WAVCS are achieved using algorithms based on machine learning which involves offline training and testing of ML models with CPS datasets incorporating physics-based features that allow accurate distinction between system faults and cyber attacks. For attack prevention, a methodology based on software defined network (SDN)-based moving target defense (MTD) network routing is proposed that enables prevention of Denial of Service (DoS) type attacks on the smart grid communication system. Subsequently, these methodologies and algorithms are implemented and evaluated on an HIL testbed that allows for real-time attack prevention, detection, and mitigation of emulated cyber attacks on the WAVCS in a close to real-world environment. The results show highly accurate and efficient performance of the implemented algorithms and methodologies with the smart grid system operating within the NERC's system operation limits even in the presence of DoS and data integrity cyber attacks. This work opens up future research opportunities in other directions such as (1) Expanding cybersecurity planning methodologies to real-time cyber contingency analysis with different game formulations; and (2) Applying the cybersecurity for system operation algorithms to broader categories of wide-area control applications.

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PR100: Puerto Rico Grid Resilience and Transition to 100% Renewable Energy: Preventing and Responding to Extreme Events

This presentation discusses the aftermath of Hurricane Maria's landfall in Puerto Rico on September 20, 2017. Maria incapacitated Puerto Rico's power systems, leaving the entire island without electricity and access to fresh water. Some parts are still recovering years later. A resilient electric grid is vital to Puerto Rico's security, economy, and way of life.

demand impacts↗

Orbiter Repair Maneuver Contingency Separation Methods and Analysis

Repairing damaged thermal protection system tile requires the Space Shuttle to be oriented such that repair platform access from the International Space Station (ISS) is possible. To do this, the Space Shuttle uses the Orbiter Repair Maneuver (ORM), which utilizes the Shuttle Remote Manipulator System (SRMS) to rotate the Space Shuttle in relation to the ISS, for extended periods of time. These positions cause difficulties and challenges to performing a safe separation (no collision or thruster plume damage to sensitive ISS structures) should an inadvertent release occur or a contingency procedure require it. To help protect for an SRMS failure or other failures, a method for separating without collision and the ability to redock to ISS from the ORM configuration was needed. The contingency ORM separation solution elegantly takes advantage of orbital mechanics between ISS and the separating Space Shuttle. By pitching the ISS down approximately 45 degrees, in a majority of the ORM repair positions, the altitude difference between the ISS and Space Shuttle center of gravity is maximized. This altitude difference results in different orbital energies (orbital periods) causing objects to separate from each other without requiring translational firings. Using this method, a safe contingency ORM separation is made possible in many odd positions even though some separation positions point high powered thrusters directly at fragile ISS and Soyuz solar arrays. Documented in this paper are the development simulations and procedures of the contingency ORM separation and the challenges encountered with large constraints to work around. Lastly, a method of returning to redock with the ISS to pick up the stranded crew members (or transfer the final crew members) is explained as well as the thruster and ISS loads analysis.

Machula, Michael↗

Relaxing USOS Solar Array Constraints for Russian Vehicle Undocking

With the retirement of Space Shuttle cargo delivery capability and the ten year life extension of the International Space Station (ISS) more emphasis is being put on preservation of the service life of ISS critical components. Current restrictions on the United States Orbital Segment (USOS) Solar Array (SA) positioning during Russian Vehicle (RV) departure from ISS nadir and zenith ports cause SA to be positioned in the plume field of Service Module thrusters and lead to degradation of SAs as well as potential damage to Sun tracking Beta Gimbal Assemblies (BGA). These restrictions are imposed because of the single fault tolerant RV Motion Control System (MCS), which does not meet ISS Safety requirements for catastrophic hazards and dictates 16 degree Solar Array Rotary Joint position, which ensures that ISS and RV relative motion post separation, does lead to collision. The purpose of this paper is to describe a methodology and the analysis that was performed to determine relative motion trajectories of the ISS and separating RV for nominal and contingency cases. Analysis was performed in three phases that included ISS free drift prior to Visiting Vehicle separation, ISS and Visiting Vehicle relative motion analysis and clearance analysis. First, the ISS free drift analysis determined the worst case attitude and attitude rate excursions prior to RV separation based on a series of different configurations and mass properties. Next, the relative motion analysis calculated the separation trajectories while varying the initial conditions, such as docking mechanism performance, Visiting Vehicle MCS failure, departure port location, ISS attitude and attitude rates at the time of separation, etc. The analysis employed both orbital mechanics and rigid body rotation calculations while accounting for various atmospheric conditions and gravity gradient effects. The resulting relative motion trajectories were then used to determine the worst case separation envelopes during the clearance analysis. Analytical models were developed individually for each stage and the results were used to build initial conditions for the following stages. In addition to the analysis approach, this paper also discusses the analysis results, showing worst case relative motion envelopes, the recommendations for ISS appendage positioning and the suggested approach for future analyses.

Menkin, Evgeny↗

Information analysis of a spatial database for ecological land classification

An ecological land classification was developed for a complex region in southern California using geographic information system techniques of map overlay and contingency table analysis. Land classes were identified by mutual information analysis of vegetation pattern in relation to other mapped environmental variables. The analysis was weakened by map errors, especially errors in the digital elevation data. Nevertheless, the resulting land classification was ecologically reasonable and performed well when tested with higher quality data from the region.

Davis, Frank W.↗

The LSBmax algorithm for boosting resilience of electric grids post (N‐2) contingencies

Abstract A computationally improved algorithm is presented to find the best transmission switching (TS) candidate for boosting resilience of electricity grids subject to ( N ‐2) contingencies. Here, resilience is computed as the reduction in load shed after the above‐mentioned ( N‐ ) contingencies. TS is a planned line outage, and past research shows that changing the transmission system's topology changes the power flow and removes post contingency violations. Finding the best TS candidate in a computationally suitable time for effectively boosting resilience is a challenge. The best TS candidate is found using a novel heuristic method by decreasing the search space based on proximity to the bus with the maximum load shedding (LSB). The LSB algorithm is faster than existing algorithms in the literature; and, it is compatible with both the AC and DC optimal power flow formulations. To validate the authors' claims of speedup and accuracy, two metrics are used to analyze the results from the IEEE 39‐bus and 118‐bus systems. Finally, the inherent parallelism of the LSB algorithm is leveraged on a high‐performance computing platform and applied to the large‐scale Polish 2383‐bus test system to validate scalability in both size and speedup in computation time.

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Down-Selection of Four Common Habitat Variants

The Common Habitat is a large habitat developed as an alternative architecture study, not part of the current NASA baseline, that uses the SLS core stage liquid oxygen tank as its primary structure. It has a gravity-independent internal architecture, such that identical units can be used on the lunar surface, Mars surface, and in microgravity. In developing the habitat, two key architectural questions emerged. Should the internal layout use a vertical or horizontal orientation of the tank? Should the crew size be four or eight? This led to the design of four variants: a four-crew horizontal, four-crew vertical, eight-crew horizontal, and eight-crew vertical. The four-crew variants use a shortened version of the tank while the eight-crew variants use the entire tank. The primary consideration applied for down-selection is the crew experience living and working in the habitat, inclusive of crew productivity, well-being, and survivability. Based on this consideration, a series of seven assessments were performed to compare the variants. This analysis was performed as an unfunded, volunteer activity leveraging civil servants across multiple field centers, most with expertise working in various Artemis teams. Additionally, the evaluation was limited to the use of CAD models, images, and spreadsheet data, with no resources available for mockups or Virtual Reality. A logistics analysis developed a standard logistics module and then estimated how much stowage could be carried onboard each Common Habitat and how many logistics modules are required by each variant for a given mission duration. It also considered the amounts of water to be stored in each variant. A functional analysis identified and compared the living and working functions across the habitats, ranking them relative to each other. A crew time assessment first estimated the total crew time, building a weekly crew timeline for both four and eight-person crews. It then allocated time to activities linked to living and working functions, comparing how much time was available for each function in each variant. A science productivity assessment developed a relative metric using crew time, science stowage, and assumed rates of experiment consumables use to analytically compare the four variants. It also comparatively ranked the habitats with respect to a number of subjective parameters and a workstation acceptability rating. A maintenance capacity assessment identified and compared eleven generic maintenance capabilities across the variants and also ranked them for their predicted ability to complete twelve fabrication, maintenance, and repair scenarios. A contingency responsiveness analysis examined twelve serious in-flight contingencies. For each scenario, the number of crew needed to respond were predicted and acceptability of various aspects of contingency response were evaluated, comparing the variants against each other. Finally, in a habitability assessment, 120 habitability characteristics reflecting 13 major categories were evaluated for each habitat. These results were compared to identify the most acceptable habitat in each category. Ultimately, the data favored the horizontal orientation over the vertical and an eight-person crew over four. Implications of selecting this variant are discussed, including specific architectural challenges that result from the use of the full tank.

Habitability↗

Down-Selection of Four Common Habitat Variants

The Common Habitat is a large habitat that uses the Space Launch System core stage liquid oxygen tank as its primary structure. It has a gravity-independent internal architecture, such that identical units can be used on the lunar surface, Mars surface, and in microgravity. In developing the habitat, two key architectural questions emerged. Should the internal layout use a vertical or horizontal orientation of the tank? Should the crew size be four or eight? This led to the design of four variants: a four-crew horizontal, four-crew vertical, eight-crew horizontal, and eight-crew vertical. The primary consideration applied for down-selection was the crew experience living and working in the habitat, inclusive of crew productivity, well-being, and survivability. Based on this consideration, a series of seven assessments was performed to compare the four variants. A stowage assessment developed a standard logistics module and then considered the amounts of water to be stored in each variant. It then estimated how much stowage could be carried onboard each Common Habitat and how many logistics modules are required by each variant for a given mission duration. A functional analysis identified and compared the living and working functions across the four habitat, ranking them relative to each other. A crew time assessment first estimated the total crew time, building a weekly crew timeline for both four and eight-person crews. It then allocated time to activities linked to living and working functions, comparing how much time was available for each function in each variant. A science productivity assessment developed a relative metric using crew time, science stowage, and assumed rates of experiment consumables use to analytically compare the four variants. It also comparatively ranked the habitats with respect to a number of subjective parameters and a workstation acceptability rating. A maintenance capacity assessment identified and compared eleven generic maintenance capabilities across the four variants and also ranked the variants for their predicted ability to complete twelve fabrication, maintenance, and repair scenarios. A contingency responsiveness analysis examined twelve serious in-flight contingencies. For each scenario, the number of crew needed to respond was predicted and acceptability of various aspects of contingency response was evaluated, comparing the four variants against each other. Finally, in a habitability assessment, 120 habitability characteristics reflecting 13 major categories were evaluated for each habitat. These results were compared to identify the most acceptable habitat in each category. Ultimately, the data was shown to favor the horizontal orientation over the vertical and an eight-person crew over four. Implications of selecting this variant are discussed, including specific architectural challenges that result from the use of the full SLS liquid oxygen tank.

Habitability↗

IMPACT 1.0—Task Impairment: A Novel Approach for Assessing Impairment during Exploration-Class Missions

Exploration-class and International Space Station (ISS) missions have significantly different levels of associated medical risk for crewmembers. The Integrated Medical Model (IMM), the probabilistic risk assessment tool used for ISS medical trade-space analyses, uses a Functional Impairment (FI) metric to determine quality time lost should a crewmember be afflicted with a medical condition. While IMM-based FI has been successful for ISS operations, it has limitations when applied to exploration-class missions. As the National Aeronautics and Space Administration (NASA) looks ahead to Gateway, Artemis, and Martian missions, a novel, dynamic, and mission-appropriate impairment paradigm is necessary for accurate contingency planning. This paradigm, Task Impairment (TI), fulfills that need by utilizing mission-specific tasks. TI will allow future capability for a loss of mission metric, previously not available with IMM. TI serves as a replacement metric for FI within IMPACT, the next-generation trade-space analysis tool suite created to replace the IMM. IMPACT significantly increases the fidelity of probabilistic risk assessment for exploration-class missions. The Human Exploration of Mars Preliminary List of Crew Tasks (MTL, a source of 1100+ exploration-class mission-specific tasks for crewmembers) was used to calculate TI. Using the Task List, 18 individual Human System Categories were identified as being required to perform each task (e.g., Cardiopulmonary, Cognitive, etc.). Each of the 1200+ tasks were mapped to the Human System categories listed in the Task List. The total number of tasks in each category were tallied to determine how many tasks required each Human System. Lastly, each of the 120 medical conditions from the IMPACT condition list were mapped to the Human System categories to complete the TI calculation. NASA subject matter experts across five medical specialties established consensus for the mapping of each condition. The resulting total tasks impaired by each condition were used to calculate discrete TI values. This process was repeated for each of the four severity/resource utilization variants of each condition, and for each of the three phases of clinical care. Through this process, discrete TI values were calculated for each of the 120 IMPACT medical conditions and their variants. The Task Impairment metric provides higher fidelity, dynamic utility, and quicker analysis of medical impairment compared to the previous Functional Impairment metric used for the Integrated Medical Model. TI will be used for higher fidelity medical impairment analysis and contingency planning during Lunar, Martian, and other long-term exploration-class missions.

William L Fernandez↗

Conceptual Launch Vehicle and Spacecraft Design for Risk Assessment

One of the most challenging aspects of developing human space launch and exploration systems is minimizing and mitigating the many potential risk factors to ensure the safest possible design while also meeting the required cost, weight, and performance criteria. In order to accomplish this, effective risk analyses and trade studies are needed to identify key risk drivers, dependencies, and sensitivities as the design evolves. The Engineering Risk Assessment (ERA) team at NASA Ames Research Center (ARC) develops advanced risk analysis approaches, models, and tools to provide such meaningful risk and reliability data throughout vehicle development. The goal of the project presented in this memorandum is to design a generic launch 7 vehicle and spacecraft architecture that can be used to develop and demonstrate these new risk analysis techniques without relying on other proprietary or sensitive vehicle designs. To accomplish this, initial spacecraft and launch vehicle (LV) designs were established using historical sizing relationships for a mission delivering four crewmembers and equipment to the International Space Station (ISS). Mass-estimating relationships (MERs) were used to size the crew capsule and launch vehicle, and a combination of optimization techniques and iterative design processes were employed to determine a possible two-stage-to-orbit (TSTO) launch trajectory into a 350-kilometer orbit. Primary subsystems were also designed for the crewed capsule architecture, based on a 24-hour on-orbit mission with a 7-day contingency. Safety analysis was also performed to identify major risks to crew survivability and assess the system's overall reliability. These procedures and analyses validate that the architecture's basic design and performance are reasonable to be used for risk trade studies. While the vehicle designs presented are not intended to represent a viable architecture, they will provide a valuable initial platform for developing and demonstrating innovative risk assessment capabilities.

Launch Vehicle↗