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Earth Entry Vehicle for Mars Sample Return

The driving requirement for design of a Mars Sample return mission is assuring containment of the returned samples. The impact of this requirement on developmental costs, mass allocation, and design approach of the Earth Entry Vehicle is significant. A simple Earth entry vehicle is described which can meet these requirements and safely transport the Mars Sample Return mission's sample through the Earth's atmosphere to a recoverable location on the surface. Detailed analysis and test are combined with probabilistic risk assessment to design this entirely passive concept that circumvents the potential failure modes of a parachute terminal descent system. The design also possesses features that mitigate other risks during the entry, descent, landing and recovery phases. The results of a full-scale drop test are summarized.

Mitcheltree, R. A.↗

Probabilistic Design of a Mars Sample Return Earth Entry Vehicle Thermal Protection System

The driving requirement for design of a Mars Sample Return mission is to assure containment of the returned samples. Designing to, and demonstrating compliance with, such a requirement requires physics based tools that establish the relationship between engineer's sizing margins and probabilities of failure. The traditional method of determining margins on ablative thermal protection systems, while conservative, provides little insight into the actual probability of an over-temperature during flight. The objective of this paper is to describe a new methodology for establishing margins on sizing the thermal protection system (TPS). Results of this Monte Carlo approach are compared with traditional methods.

Dec, John A.↗

The Planetary Protection Strategy of the Earth Return Orbiter–Capture, Containment & Return System in the Context of the Mars Sample Return Campaign

The Mars Sample Return Campaign aims at bringing back to Earth the rock and atmospheric samples that the rover Perseverance has started to collect on the surface of Mars with the goal of analyzing them in a facility built specifically for this purpose to answer questions about the habitability of Mars. The Campaign consists of several missions, including the Earth Return Orbiter–Capture, Containment & Return System (ERO-CCRS), which will capture the samples previously put in Martian orbit, contain them in redundant containers to ensure that no unsterilized particles are released, and return them to Earth through a parachute-less entry vehicle. Both NASA and ESA policies address the United Nations’ Outer Space Treaty by addressing potential harm from material returned from solar system bodies beyond the Earth-Moon system. In the conduct of Mars Sample Return, the two agencies have agreed to apply approaches consistent with their own standards to campaign elements each provides. This work presents the overall strategy for both forward and backward planetary protection for the ERO-CCRS mission. Specifically, for forward planetary protection, CCRS is not required to meet specific bioburden requirements as a Category III mission provided the ERO (1) meets orbital lifetime requirements during orbiter operations and (2) any elements jettisoned at Mars meet orbital lifetime requirements. CCRS is required to be built in ISO-8 or better cleanrooms and, by agreement with ERO, be compatible with direct bioburden verification methods. For backward planetary protection, the overall approach includes building robust, highly reliable systems to prevent inadvertent release of unsterilized Mars material through redundant containment vessels and particle transport analyses. Ongoing work to define verification approaches and quantify containment assurance levels for specific sample return systems will also be discussed, along with how those data will inform launch approval for ERO-CCRS.

Giuseppe Cataldo↗

Overview of Micrometeoroid and Orbital Debris Analysis Process for Mars Sample Return Earth Entry System

Introduction: Micrometeoroid and orbital debris (MMOD) risk analyses for the Mars Sample Return (MSR) Earth Entry System (EES) have been significantly more rigorous than previously flown missions because of its categorization as a Class V restricted return mission. This means the returned samples present significant concern for biogenic contamination. These analyses seek to determine if a micrometeoroid or orbital debris strike would result in loss of containment assurance and are summarized in the flowchart in Fig. 1. Methodology: The mission is considered in two MMOD phases: a pre-release phase where the EES is protected by a Micrometeoroid Protection System (MMPS) and a post-release phase called “free-flight” where the EES is exposed directly to the MMOD environment. These phases correspond to interplanetary cruise and imminent re-entry, respectively. To inform the MMPS design, a 30-shot high velocity impact testing (HVIT) series on candidate configurations at NASA White Sands Test Facility was completed in the summer of 2022. Sample post-shot images are shown in Fig 2 [1]. These data are used to baseline the MMPS design and to tune the hydrocode simulations. ALE3D, CTH, and SPHC are the hydrocodes that simulate physics of high-speed impacts [2]. Results generated with these populate a penetration depth versus energy space beyond the testable velocity regime of HVIT (~7 km/s). The penetration depth versus energy space data are used to define a critical projectile diameter function called a Ballistic Limit Equation (BLE), where the projectile “criticality” is determined by zone dependent failure criteria defined a-priori [3]. For example, the nose of the heatshield has a failure criterion of 50% TPS penetration, assigned because the landing loads are concentrated on that region and no substructure damage is permitted. The BLEs for each vehicle material zone are input into the BUMPER 3 code, along with the vehicle surface mesh and the corresponding space environment model, to calculate a probability of penetration or number of penetrations. The environment models, MEM3 for MM and ORDEM 3.2 for OD, simulate the meteoroid environment from 0.2 to 2 au based on the Grün flux equation, and the debris environment up to 40,000 km altitude from Earth surface, respectively [4,5]. Presentation Focus: The presentation or poster will present the results to-date focusing on the full risk analysis process flow seen in Fig. 1. Details on the derivation of the failure criteria will be discussed, along with HVIT results and how these influenced the MMPS configuration baseline decision. Further, results of hydrocode simulations will be presented and the tuning to HVIT outputs will be described. Finally, the strategies that direct the BLE formulation will be reviewed, specifically, for the EES elements that are most exposed to the MMOD environment.

mmod↗

Atmosphere Modeling and Performance Sensitivity for the Mars Sample Return Earth Entry System

The Capture, Containment, and Return System (CCRS) mission is a key element of the joint NASA-European Space Agency (ESA) planned Mars Sample Return (MSR) Campaign. The CCRS assembled Earth Entry System (EES) will enter the mission’s final segment in its Approach, Entry, Descent, and Landing (AEDL) Phase. The EES AEDL aims to deliver a highly reliable, safe, and accurate return while maintaining strict containment assurance targets established by the campaign. As currently designed, the EES would be the first fully passive sample return capsule with no parachute or onboard control system, prompting a significant effort in Earth atmosphere characterization and modeling. Earth’s atmosphere, specifically winds, have a strong influence on EES flight mechanics and landing footprint during its free fall landing. This paper describes Earth atmosphere modeling, atmosphere characterization, and performance sensitivities incorporated into the teams’s efforts to ensure AEDL success. By utilizing high resolution balloon radiosondes, analyzing wind structural and distributional compositions, and investigating flight mechanics sensitivities, the AEDL atmosphere team has been able to better understand and simulate local wind conditions at the Utah Test and Training Range (UTTR). Utilizing tools such as horizontal turbulent kinetic energy, vertical wind shear, or integrated wind, the team have been able to reveal valuable information about wind profiles in a deeper context than previously conducted, ultimately improving understanding of AEDL flight mechanics sensitivity and EES design.

Kaustubh Ray↗

Software Quality Assurance for High Performance Computing Containers

Software containers are a key channel for delivering portable and reproducible scientific software in high performance computing (HPC) environments. HPC environments are different from other types of computing environments primarily due to usage of the message passing interface (MPI) and drivers for specialized hard- ware to enable distributed computing capabilities. This distinction directly impacts how software containers are built for HPC applications and can complicate software quality assurance efforts including portability and performance. This work introduces a strategy for building containers for HPC applications that adopts layering as a mechanism for software quality assurance. The strategy is demonstrated across three different HPC systems, two of them petaflops scale with entirely different interconnect technologies and/or processor chipsets but running the same container. Performance consequences of the containerization strategy are found to be less than 5-14% while still achieving portable and reproducible containers for HPC systems.

97 MATHEMATICS AND COMPUTING↗

Facility Concepts for Mars Returned Sample Handling

Samples returned from Mars must be held in quarantine until their biological safety has been determined. A significant challenge, unique to NASA's needs, is how to contain the samples (to protect the blaspheme) while simultaneously protecting their pristine nature. This paper presents a comparative analysis of several quarantine facility concepts for handling and analyzing these samples. The considerations in this design analysis include: modes of manipulation; capability for destructive as well as non-destructive testing; avoidance of cross-contamination; linear versus recursive processing; and sample storage and retrieval within a closed system. The ability to rigorously contain biologically hazardous materials has been amply demonstrated by facilities that meet the specifications of the Center for Disease Control Biosafety Level 4. The newly defined Planetary Protection Level Alpha must provide comparable containment while assuring that the samples remain pristine; the latter requirement is based on the need to avoid compromising science analyses by instrumentation of the highest possible sensitivity (among other things this will assure that there is no false positive detection of organisms or organic molecules - a situation that would delay or prevent the release of the samples from quarantine). Protection of the samples against contamination by terrestrial organisms and organic molecules makes a considerable impact upon the sample handling facility. The use of glove boxes appears to be impractical because of their tendency to leak and to surges. As a result, a returned sample quarantine facility must consider the use of automation and remote manipulation to carry out the various functions of sample handling and transfer within the system. The problem of maintaining sensitive and bulky instrumentation under the constraints of simultaneous sample containment and contamination protection also places demands on the architectural configuration of the facility that houses it.

Cohen, Marc M.↗

NRAP-open-IAM: A flexible open-source integrated-assessment-model for geologic carbon storage risk assessment and management

Large-scale implementation of geologic carbon storage (GCS) to help reduce atmospheric greenhouse gas emissions requires stakeholder confidence that injected CO2 will remain contained and that potential subsurface environmental risks are acceptably small and manageable. The U.S. Department of Energy’s National Risk Assessment Partnership (NRAP) has developed an open-source integrated assessment model (NRAP-Open-IAM) to help address questions about a potential GCS site’s ability to effectively contain injected CO 2 and protect groundwater and other overlying environmentally sensitive receptors. NRAP-Open-IAM allows a user to: (1) incorporate relevant site geologic and injection scenario data; (2) characterize important site features and events;(3) couple fast prediction models of various system components of the engineered geologic system; and (4) execute stochastic, dynamic simulation of whole GCS system performance, leakage risk assessment, and uncertainty quantification. NRAP-Open-IAM is available on GitLab (https://gitlab.com/NRAP/OpenIAM), and is accompanied by multiple application examples and detailed user and developer guides.

54 ENVIRONMENTAL SCIENCES↗

An experimental investigation on the CO 2 storage capacity of the composite confining system

Assuring secure containment of stored CO 2 is of paramount importance—for climate change mitigation, for permitting, and for reassuring the public. Regional seals, such as those sealing petroleum accumulations, have proven to be effective for securing CO 2 . However, the goal of permanent sequestration can also be satisfied with “composite confining systems” consisting of multiple, possibly discontinuous flow barriers that, in aggregate, create a system with very high permeability anisotropy and effectively retard the vertical migration of CO 2 . This study focuses on investigating the barrier characteristics necessary for effective containment of CO 2 , using both physical flow experiments and modified invasion percolation simulations. The simulations are calibrated to the physical experiments and are used to further extend the analysis. Results show that for a composite confining system, a) even barriers with low capillary entry pressure contrast to the underlying flow unit can divert rising CO 2 ; b) curved or anticlinal barrier topography can enhance CO 2 trapping; c) fining-upward gradations make little difference to barrier effectiveness or CO 2 retention; d) longer barriers retain more CO 2 regardless of barrier topography. Finally, field-scale simulations have demonstrated the importance of barrier length for increasing CO 2 storage capacity. Furthermore, the results presented can be used to inform the development of new screening criteria for characterization and effectiveness of composite confining systems.

58 GEOSCIENCES↗

NRAP-Open-IAM: FutureGen2 Component Models

This report describes the development and testing of three component models for NRAP-Open-IAM, the National Risk Assessment Partnership’s open-source integrated assessment model. The FutureGen2 Lookup Table Reservoir component model is based on interpolation of data from a set of lookup tables. The lookup tables contain pressures and saturations predicted by multiphase flow simulations performed with a reservoir simulator. The FutureGen2 Above Zone Monitoring Interval (AZMI) component is a surrogate model that can be used to estimate the impact that carbon dioxide (CO 2 ) and brine leaks from the CO 2 storage reservoir at the FutureGen 2.0 site might have had on overlying aquifers or monitoring units were a leak to occur. The model estimates the size of “impact plumes” according to five metrics: pH, Total Dissolved Solids (TDS), pressure, dissolved CO 2 and temperature. The FutureGen2 Aquifer component is similar, but is limited to four metrics: pH, Total Dissolved Solids (TDS), pressure, and dissolved CO 2 . The input parameters for each model are the same, but the Aquifer component is applicable to depths between 100 m and 700 m and the AZMI component is applicable from depths between 700 m and 1050 m.

42 ENGINEERING↗

Workflow for Process Automation of Soil Gas Results from an Automated Soil Gas-Sampling System for Application in Carbon Storage Projects

Conference presentation at Geoconvention, Calgary, Alberta, Canada, May 12–14, 2025. The Energy & Environmental Research Center (EERC) developed an automated workflow for processing soil gas measurements collected from the automated soil gas-sampling systems deployed across the project site. Raw soil gas measurements are collected from each station every 4 hours and automatically uploaded to a cloud database. The workflow begins by writing code to download the data to a workstation automatically, then the data are published to an online dashboard that visualizes the measurements in time-series plots and a process-based decision-making framework. This automated workflow accelerates the time from data acquisition to decision-making. It supports carbon storage project operators by preparing and delivering a live, standardized dataset for quick analysis and source attribution to provide assurance of containment and overall permit compliance.

02 PETROLEUM↗

Mars Sample Return – An Overview of the Capture, Containment and Return System

The Mars Sample Return campaign aims at bringing back soil, rock and atmospheric samples from Mars to Earth to answer key questions about Mars’ biological evolution by means of four missions. The first one, Mars 2020, landed on the red planet on February 18, 2021 and has to date collected a number of samples through the Perseverance rover. The three subsequent missions will recover the sample tubes, launch them into Mars orbit and transport them back to Earth. These missions are currently in the planning and design stages of development and represent an international effort comprising NASA, ESA and many industry partners. The work presented here provides an overview of the current design and concept of operations of the NASA-provided Capture, Containment, and Return System (CCRS), which is the payload of the ESA-provided Earth Return Orbiter (ERO). ERO will rendezvous with the orbiting samples and CCRS will capture them, contain them and robotically insert them into a capsule that will return the samples to Earth, the Earth Entry System (EES). Three days before arrival on Earth, CCRS will release the EES, which will fly through space, enter Earth’s atmosphere, descend on a well-defined trajectory and safely land at the Utah Test and Training Range. The decision to implement Mars Sample Return will not be finalized until NASA’s completion of the National Environmental Policy Act process. This document is being made available for information purposes only.

Mars Sample Return↗

Workflow for Process Automation of Soil Gas Results from an Automated Soil Gas-Sampling System for Application in Carbon Storage Projects

Extended abstract for Geoconvention, Calgary, Alberta, Canada, May 12–14, 2025. The Energy & Environmental Research Center (EERC) developed an automated workflow for processing soil gas measurements collected from the automated soil gas-sampling systems deployed across the project site. Raw soil gas measurements are collected from each station every 4 hours and automatically uploaded to a cloud database. The workflow begins by writing code to download the data to a workstation automatically, then the data are published to an online dashboard that visualizes the measurements in time-series plots and a process-based decision-making framework. This automated workflow accelerates the time from data acquisition to decision-making. It supports carbon storage project operators by preparing and delivering a live, standardized dataset for quick analysis and source attribution to provide assurance of containment and overall permit compliance.

02 PETROLEUM↗

Analysis of SPAR 8 single-axis levitation experiment

The melting and resolidification of SPAR 8 payload melting and resolidification of a glass specimen from the in a containerless condition and the retrieval and examination of the specimen from the. The absence of container contact was assured by use of a single-axis acoustic levitation system. However, the sample contacted a wire cage after being held without container contact by the acoustic field for only approximately 87 seconds. At this time, the sample was still molten and, therefore, flowed aroung the wire and continued to adhere to it. An analysis of why the sample did not remain levitated free of container contact is presented. The experiment is described, and experimental observations are discussed and analyzed.

Rush, J. E.↗

Recommendations on Evidence and Process for Certification of Learning-enabled Components in Aerospace Systems

This report primarily identifies a collection of relevant and necessary evidence for assurance of machine learnt components (MLCs)—also known as learning-enabled components—integrated into aircraft systems, and gives preliminary suggestions on the elements of a certification process that invoke the identified evidence. The main focus is on feedforward neural networks that are static and trained offline through supervised learning. A brief background on the generic elements of the lifecycle of an MLC is given to contextualize the assurance considerations and, consequently, the evidence that is relevant and necessary to support certification. At the level of an MLC, those considerations relate to: (i) the consistency and correctness of MLC contributions to system functions in the context of a validated functional intent; and (ii) the absence of MLC contributions to aircraft-level failure conditions. At an ML model level, confidence in model and data properties contribute to assurance of the containing MLC, in particular: (a) generalizability and robustness of models, in the presence of inputs not previously seen during training, disturbances to inputs, and unexpected inputs; and (b) valid data, i.e., data that are at least representative, relevant, complete, and accurate. Evidence for the above span the elements of the ML lifecycle, and includes, at a minimum, lifecycle artifacts that pertain to: (1) properties of requirements capturing functional intent, safety constraints, and aspects of the intended use and operating environment; (2) model performance, model complexity and design, and algorithm choice; (3) achievement of required performance at the levels of a trained model during model development, a trained model after model development is complete, and a trained model that is transformed into an executable equivalent; (4) model implementation aspects necessary for transforming a trained model into the executable equivalent; (5) integration of the executable trained model into the containing MLC, and eventually the larger system; and, (6) lastly, the verification and validation (V&V) of each of the above. Such V&V lifecycle artifacts themselves include: aspects of coverage, e.g., of various levels of requirements by the input space of the model and the data; traceability (where applicable); application of formal methods for property specification, analysis, and checking. Examples of evidence generation methods and tools further ground the discussion on what constitutes evidence, and the contribution to assurance during certification. The identified assurance considerations and supporting evidence is not a comprehensive set. Additionally, neither what should be considered as sufficient evidence relative to the assigned criticality of an MLC, nor how criticality ought to be determined and adjusted, have been considered in this report. However, suggestions are made for potential activities of the ML lifecycle that are aimed at providing confidence that an MLC can be relied upon when integrated into its containing (aircraft) system. Those activities are proposed as candidate elements of a certification process for MLCs. The main purpose of this report to inform regulatory guidance and consensus standards that may be used to meet the safety intent of the applicable regulations.

Aviation safety↗

QA/QC-ed Groundwater Level Time Series in PLM-1 and PLM-6 Monitoring Wells, East River, Colorado (2016-2022)

This data set contains QA/QC-ed (Quality Assurance and Quality Control) water level data for the PLM1 and PLM6 wells. PLM1 and PLM6 are location identifiers used by the Watershed Function SFA project for two groundwater monitoring wells along an elevation gradient located along the lower montane life zone of a hillslope near the Pumphouse location at the East River Watershed, Colorado, USA. These wells are used to monitor subsurface water and carbon inventories and fluxes, and to determine the seasonally dependent flow of groundwater under the PLM hillslope. The downslope flow of groundwater in combination with data on groundwater chemistry (see related references) can be used to estimate rates of solute export from the hillslope to the floodplain and river. QA/QC analysis of measured groundwater levels in monitoring wells PLM-1 and PLM-6 included identification and flagging of duplicated values of timestamps, gap filling of missing timestamps and water levels, removal of abnormal/bad and outliers of measured water levels. The QA/QC analysis also tested the application of different QA/QC methods and the development of regular (5-minute, 1-hour, and 1-day) time series datasets, which can serve as a benchmark for testing other QA/QC techniques, and will be applicable for ecohydrological modeling. The package includes a Readme file, one R code file used to perform QA/QC, a series of 8 data csv files (six QA/QC-ed regular time series datasets of varying intervals (5-min, 1-hr, 1-day) and two files with QA/QC flagging of original data), and three files for the reporting format adoption of this dataset (InstallationMethods, file level metadata (flmd), and data dictionary (dd) files).QA/QC-ed data herein were derived from the original/raw data publication available at Williams et al., 2020 (DOI: 10.15485/1818367). For more information about running R code file (10.15485_1866836_QAQC_PLM1_PLM6.R) to reproduce QA/QC output files, see README (QAQC_PLM_readme.docx). This dataset replaces the previously published raw data time series, and is the final groundwater data product for the PLM wells in the East River. Complete metadata information on the PLM1 and PLM6 wells are available in a related dataset on ESS-DIVE: Varadharajan C, et al (2022). https://doi.org/10.15485/1660962. These data products are part of the Watershed Function Scientific Focus Area collection effort to further scientific understanding of biogeochemical dynamics from genome to watershed scales. 2022/09/09 Update: Converted data files using ESS-DIVE’s Hydrological Monitoring Reporting Format. With the adoption of this reporting format, the addition of three new files (v1_20220909_flmd.csv, V1_20220909_dd.csv, and InstallationMethods.csv) were added. The file-level metadata file (v1_20220909_flmd.csv) contains information specific to the files contained within the dataset. The data dictionary file (v1_20220909_dd.csv) contains definitions of column headers and other terms across the dataset. The installation methods file (InstallationMethods.csv) contains a description of methods associated with installation and deployment at PLM1 and PLM6 wells. Additionally, eight data files were re-formatted to follow the reporting format guidance (er_plm1_waterlevel_2016-2020.csv, er_plm1_waterlevel_1-hour_2016-2020.csv, er_plm1_waterlevel_daily_2016-2020.csv, QA_PLM1_Flagging.csv, er_plm6_waterlevel_2016-2020.csv, er_plm6_waterlevel_1-hour_2016-2020.csv, er_plm6_waterlevel_daily_2016-2020.csv, QA_PLM6_Flagging.csv). The major changes to the data files include the addition of header_rows above the data containing metadata about the particular well, units, and sensor description. 2023/01/18 Update: Dataset updated to include additional QA/QC-ed water level data up until 2022-10-12 for ER-PLM1 and 2022-10-13 for ER-PLM6. Reporting format specific files (v2_20230118_flmd.csv, v2_20230118_dd.csv, v2_20230118_InstallationMethods.csv) were updated to reflect the additional data. R code file (QAQC_PLM1_PLM6.R) was added to replace the previously uploaded HTML files to enable execution of the associated code. R code file (QAQC_PLM1_PLM6.R) and ReadMe file (QAQC_PLM_readme.docx) were revised to clarify where original data was retrieved from and to remove local file paths.

54 ENVIRONMENTAL SCIENCES↗

Introduction to Mars Sampling Handling Workshop Series. Workshop on Life Detection: Issues and Topics

Before martian soil and rock samples can be distributed to the research community, the returned materials will initially be quarantined and examined in a proposed BSL-4 containment facility to assure that no putative martian microorganisms or attendant potential biohazards exist. During the initial quarantine, state-of-the-art life detection and biohazard testing of the returned martian samples will be conducted. Life detection, as defined here in regard to Mars sample return missions, is the detection of living organisms and/or materials that have been derived from living organisms that may be present in the sample.

Rummel, John D.↗

Product Assurance for Spaceflight Hardware

This report contains information about the tasks I have completed and the valuable experience I have gained at NASA. The report is divided into two different sections followed by a program summary sheet. The first section describes the two reports I have completed for the Office of Mission Assurance (OMA). I describe the approach and the resources and facilities used to complete each report. The second section describes my experience working in the Receipt Inspection/Quality Assurance Lab (RI/QA). The first report described is a Product Assurance Plan for the Gas Permeable Polymer Materials (GPPM) mission. The purpose of the Product Assurance Plan is to define the various requirements which are to be met through completion of the GPPM mission. The GPPM experiment is a space payload which will be flown in the shuttle's SPACEHAB module. The experiment will use microgravity to enable production of complex polymeric gas permeable materials. The second report described in the first section is a Fracture Analysis for the Mir Environmental Effects Payload (MEEP). The Fracture Analysis report is a summary of the fracture control classifications for all structural elements of the MEEP. The MEEP hardware consists of four experiment carriers, each of which contains an experiment container holding a passive experiment. The MEEP hardware will be attached to the cargo bay of the space shuttle. It will be transferred by Extravehicular Activity and mounted on the Mir space station. The second section of this report describes my experiences in the RVQA lab. I listed the different equipment I used at the lab and their functions. I described the extensive inspection process that must be completed for spaceflight hardware. Included, at the end of this section, are pictures of most of the equipment used in the lab. There is a summary sheet located at the end of this report. It briefly describes the valuable experience I have gained at NASA this summer and what I will be able to take with me as I return to college. I briefly discuss the experiences I mentioned in the previous three paragraphs along with training classes I attended and courses I completed at the Learning Lab.

Monroe, Mike↗