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Mass and Volume Optimization of Space Flight Medical Kits

Resource allocation is a critical aspect of space mission planning. All resources, including medical resources, are subject to a number of mission constraints such a maximum mass and volume. However, unlike many resources, there is often limited understanding in how to optimize medical resources for a mission. The Integrated Medical Model (IMM) is a probabilistic model that estimates medical event occurrences and mission outcomes for different mission profiles. IMM simulates outcomes and describes the impact of medical events in terms of lost crew time, medical resource usage, and the potential for medically required evacuation. Previously published work describes an approach that uses the IMM to generate optimized medical kits that maximize benefit to the crew subject to mass and volume constraints. We improve upon the results obtained previously and extend our approach to minimize mass and volume while meeting some benefit threshold. METHODS We frame the medical kit optimization problem as a modified knapsack problem and implement an algorithm utilizing dynamic programming. Using this algorithm, optimized medical kits were generated for 3 mission scenarios with the goal of minimizing the medical kit mass and volume for a specified likelihood of evacuation or Crew Health Index (CHI) threshold. The algorithm was expanded to generate medical kits that maximize likelihood of evacuation or CHI subject to mass and volume constraints. RESULTS AND CONCLUSIONS In maximizing benefit to crew health subject to certain constraints, our algorithm generates medical kits that more closely resemble the unlimited-resource scenario than previous approaches which leverage medical risk information generated by the IMM. Our work here demonstrates that this algorithm provides an efficient and effective means to objectively allocate medical resources for spaceflight missions and provides an effective means of addressing tradeoffs in medical resource allocations and crew mission success parameters.

Monte Carlo Method↗

NASA Unmanned Aircraft (UA) Control and Non-Payload Communication (CNPC) System Waveform Trade Studies

Unmanned Aircraft Systems (UAS) represent a new capability that will provide a variety of services in the government (public) and commercial (civil) aviation sectors. The growth of this potential industry has not yet been realized due to the lack of a common understanding of what is required to safely operate UAS in the National Airspace System (NAS). To address this deficiency, NASA has established a project called UAS Integration in the NAS (UAS in the NAS), under the Integrated Systems Research Program (ISRP) of the Aeronautics Research Mission Directorate (ARMD). This project provides an opportunity to transition concepts, technology, algorithms, and knowledge to the Federal Aviation Administration (FAA) and other stakeholders to help them define the requirements, regulations, and issues for routine UAS access to the NAS. The safe, routine, and efficient integration of UAS into the NAS requires new radio frequency (RF) spectrum allocations and a new data communications system which is both secure and scalable with increasing UAS traffic without adversely impacting the Air Traffic Control (ATC) communication system. These data communications, referred to as Control and Non-Payload Communications (CNPC), whose purpose is to exchange information between the unmanned aircraft and the ground control station to ensure safe, reliable, and effective unmanned aircraft flight operation. A Communications Subproject within the UAS in the NAS Project has been established to address issues related to CNPC development, certification and fielding. The focus of the Communications Subproject is on validating and allocating new RF spectrum and data link communications to enable civil UAS integration into the NAS. The goal is to validate secure, robust data links within the allocated frequency spectrum for UAS. A vision, architectural concepts, and seed requirements for the future commercial UAS CNPC system have been developed by RTCA Special Committee 203 (SC-203) in the process of determining formal recommendations to the FAA in its role provided for under the Federal Advisory Committee Act. NASA intends to conduct its research and development in keeping with this vision and associated architectural concepts. The prototype communication systems developed and tested by NASA will be used to validate and update the initial SC-203 requirements in order to provide a foundation for SC-203's Minimum Aviation System Performance Standards (MASPS).

Aircraft Communications↗

Frequency Spectrum for Integration of Unmanned Aircraft

The goal of enabling the integration of unmanned aircraft systems (UAS) into the National Airspace System (NAS) in terms of UAS achieving routine access to the NAS has been established as a national goal in the United States. Among a number of technical barriers that must be overcome to meet this goal is the absence of standard, certifiable communications links supplying the control and non-payload communications (CNPC) function, essentially providing the link over which a pilot on the ground can control the unmanned aircraft (UA). The International Civil Aviation Organization (ICAO) has determined that the CNPC link must operate over protected aviation spectrum. Therefore protected aviation spectrum must be allocated for this function, approved through the processes of the International Telecommunications Union Radiocommunication Sector (ITU-R). Work has progressed in the definition of spectrum requirements for CNPC, and a portion of these requirements has been satisfied through new allocations approved at the ITU-R 2012 World Radiocommunication Conference (WRC-12). Additional work is ongoing or planned to satisfy the remaining spectrum requirements and define the specifications for the usage of CNPC spectrum allocations and develop supporting standards. This paper provides an overview of the status of RF spectrum for UAS CNPC. Issues that have been identified and ongoing analysis and research that will be necessary to fulfill spectrum requirements for UAS CNPC will be discussed. The results of this work will provide for the safe integration of UA into the NAS in both the LOS (Line of Sight) and BLOS (Beyond Line of Sight) realms.

aircraft communications↗

Artificial Intelligence Based Control Power Optimization on Tailless Aircraft

Traditional methods of control allocation optimization have shown difficulties in exploiting the full potential of controlling large arrays of control devices on innovative air vehicles. Artificial neutral networks are inspired by biological nervous systems and neurocomputing has successfully been applied to a variety of complex optimization problems. This project investigates the potential of applying neurocomputing to the control allocation optimization problem of Hybrid Wing Body (HWB) aircraft concepts to minimize control power, hinge moments, and actuator forces, while keeping system weights within acceptable limits. The main objective of this project is to develop a proof-of-concept process suitable to demonstrate the potential of using neurocomputing for optimizing actuation power for aircraft featuring multiple independently actuated control surfaces. A Nastran aeroservoelastic finite element model is used to generate a learning database of hinge moment and actuation power characteristics for an array of flight conditions and control surface deflections. An artificial neural network incorporating a genetic algorithm then uses this training data to perform control allocation optimization for the investigated aircraft configuration. The phase I project showed that optimization results for the sum of required hinge moments are improved by more than 12% over the best Nastran solution by using the neural network optimization process.

Gern, Frank↗

Developing a Crew Time Model for Human Exploration Missions to Mars

Candidate human missions to Mars require mission lengths that could extend beyond those that have previously been demonstrated during crewed Lunar (Apollo) and International Space Station (ISS) missions. The nature of the architectures required for deep space human exploration will likely necessitate major changes in how crews operate and maintain the spacecraft. The uncertainties associated with these shifts in mission constructs - including changes to habitation systems, transit durations, and system operations - raise concerns as to the ability of the crew to complete required overhead activities while still having time to conduct a set of robust exploration activities. This paper will present an initial assessment of crew operational requirements for human missions to the Mars surface. The presented results integrate assessments of crew habitation, system maintenance, and utilization to present a comprehensive analysis of potential crew time usage. Destination operations were assessed for a short (approx. 50 day) and long duration (approx. 500 day) surface habitation case. Crew time allocations are broken out by mission segment, and the availability of utilization opportunities was evaluated throughout the entire mission progression. To support this assessment, the integrated crew operations model (ICOM) was developed. ICOM was used to parse overhead, maintenance and system repair, and destination operations requirements within each mission segment - outbound transit, Mars surface duration, and return transit - to develop a comprehensive estimation of exploration crew time allocations. Overhead operational requirements included daily crew operations, health maintenance activities, and down time. Maintenance and repair operational allocations are derived using the Exploration Maintainability and Analysis Tool (EMAT) to develop a probabilistic estimation of crew repair time necessary to maintain systems functionality throughout the mission.

Battfeld, Bryan↗

How To Make the Most of Your Human: Design Considerations for Single Pilot Operations

Reconsidering the function allocation between automation and the pilot in the flight deck is the next step in improving aviation safety. The current allocation, based on who does what best, makes poor use of the pilot's resources and abilities. In some cases it may actually handicap pilots from performing their role. Improving pilot performance first lies in defining the role of the pilot - why a human is needed in the first place. The next step is allocating functions based on the needs of that role (rather than fitness), then using automation to target specific human weaknesses in performing that role. Examples are provided (some of which could be implemented in conventional cockpits now). Along the way, the definition of human error and the idea that eliminating/automating the pilot will reduce instances of human error will be challenged.

Schutte, Paul C.↗

Satellite Communications for Unmanned Aircraft C2 Links: C-Band, Ku-Band and Ka-Band

Unmanned aircraft (UA) that require access to controlled (or non-segregated) airspace require a highly reliable and robust command and control (C2) link, operating over protected aviation spectrum. While operating within radio line-of-sight (LOS) UA can make use of air-to-ground C2 links to terrestrial stations. When operating beyond LOS (BLOS) where a group of networked terrestrial stations does not exist to provide effective BLOS coverage, a satellite communications link is required. Protected aviation spectrum for satellite C2 links has only recently been allocated in bands where operational satellites exist. A previously existing C-Band allocation covers a bands where there are currently no operational satellites. The new allocations, within the Fixed Satellite Service bands at Ku and Ka-Bands will not be finalized until 2023 due to the need for the development of standards and technical decisions on the operation of UA satellite C2 links within these bands. This paper provides an overview of BLOS satellite C2 links, some of the conditions which will need to be met for the operation of such links, and a look at some aspects of spectrum sharing which may constrain these operations.

radiofrequency spectrum↗

Unmanned Aircraft Systems (UAS) Integration in the National Airspace System (NAS) Project KDP-C Review

The topics discussed are the UAS-NAS project life-cycle and ARMD thrust flow down, as well as the UAS environments and how we operate in those environments. NASA's Armstrong Flight Research Center at Edwards, CA, is leading a project designed to help integrate unmanned air vehicles into the world around us. The Unmanned Aircraft Systems Integration in the National Airspace System project, or UAS in the NAS, will contribute capabilities designed to reduce technical barriers related to safety and operational challenges associated with enabling routine UAS access to the NAS. The project falls under the Integrated Systems Research Program office managed at NASA Headquarters by the agency's Aeronautics Research Mission Directorate. NASA's four aeronautics research centers - Armstrong, Ames Research Center, Langley Research Center, and Glenn Research Center - are part of the technology development project. With the use and diversity of unmanned aircraft growing rapidly, new uses for these vehicles are constantly being considered. Unmanned aircraft promise new ways of increasing efficiency, reducing costs, enhancing safety and saving lives 460265main_ED10-0132-16_full.jpg Unmanned aircraft systems such as NASA's Global Hawks (above) and Predator B named Ikhana (below), along with numerous other unmanned aircraft systems large and small, are the prime focus of the UAS in the NAS effort to integrate them into the national airspace. Credits: NASA Photos 710580main_ED07-0243-37_full.jpg The UAS in the NAS project envisions performance-based routine access to all segments of the national airspace for all unmanned aircraft system classes, once all safety-related and technical barriers are overcome. The project will provide critical data to such key stakeholders and customers as the Federal Aviation Administration and RTCA Special Committee 203 (formerly the Radio Technical Commission for Aeronautics) by conducting integrated, relevant system-level tests to adequately address safety and operational challenges of national airspace access by unmanned aircraft systems, or UAS. In the process, the project will work with other key stakeholders to define necessary deliverables and products to help enable such access. Within the project, NASA is focusing on five sub-projects. These five focus areas include assurance of safe separation of unmanned aircraft from manned aircraft when flying in the national airspace; safety-critical command and control systems and radio frequencies to enable safe operation of UAS; human factors issues for ground control stations; airworthiness certification standards for UAS avionics and integrated tests and evaluation designed to determine the viability of emerging UAS technology. Five Focus Areas of the UAS Integration in the NAS Project Separation Assurance Provide an assessment of how planned Next Generation Air Transportation System (NextGen) separation assurance systems, with different functional allocations, perform for UAS in mixed operations with manned aircraft Assess the applicability to UAS and the performance of NASA NextGen separation assurance systems in flight tests with realistic latencies and uncertain trajectories Assess functional allocations ranging from today's ground-based, controller-provided aircraft separation to fully autonomous airborne self-separation Communications Develop data and rationale to obtain appropriate frequency spectrum allocations to enable safe and efficient operation of UAS in the NAS Develop and validate candidate secure safety-critical command and control system/subsystem test equipment for UAS that complies with UAS international/national frequency regulations, standards and recommended practices and minimum operational and aviation system performance standards for UAS Perform analysis to support recommendations for integration of safety-critical command and control systems and air traffic control communications to ensure safe and efficient operation of UAS in the NAS Human Systems Integration Develop a research test bed and database to provide data and proof of concept for GCS - ground control station - operations in the NAS Coordinate with standards organizations to develop human-factors guidelines for GCS operation in the NAS Certification Define a UAS classification scheme and approach to determining Federal Aviation Regulation airworthiness requirements applicable to all UAS digital avionics Provide hazard and risk-related data to support development of type design criteria and best development practices Integrated Tests and Evaluation Integrate and test mature concepts from technical elements to demonstrate and test viability Evaluate the performance of technology development in a relevant environment (full-mission, human-in-the-loop simulations and flight tests)

outreach↗

UAS Satellite Earth Station Emission Limits for Terrestrial System Interference Protection

Unmanned aircraft systems (UAS) will have a major impact on future aviation. Medium and large UA operating at altitudes above 3000 feet will require access to non-segregated, that is, controlled airspace. In order for unmanned aircraft to be integrated into the airspace and operate with other commercial aircraft, a very reliable command and control (C2, a. k. a. control and non-payload communications, (CNPC)) link is required. For operations covering large distances or over remote locations, a beyond-line-of-sight (BLOS) CNPC link would need to be implemented through satellite. Significant progress has taken place on several fronts to advance the integration of UAS into controlled airspace, including the recent completion of Minimum Operational Performance Standards (MOPS) for terrestrial line-of-sight (LOS) UAS command and control (C2) links. The development of MOPS for beyond line-of-sight C2 satellite communication links is underway. Meanwhile the allocation of spectrum for UAS C2 by the International Telecommunications Union Radiocommunication Sector (ITU-R) has also progressed. Spectrum for LOS C2 was allocated at the 2012 World Radiocommunication Conference (WRC-12), and for BLOS C2 an allocation was made at WRC-15, under WRC-15 Resolution 155. Resolution 155, however, does not come into effect until several other actions have been completed. One of these required actions is the identification of a power flux density (pfd) limit on the emissions of UAS Ku-Band satellite communications transmitters reaching the ground. The pfd limit is intended to protect terrestrial systems from harmful interference. WRC-19 is expected to finalize the pfd limit. In preparation for WRC-19, analyses of the required pfd limit are on-going, and supporting activities such as propagation modeling are also planned. This paper provides the status of these activities.

radiofrequency spectrum↗

Assessment and Verification of SLS Block 1-B Exploration Upper Stage State and Stage Disposal Performance

One of the SLS Navigation System's key performance requirements is a constraint on the payload system's delta-v allocation to correct for insertion errors due to vehicle state uncertainty at payload separation. The SLS navigation team has developed a Delta-Delta-V analysis approach to assess the effect on trajectory correction maneuver (TCM) design needed to correct for navigation errors. This approach differs from traditional covariance analysis based methods and makes no assumptions with regard to the propagation of the state dynamics. This allows for consideration of non-linearity in the propagation of state uncertainties. The Delta-Delta-V analysis approach re-optimizes perturbed SLS mission trajectories by varying key mission states in accordance with an assumed state error. The state error is developed from detailed vehicle 6-DOF Monte Carlo analysis or generated using covariance analysis. These perturbed trajectories are compared to a nominal trajectory to determine necessary TCM design. To implement this analysis approach, a tool set was developed which combines the functionality of a 3-DOF trajectory optimization tool, Copernicus, and a detailed 6-DOF vehicle simulation tool, Marshall Aerospace Vehicle Representation in C (MAVERIC). In addition to delta-v allocation constraints on SLS navigation performance, SLS mission requirement dictate successful upper stage disposal. Due to engine and propellant constraints, the SLS Exploration Upper Stage (EUS) must dispose into heliocentric space by means of a lunar fly-by maneuver. As with payload delta-v allocation, upper stage disposal maneuvers must place the EUS on a trajectory that maximizes the probability of achieving a heliocentric orbit post Lunar fly-by considering all sources of vehicle state uncertainty prior to the maneuver. To ensure disposal, the SLS navigation team has developed an analysis approach to derive optimal disposal guidance targets. This approach maximizes the state error covariance prior to the maneuver to develop and re-optimize a nominal disposal maneuver (DM) target that, if achieved, would maximize the potential for successful upper stage disposal. For EUS disposal analysis, a set of two tools was developed. The first considers only the nominal pre-disposal maneuver state, vehicle constraints, and an a priori estimate of the state error covariance. In the analysis, the optimal nominal disposal target is determined. This is performed by re-formulating the trajectory optimization to consider constraints on the eigenvectors of the error ellipse applied to the nominal trajectory. A bisection search methodology is implemented in the tool to refine these dispersions resulting in the maximum dispersion feasible for successful disposal via lunar fly-by. Success is defined based on the probability that the vehicle will not impact the lunar surface and will achieve a characteristic energy (C3) relative to the Earth such that it is no longer in the Earth-Moon system. The second tool propagates post-disposal maneuver states to determine the success of disposal for provided trajectory achieved states. This is performed using the optimized nominal target within the 6-DOF vehicle simulation. This paper will discuss the application of the Delta-Delta-V analysis approach for performance evaluation as well as trajectory re-optimization so as to demonstrate the system's capability in meeting performance constraints. Additionally, further discussion of the implementation of assessing disposal analysis will be provided.

Patrick, Sean↗

Robotic Specialization in Autonomous Robotic Structural Assembly

Robotic in-space assembly of large space structures is a long-term NASA goal to reduce launch costs and enable larger scale missions. Recently, researchers have proposed using discrete lattice building blocks and co-designed robots to build high-performance, scalable primary structure for various on-orbit and surface applications. These robots would locomote on the lattice and work in teams to build and reconfigure building-blocks into functional structure. However, the most reliable and efficient robotic system architecture, characterized by the number of different robotic 'species' and the allocation of functionality between species, is an open question. To address this problem, we decompose the robotic building-block assembly task into functional primitives and, in simulation, study the performance of the the variety of possible resulting architectures. For a set consisting of five process types (move self, move block, move friend, align bock, fasten block), we describe a method of feature space exploration and ranking based on energy and reliability cost functions. The solution space is enumerated, filtered for unique solutions, and evaluated against energy and reliability cost functions for various simulated build sizes. We find that a 2 species system, dividing the five mentioned process types between one unit cell transport robot and one fastening robot, results in the lowest energy cost system, at some cost to reliability. This system enables fastening functionality to occupy the build front while reducing the need for that functional mass to travel back and forth from a feed station. Because the details of a robot design affect the weighting and final allocation of functionality, a sensitivity analysis was conducted to evaluate the effect of changing mass allocations on architecture performance. Future systems with additional functionalities such as repair, inspection, and others may use this process to analyze and determine alternative robot architectures.

Bernus, Borbala↗

A Generalized Approach to Aircraft Trajectory Prediction via Supervised Deep Learning

As research advances diverse forms and missions of aircraft, the National Airspace System (NAS) will become increasingly crowded, limiting current communications resources to accommodate aviation operations. Ongoing research proposes a paradigm of airspace communications, such that resources are autonomously and dynamically allocated via intelligent agents; this allocation requires accurate representations of the NAS, including the predicted positions of aircraft. State-of-the-art research emphasizes the importance of a hybrid-recurrent framework for trajectory prediction and compares the impact of commonly considered weather data on prediction accuracy. However, current research has been limited in its scope of efforts, frequently utilizing a unique flight route, architecture, set of weather data, and date range. This article considers the challenges of generalizing hybrid-recurrent predictive models for flight trajectories. Results illustrate an increase in error variance when identical models are trained over a generalized set of flights; this may be mitigated with careful tuning of hyperparameters, both in the network structure and optimization algorithms. Even so, an irreducible vertical error was identified, resulting from the complex takeoff and landing procedures which can not be correlated to functions of weather or additional assumptions of aircraft behavior. Finally, the use of a test route indicates that generalized models still do not possess sufficient knowledge for general aircraft predictions, with mean error increases ranging from 70-500%. These results illustrate the need for continued efforts on improving model versatility, as well as potential limitations for spectrum allocation near airports and other centers.

Nathan Schimpf↗

Bayesian Rules of Thumb: Robust Uncertainty Quantification in Early Project Cost Estimation

Systems engineers often make use of cost Rules ofThumb in order to estimate cost during early phases of projectformulation. These Rules of Thumb typically take the form ofa sequence of percentages over which a total cost is allocatedacross NASA WBS elements. Rules of Thumb can then be usedto extrapolate cost from one or more known WBS elements tothe remaining unknown WBS elements, assisting early projectformulation architecture studies (such as those in JPL’s Team Xand A Team).A number of issues can arise when generating and using costRules of Thumb. For example, many records of project costsconsist of incomplete data. Typical methods of dealing withincomplete cost allocation data include (a) ignoring missionswith incomplete data, or (b) taking averages of the non-zero percentagesacross missions, but both of these methods can result inbiased estimates if the existence of incomplete data correlateswith total mission cost or any particular WBS element. Anothercommon example is cost reported in one or more incorrect WBSelements. This is especially prevalent in smaller missions whereit is more common for engineers to perform tasks that fall underthe purview of multiple WBS elements.Furthermore, a Rule of Thumb estimate is typically reported asa point estimate; there is no reported uncertainty around thepercentages used to generate an allocation. Even in the rarecase in which confidence intervals around mean percentages areprovided, there may be positive or negative correlations betweenWBS elements which can skew estimates.Here we attempt to address these problems by formulatingprobabilistic Rules of Thumb in which a distribution of allocationschemes, rather than a single allocation scheme, is generated.We use a bootstrap imputation method to simultaneouslyaccount for uncertainty in the missing data while using allavailable information contained in the dataset. The imputeddatasets are then input into a multivariate Bayesian modelwhich accounts for correlations between WBS elements andproperly accounts for uncertainty in the final Rule of Thumbpercentages and predictions. We describe the mathematicalmodel and provides snippets of R code utilizing the brms(Bayesian Regression Models using Stan) package. To illustratethis model, we generate a Bayesian Level 2 WBS Cost Rule ofThumb for MIDEX (Medium-Class Explorers) missions withdata extracted from NASA’s CADRe. We then compare thismethod’s performance with the classical Rule of Thumb method.

Hooke, Melissa A↗

Aerocapture Trajectory Design for Uranus Orbiter

Introduction: The recently released National Academies Planetary Science and Astrobiology Decadal Survey 2023-2032 [1] identified the Ice Giants as the top priority science destination. While the survey acknowledged the potential for either a Uranus Orbiter and Probe (UOP) mission or a Neptune-Triton Odyssey mission, it ultimately identified the former as the highest priority new flagship mission. UOP missions calls for a launch window of opportunity between 2031-2038 with 12-15 year interplanetary cruise time along with a fully-propulsive Uranus Orbit Insertion burn on the order of a few km/s. However, a mission to Uranus with the same science payload could utilize aerocapture for orbit insertion to achieve both a significant reduction in the interplanetary cruise time and reduction in propulsive burn costs. Why Aerocapture: Aerocapture is a promising propellant and time-saving orbital insertion technique for planetary destinations with an atmosphere. Although not flight-proven, previous aerocapture systems studies in the literature have demonstrated both the validity and robustness of the technique at various planetary destinations. With respect to the Ice Giant planets, Neptune has seen more of the analysis in the literature. For science missions at Neptune, aerocapture can enable 1.4 times more delivered mass to orbit than an all-propulsive mission for the same launch vehicle while reducing interplanetary cruise times by more than 3 years [2] Additionally with modern guidance and control, Neptune aerocapture with blunt-body aeroshells is realizable [3][4]. There are limited papers in the literature investigating Uranus aerocapture with those available providing a preliminary feasibility assessment [5]. Consequently, the two-year funded NASA Space Technology Mission Directorate (STMD)-funded project, titled Aerocapture System as an Enabling Technology for Ice Giants Missions, aims to mature the analysis and technology state of Uranus aerocapture. Trajectory Design: This paper presents the current state of the trajectory design in support of the new aerocapture project. The project design philosophy is inspired from recent Neptune aerocapture studies, which employed modern guidance and control, in the sense that blunt-body aeroshells are analyzed. An assessment of the theoretical flight path angle corridor width is conducted for a range of ballistic coefficients and lift-to-drag ratios for both Space Launch System and Falcon Heavy Launch Vehicle interplanetary trajectory solutions. The results from the corridor width assessment provide an assessment of the aerocapture design-space and qualitative metrics on trajectory design considerations. The Program to Optimize Simulated Trajectories II (POST2) is utilized to run Monte Carlo simulations of Uranus aerocapture three-degree-of-freedom bank angle modulated trajectories using a closed-loop numerical-predictor corrector guidance algorithm. UranusGRAM 2021 is utilized as the atmospheric model [6]. A Uranus-developed aerodatabase, originally derived from Mars Science Laboratory (MSL), is utilized to provide vehicle aerodynamics over a wide range of hypersonic flow regimes. A MSL-derived 70 deg 4.5m diameter sphere-cone aeroshell that houses the UOP payload mass is assumed. Robustness testing and performance analysis is conducted, including the assessment of entry state errors, atmosphere density variations, and aerodynamic dispersions. Post-aerocapture Delta-V and aerothermal statistics are formulated into propellant mass and TPS requirements. The results presented in the paper will demonstrate the trajectory viability of Uranus aerocapture. Preliminary Results: Preliminary trajectory design results indicates successful Uranus aerocapture with a blunt-body aeroshell housing the same payload mass as the UOP mission from an Earth-to-Uranus interplanetary trajectory arriving in less than 7 years. From this interplanetary trajectory, aerocapture provides an orbit insertion Delta-V capability of 6.9 km/s requiring less than 300 m/s for post-aerocapture correction burns (15% of wet mass allocated to propellant). To put this into perspective, the UOP study utilized an Earth-to-Uranus trajectory that arrives in 13 years and requires more than 1000 m/s for fully-propulsive orbit insertion (40% of wet mass allocated to propellant). Achieving the same 6.9 km/s Delta-V capability fully-propulsively is mass prohibitive (97% of wet mass allocated to propellant). Nevertheless, aerocapture has the potential to reduce interplanetary transit times to Uranus by half while delivering the same payload mass to orbit in a reduced propellant mass footprint.

Rohan Deshmukh↗

The Collection, Usage, and Preliminary Examination of the Apollo Sample Suite: Lessons for Artemis

Apollo Sample Collection and Usage: From 1969 to 1972 there were six Apollo missions to the surface of the Moon during which the astronauts collected 382 kg of rock and regolith (~2200 samples). The samples collected fall into these general categories: rocks (~66% by mass), rake samples (~4%), bulk regolith (~24%), and specialty regolith (deep drill cores, drive tubes, sealed bulk regolith) samples (~6%). In each category there are a variety of different subtypes available for study, e.g., among the bulk regolith samples there are also skim, trench, and (partially) shaded regolith samples each sampling unique types or depths of regolith. This variety of subsamples has enabled a multitude of different studies over the past 55 years (>3400 individual requests). We are still averaging ~50 unique requests and have allocated >500 individual Apollo samples annually for the past 10 years (2020 excepted). Looking at the 4,675 non-ANGSA (Apollo Next Generation Sample Analysis) samples allocated over the past 10 years, the proportions of allocated samples do not precisely align with the abundance (by mass) of those samples withing the collection: Rock (69.4 %); Rake (10.8 %); Bulk Regolith (15.5 %); Drive Tube (3.3 %); Core/Specialty (1.0 %). Apollo Preliminary Examination (PE): The PE process differs significantly for the various sample types enumerated above; we focus on regolith and rock samples here. During the Apollo mission era, the PE process evolved over the course of the missions; below is what was done for the Apollo 17 mission. For regolith samples, the PE process was: (1) documented bags containing regolith are opened, photographed, and described; (2) large rocks are removed and treated separately; (3) 25% to 33% of the bulk soil is scooped out, weighed, and stored in reserve; (4) the remaining sample is sieved to produce the size fractions <1, 1- 2, 2-4, and 4-10 mm, all of which are weighed. For rock samples, the process is: (1) removing rocks from the container(s) it came back from the Moon in; (2) rematching any materials that spalled off the rock to their original location; (3) numbering, weighing, and basic photographic documentation; (4) dusting with a gentle N2 gas jet; (5) Orthogonal photography; (6) detailed description of the textures and features of the rock; (7) rock modelling and measurement; (8) stereophotography; (9) determination of the orientation of the rock on the lunar surface. Drive tubes and deep drill cores were not characterized during PE beyond an initial weight and a sketch of the interior tube materials derived from 2D medical X-ray images. Catalogs: The ongoing utility of the Apollo samples is enabled by the robust cataloguing process for the samples [3-5], which allows the scientific community to accurately request samples uniquely suited to their proposed studies. A common misconception, however, is the amount of detail that goes into the initial catalog (e.g., [6]) for a collection from the preliminary examination (PE) period, versus what goes into the catalogs that come later in the life cycle of the samples from that mission (e.g., [7]). The only required data for a PE catalog is a weight, a basic photograph, and a description of the nature of the sample. Artemis PE: Over the past few years, the ongoing ANGSA project studied previously unopened Apollo 17 double drive tube samples 73001/2 [1], and a PE of the drive tubes was done. The PE took the existing core dissection process (developed during PE of Apollo cores in the 1970s, 1980s), and modernized it [7]. The main lesson from the ANGSA PE relative to future missions was that the physical work done during PE of lunar samples has not changed much over the past 5 decades. The use of “modern” technology during PE (e.g., XCT; multispectral analyses) resulted in an enhanced initial understanding of the 73001 and 73002 drive tubes, but greatly increased the time required. The lessons learned from recent astromaterial PEs (e.g., ANGSA and OREx) are important to consider when planning for Artemis, but the unique nature of the Artemis Campaign means many lessons learned from these mission will not be applicable. Given the time constraints (6 months) and likely number of samples that will be returned by Artemis (>200), the Artemis PE catalog will necessarily look much more like [4] than [6].

J Gross↗

OSIRIS-REx Curation: The First Year with Bennu Samples on Earth

The OSIRIS-REx (Origins, Spectral Interpretation, Resource Identification, and Security – Regolith Explorer) sample return capsule landed on the Utah Test and Training Range (UTTR) on September 24, 2023. Preparations for the curation of the sample from asteroid Bennu inside of this capsule spanned more than a decade. On the morning of landing, the sample return capsule was brought to a temporary cleanroom at UTTR for initial de-integration and connection of the sample canister to a nitrogen gas purge to protect the sample from modification by the terrestrial atmosphere. In the week following landing, the sample canister was flown to Houston while on nitrogen purge, transferred to a nitrogen atmosphere glovebox at NASA Johnson Space Center in which the canister lid was removed revealing small amounts of sample on the inside of the canister lid and avionics deck, some of this sample was allocated rapidly to the mission sample analysis team as “quick look” samples. Next, the Touch-and-Go sample acquisition mechanism (TAGSAM) head was disassembled inside of a specially designed glovebox. A challenge arose during one of the last stages of disassembly when two fasteners resisted being loosened. The curation team was able to remove 70.3 grams of asteroid sample from the TAGSAM head with those fasteners in-place and began initial sample processing which supported long-term curation of hermetically sealed and frozen samples, transfer of some samples to remote storage, and allocation of aggregate samples to the mission sample analysis team. Meanwhile, curation engineers developed a tool to remove the stubborn fasteners without contaminating the remaining sample, enabling the remaining bulk sample to be transferred to long-term storage trays in January 2024. With this second part of the bulk sample, the returned bulk asteroid sample reached 121.6 grams. During disassembly and prior to sealing the bulk sample trays into long-term storage containers, archival photographs were collected. Select particles are gradually being XCT scanned while inside of containers that hold a nitrogen atmosphere. The initial OSIRIS-REx sample catalog was released in spring 2024 with an update in fall 2024. The curation team will be busy working to allocate samples to scientists around the world for the foreseeable future.

Curation↗

Sampling Size Optimization for Bioburden Density Estimation in Planetary Protection

Planetary protection (PP) is a discipline that focuses on minimizing the biological contamination of spacecraft to ensure compliance with international policy. Precise estimation of bioburden - the total number of microbes in or on spacecraft hardware – and the bioburden density are of utmost importance for PP. Such estimation is the way concordance with requirements is demonstrated, and it is critical for quantifying the potential risk of inadvertently contaminating other planetary bodies. Although a suite of molecular techniques have been used to thoroughly characterize and profile the microbiome of various cleanroom environments and spacecraft, the gold standard remains the physical enumeration of microbes via culturing of samples directly taken from spacecraft and associated surfaces. However, due to technical, budgetary, and programmatic constraints, only a manageable portion (around 10%) of the entire spacecraft surface is directly sampled with cotton swabs or wipes. To generate the bioburden current best estimate (CBE) for components not directly verifiable, the accepted approach is to apply a NASA-defined bioburden estimate based on the components’ manufacturing or assembly environment. This approach utilizes a prespecified bioburden density estimation that applies a maximum value across the total surface area of the specified component. For hardware components that underwent similar assembly processes, an implied bioburden is adopted for all components, based on a direct verification of a representative component within the same lot. Once all components have a CBE, the bioburden estimates are generated. In previous publication [ 1], we have shown that statistical risks quantifying the accuracy of the estimates for sampled, prespecified, and implied components can be derived and ranked. For mean squared error (MSE) function, the risks are available analytically and hence a cost function can be obtained to optimize the risks with respect to the sampling area and sampling cost. Since the sampling area and sampling cost are two complimentary variables, their sum will have a well-defined minimum. This paper presents the multivariate optimization of the integrated risk of an empirical Bayes estimator to determine the optimal sampling schedule for a given number of components. It is assumed that given a number of components, N, the bioburden density for each component can either be sampled, implied, or prespecified. The multivariate optimization searches through different options to sample, imply or prespecify the bioburden density for a component, and account for the component’s surface area and cost of sampling. The idea of the optimization is based on the observation that the statistical risk of using an estimator is a monotonically decreasing function of the sampled area. The larger the sampled area, the lower the risk of using the estimator as the estimator becomes more and more accurate as the sampling area increases. On the other hand, the cost of sampling is monotonically increasing as the sampled surface grows. This makes the risk and total cost of sampling complimentary variables which can be counterbalanced to achieve an optimal overall value with respect to the sampled surface. In this paper, the integrated risk has been used to quantify the accuracy of the estimator. This risk has been selected because it depends on neither the true value of the parameter nor on the collected data. The cost of each sample was also available to obtain the total cost of sampling of N components. The paper will present the results based on computer-simulated data as well as the data collected during the InSight mission. The computer-simulated data have N components with randomly generated total areas and each component assigned to one of the three categories according to the method of estimating of bioburden density: sampled, implied, or prespecified. The cost of sampling is also available. The cost of sampling is estimated based on a cost model provided by the planetary protection group at JPL. For this paper, the overall cost was assumed to be a linear function of exposure. The optimization process finds the allocation of the components to the three categories that minimizes the tradeoff between integrated risk and total cost. For the InSight data, a set of components is selected representing all three categories, and optimization is performed to determine if the performed allocation was optimal or if a better allocation could have been obtained. To the best of our knowledge, this work is the first attempt not only perform an accurate estimation of bioburden density but also do it in an optimal way.

97 - MATHEMATICS AND COMPUTING↗

Tonoplast Sucrose Transporter SUT4-Dependent Sugar Partitioning Modulates Phenological Transitions and Reproductive Success in Poplar

Climate uncertainty is intensifying the need for greater plasticity in carbohydrate reserve utilization to support winter survival and spring growth in woody perennials. In poplar, the single-copy SUT4, which encodes a tonoplast-localized sucrose transporter, and the SUT5/SUT6 genome duplicates, which encode plasma membrane-localized transporters, are expressed year-round, with SUT4 showing the highest expression during cool seasons. Given its role in vacuolar sucrose efflux and winter-predominant expression, SUT4 may play a key role in modulating seasonal carbohydrate dynamics. While SUT4-knockdown and knockout effects have been studied under greenhouse conditions, their impact under field conditions remains unexplored. Here, we report a field-based study comparing CRISPR knockout mutants of winter-expressed SUT4 and SUT5/SUT6 in Populus tremula x alba. We show that sut4, but not sut5/6, mutants exhibited earlier autumn leaf senescence, delayed spring bud flush, reduced stem growth, and altered sugar partitioning in winter xylem and bark relative to controls. After 2 years in the field, all genotypes flowered before leaf flush in early spring; however, sut4 mutants produced sterile ovules despite developing normal-looking catkins. Metabolic profiling revealed disrupted sucrose and raffinose dynamics in elongating sut4 catkins. This was accompanied by transcriptomic signatures of elevated stress and downregulation of proanthocyanidin biosynthesis and circadian clock genes. These findings highlight the critical role of SUT4 in coordinating sugar allocation, stress responses, and seasonal development in poplar.

09 BIOMASS FUELS↗