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User Guidelines and Best Practices for CASL VUQ Analysis Using Dakota

Sandia’s Dakota software (available at http://dakota.sandia.gov) supports science and engineering transformation through advanced exploration of simulations. Specifically it manages and analyzes ensembles of simulations to provide broader and deeper perspective for analysts and decision makers. This enables them to enhance understanding of risk, improve products, and assess simulation credibility. In its simplest mode, Dakota can automate typical parameter variation studies through a generic interface to a physics-based computational model. This can lend efficiency and rigor to manual parameter perturbation studies already being conducted by analysts. However, Dakota also delivers advanced parametric analysis techniques enabling design exploration, optimization, model calibration, risk analysis, and quantification of margins and uncertainty with such models. It directly supports verification and validation activities. Dakota algorithms enrich complex science and engineering models, enabling an analyst to answer crucial questions of - Sensitivity: Which are the most important input factors or parameters entering the simulation, and how do they influence key outputs?; Uncertainty: What is the uncertainty or variability in simulation output, given uncertainties in input parameters? How safe, reliable, robust, or variable is my system? (Quantification of margins and uncertainty, QMU); Optimization: What parameter values yield the best performing design or operating condition, given constraints? Calibration: What models and/or parameters best match experimental data? In general, Dakota is the Consortium for Advanced Simulation of Light Water Reactors (CASL) delivery vehicle for verification, validation, and uncertainty quantification (VUQ) algorithms. It permits ready application of the VUQ methods described above to simulation codes by CASL researchers, code developers, and application engineers.

97 MATHEMATICS AND COMPUTING↗

Exascale and Beyond: Configuring, Reasoning, Scaling. Report of the 2011 Workshop on Architectures II: Exascale and Beyond, held August 8-10, Albuquerque, N.M.

The push toward exascale computing (1) and beyond is torn between contradictory and possibly incompatible goals. On the one hand, one wants a system that will be available within a short span of time, on a relatively small development budget, and with the least changes possible to the current software stack. On the other hand, one wants a system that is orders of magnitude more efficient in its energy consumption. An exascale system could be as different from current systems as scalable parallel systems were from vector machines at the time of the last major transition in the field, but the amount of application software developed at DOE in the last decades makes it undesirable to take a “clean sheet of paper” approach, if at all possible. Furthermore, one wishes to explore and develop distinct exascale architectures to reduce risk while maintaining some unity so that application codes easily port among them. Finally, the design of an exascale system may involve a large number of vendors, some of which have limited experience in the field of High-Performance Computing (HPC). A proper integration of these multiple contributions requires a proper definition of many new interfaces, as well as consistent design principles for the handling of cross-cutting issues such as resilience, performance, and power management.

97 MATHEMATICS AND COMPUTING↗

Automated Thermal Image Processing for Detection and Classification of Birds and Bats (FY2012 Annual Report)

Surveying wildlife at risk from offshore wind energy development is difficult and expensive. Infrared video can be used to record birds and bats that pass through the camera view, but it is also time consuming and expensive to review video and determine what was recorded. We proposed to conduct algorithm and software development to identify and to differentiate thermally detected targets of interest that would allow automated processing of thermal image data to enumerate birds, bats, and insects. During FY2012 we developed computer code within MATLAB to identify objects recorded in video and extract attribute information that describes the objects recorded. We tested the efficiency of track identification using observer-based counts of tracks within segments of sample video. We examined object attributes, modeled the effects of random variability on attributes, and produced data smoothing techniques to limit random variation within attribute data. We also began drafting and testing methodology to identify objects recorded on video. We also recorded approximately 10 hours of infrared video of various marine birds, passerine birds, and bats near the Pacific Northwest National Laboratory (PNNL) Marine Sciences Laboratory (MSL) at Sequim, Washington. A total of 6 hours of bird video was captured overlooking Sequim Bay over a series of weeks. An additional 2 hours of video of birds was also captured during two weeks overlooking Dungeness Bay within the Strait of Juan de Fuca. Bats and passerine birds (swallows) were also recorded at dusk on the MSL campus during nine evenings. An observer noted the identity of objects viewed through the camera concurrently with recording. These video files will provide the information necessary to produce and test software developed during FY2013. The annotation will also form the basis for creation of a method to reliably identify recorded objects.

Bats↗

The Multi-Isotope Process (MIP) Monitor Project: FY12 Progress and Accomplishments

The Multi-Isotope Process (MIP) Monitor, being developed at Pacific Northwest National Laboratory (PNNL), provides an efficient approach to monitoring the process conditions in reprocessing facilities in support of the goal of "...(minimization of) the risks of nuclear proliferation and terrorism." The MIP Monitor measures distributions of a suite of indicator (radioactive) isotopes present within product and waste streams of a nuclear reprocessing facility. These indicator isotopes are monitored on-line by gamma spectrometry and compared, in near-real-time, to spectral patterns representing "normal" process conditions using multivariate pattern recognition software. The monitor utilizes this multivariate analysis and gamma spectroscopy of reprocessing streams to detect small changes in the gamma spectrum, which may indicate changes in process conditions. Multivariate analysis methods common in chemometrics, such as principal component analysis (PCA) and partial least squares regression (PLS), act as pattern recognition techniques, which can detect small deviations from the expected, nominal condition. By targeting multiple gamma-emitting indicator isotopes, the MIP Monitor approach is compatible with the use of small, portable, relatively high-resolution gamma detectors that may be easily deployed throughout an existing facility. The automated multivariate analysis can provide a level of data obscurity, giving a built-in information barrier to protect sensitive or proprietary operational data. Proof-of-concept simulations and experiments have been performed in previous years to demonstrate the validity of this tool in a laboratory setting. Development of the MIP Monitor approach continues to evaluate the efficacy of the monitor for automated, real-time or near-real-time application. This report details follow-on research and development efforts sponsored by the U.S. Department of Energy Fuel Cycle Research and Development related to the MIP Monitor for fiscal year 2012 (FY12).

fuel characterization↗

Regional-scale fault-to-structure earthquake simulations with the EQSIM framework: Workflow maturation and computational performance on GPU-accelerated exascale platforms

Continuous advancements in scientific and engineering understanding of earthquake phenomena, combined with the associated development of representative physics-based models, is providing a foundation for high-performance, fault-to-structure earthquake simulations. However, regional-scale applications of high-performance models have been challenged by the computational requirements at the resolutions required for engineering risk assessments. The EarthQuake SIMulation (EQSIM) framework, a software application development under the US Department of Energy (DOE) Exascale Computing Project, is focused on overcoming the existing computational barriers and enabling routine regional-scale simulations at resolutions relevant to a breadth of engineered systems. This multidisciplinary software development—drawing upon expertise in geophysics, engineering, applied math and computer science—is preparing the advanced computational workflow necessary to fully exploit the DOE’s exaflop computer platforms coming online in the 2023 to 2024 timeframe. Achievement of the computational performance required for high-resolution regional models containing upward of hundreds of billions to trillions of model grid points requires numerical efficiency in every phase of a regional simulation. This includes run time start-up and regional model generation, effective distribution of the computational workload across thousands of computer nodes, efficient coupling of regional geophysics and local engineering models, and application-tailored highly efficient transfer, storage, and interrogation of very large volumes of simulation data. This article summarizes the most recent advancements and refinements incorporated in the workflow design for the EQSIM integrated fault-to-structure framework, which are based on extensive numerical testing across multiple graphics processing unit (GPU)-accelerated platforms, and demonstrates the computational performance achieved on the world’s first exaflop computer platform through representative regional-scale earthquake simulations for the San Francisco Bay Area in California, USA.

58 GEOSCIENCES↗

Path Toward a Unifid Geometry for Radiation Transport

The Direct Accelerated Geometry for Radiation Analysis and Design (DAGRAD) element of the RadWorks Project under Advanced Exploration Systems (AES) within the Space Technology Mission Directorate (STMD) of NASA will enable new designs and concepts of operation for radiation risk assessment, mitigation and protection. This element is designed to produce a solution that will allow NASA to calculate the transport of space radiation through complex computer-aided design (CAD) models using the state-of-the-art analytic and Monte Carlo radiation transport codes. Due to the inherent hazard of astronaut and spacecraft exposure to ionizing radiation in low-Earth orbit (LEO) or in deep space, risk analyses must be performed for all crew vehicles and habitats. Incorporating these analyses into the design process can minimize the mass needed solely for radiation protection. Transport of the radiation fields as they pass through shielding and body materials can be simulated using Monte Carlo techniques or described by the Boltzmann equation, which is obtained by balancing changes in particle fluxes as they traverse a small volume of material with the gains and losses caused by atomic and nuclear collisions. Deterministic codes that solve the Boltzmann transport equation, such as HZETRN [high charge and energy transport code developed by NASA Langley Research Center (LaRC)], are generally computationally faster than Monte Carlo codes such as FLUKA, GEANT4, MCNP(X) or PHITS; however, they are currently limited to transport in one dimension, which poorly represents the secondary light ion and neutron radiation fields. NASA currently uses HZETRN space radiation transport software, both because it is computationally efficient and because proven methods have been developed for using this software to analyze complex geometries. Although Monte Carlo codes describe the relevant physics in a fully three-dimensional manner, their computational costs have thus far prevented their widespread use for analysis of complex CAD models, leading to the creation and maintenance of toolkit-specific simplistic geometry models. The work presented here builds on the Direct Accelerated Geometry Monte Carlo (DAGMC) toolkit developed for use with the Monte Carlo N-Particle (MCNP) transport code. The workflow for achieving radiation transport on CAD models using MCNP and FLUKA has been demonstrated and the results of analyses on realistic spacecraft/habitats will be presented. Future work is planned that will further automate this process and enable the use of multiple radiation transport codes on identical geometry models imported from CAD. This effort will enhance the modeling tools used by NASA to accurately evaluate the astronaut space radiation risk and accurately determine the protection provided by as-designed exploration mission vehicles and habitats

Lee, Kerry↗

Sequential Design of Experiments to Maximize Learning from Carbon Capture Pilot Plant Testing

Pilot plant test campaigns can be expensive and time-consuming. Therefore, it is of interest to maximize the amount of learning and the efficiency of the test campaign given the limited number of experiments that can be conducted. This work investigates the use of sequential design of experiments (SDOE) to overcome these challenges by demonstrating its usefulness for a recent solvent-based CO2 capture plant test campaign. Unlike traditional design of experiments methods, SDOE regularly uses information from ongoing experiments to determine the optimum locations in the design space for subsequent runs within the same experiment. However, there are challenges that need to be addressed, including reducing the high computational burden to efficiently update the model, and the need to incorporate the methodology into a computational tool. We address these challenges by applying SDOE in combination with a software tool, the Framework for Optimization, Quantification of Uncertainty and Surrogates (FOQUS) (Miller et al., 2014a, 2016, 2017). The results of applying SDOE on a pilot plant test campaign for CO2 capture suggests that relative to traditional design of experiments methods, SDOE can more effectively reduce the uncertainty of the model, thus decreasing technical risk. Future work includes integrating SDOE into FOQUS and using SDOE to support additional large-scale pilot plant test campaigns.

20 FOSSIL-FUELED POWER PLANTS↗

PVMapper: Report on the Second Public Opinion Survey

This report has been developed as an integral part of the PVMapper project, funded by the U.S. Department of Energy’s Office of Energy Efficiency and Renewable Energy’s SunShot program. The objective of the SunShot program is to reduce the total costs of solar energy systems. The scope of PVMapper is to develop a geographic information system (GIS) based project planning tool to identify optimal utility-scale solar facility sites. The specific objectives of the project are to 1) develop the software on an open-source platform; 2) integrate the appropriate data sets and GIS layers; 3) include a measure of social risk and public acceptance; 4) enable customization of variable weights; 5) provide a free and accessible platform for software download; and 6) provide a sustainability plan to ensure future relevance of the software. When completed, PVMapper is intended to be used by solar developers, Authorities Having Jurisdiction (AHJs), and other interested parties. This project supports SunShot’s objective by reducing the non-hardware balance of system costs (“soft costs”) for utility-scale solar project development. In order to accomplish the third project objective – including a measure of social risk and public acceptance within PVMapper – the project team has developed a time-series public opinion survey, administered yearly over the course of the three-year project. This report highlights the results and preliminary analyses from the second survey in this series. While the results of this survey are valuable to both PVMapper and future utility-scale solar development, the time-series design is extremely important. The completion of the series enables the extension of the dataset to much richer information. For example, the research team altered this iteration to sharpen the focus on specific topics (those posing potentially higher risks) and target specific locations in the oversample (such as communities near existing facilities). Using similar approaches for each iteration leads to an increasingly greater amount of detail regarding siting risks. The need for this extended dataset to aid in siting utility-scale solar projects is evident, as developers continue to scale back initial plans due to unidentified or incorrectly quantified social risks. It should be noted that this report provides the complete dataset from the survey, encompassing the wide-ranging responses from all of the survey questions. Although the methods used to integrate these data into PVMapper’s siting algorithms is not the purpose of this report, allusions to integration can be found in the discussions surrounding the design of questions and types of data to be used.

14 SOLAR ENERGY↗

Importance of Requirements Analysis & Traceability to Improve Software Quality and Reduce Cost and Risk

The goal of this paper is to emphasize the importance of developing complete and unambiguous requirements early in the project cycle (prior to Preliminary Design Phase). Having a complete set of requirements early in the project cycle allows sufficient time to generate a traceability matrix. Requirements traceability and analysis are the key elements in improving verification and validation process, and thus overall software quality. Traceability can be most beneficial when the system changes. If changes are made to high-level requirements it implies that low-level requirements need to be modified. Traceability ensures that requirements are appropriately and efficiently verified at various levels whereas analysis ensures that a rightly interpreted set of requirements is produced.

Kapoor, Manju M.↗

SMART-COM – Scalable Multi-Agent Adaptive Resolution Tools for Collaborative Outage Management

The purpose of this grant was to conduct scientific research and prototype applications to support NPP outage staff in their adaptive decision-making in efficient scheduling and resource allocation while preventing violation of safety technical specifications. The project contributed to scientific knowledge and engineering methods in (1) user interface design, (2) scheduling optimization and risk estimation, and (2) natural language processing that would benefit the nuclear power plants in minimizing schedule overruns and even unexpected shutdowns. The research team conducted site visits at a test reactor facility and an operating nuclear power plant to gather necessary information and inputs for research and development of a software application to support NPP staff in executing their outages. The final software application consisted of three modules. First, the natural language processing module supports interactive processing of technical documentation to build a database for outage staff to query non-permissible actions on system components. This module can alleviate outage staff from reviewing extensive documentation and minimize violation of technical specifications, especially in time-sensitive situations. Second, the schedule optimization module schedules outage activities and compute risk indices that outperform existing software and current practice. This module can reduce completion time of an outage that typically have too many activities for human to optimize based on current practice that does not apply the latest operations research. Finally, the visualization module presents progress and risk information of the overall outage and individual activities, as well as enabling access to the natural language processing and schedule optimization modules. This module can provide outage staff with situation awareness that are necessary to make risk-informed decisions in response to unexpected events during the execution of an outage.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Influence of local capillary trapping on containment system effectiveness

Immobilization of CO 2 injected into deep subsurface storage reservoirs is a critical component of risk assessment for geologic CO 2 storage (GCS). Local capillary trapping (LCT) is a recently established mode of immobilization that arises when CO 2 migrates due to buoyancy through heterogeneous storage reservoirs. This project sought to assess the amount and extent of LCT expected in storage formations under a range of injection conditions, and to confirm the persistence of LCT if the seal overlying the reservoir were to lose its integrity. Numerical simulation using commercial reservoir simulation software was conducted to assess the influence of injection. Laboratory experiments, modeling and numerical simulation were conducted to assess the effect of compromised seal integrity. Bench-scale (0.6 m by 0.6 m by 0.03 m) experiments with surrogate fluids provided the first empirical confirmation of the key concepts underlying LCT: accumulation of buoyant nonwetting phase at above residual saturations beneath capillary barriers in a variety of structures, which remains immobile under normal capillary pressure gradients. Immobilization of above-residual saturations is a critical distinction between LCT and the more familiar “residual saturation trapping.” To estimate the possible extent of LCT in a storage reservoir an algorithm was developed to identify all potential local traps, given the spatial distribution of capillary entry pressure in the reservoir. The algorithm assumes that the driving force for CO 2 migration can be represented as a single value of “critical capillary entry pressure” P c,entry crit , such that cells with capillary entry pressure greater/less than P c,entry crit act as barriers/potential traps during CO 2 migration. At intermediate values of P c,entry crit , the barrier regions become more laterally extensive in the reservoir, approaching a percolation threshold while non-barrier regions remain numerous. The maximum possible extent of LCT thus occurs at P c,entry crit near this threshold. Testing predictions of this simple algorithm against full-physics simulations of buoyancy-driven CO 2 migration support the concept of critical capillary entry pressure. However, further research is needed to determine whether a single value of critical capillary entry pressure always applies and how that value can be determined a priori. Simulations of injection into high-resolution (cells 0.3 m on a side) 2D and 3D heterogeneous domains show two characteristic behaviors. At small gravity numbers (vertical flow velocity much less than horizontal flow velocity) the CO 2 fills local traps as well as regions that would act as local barriers if CO 2 were moving only due to buoyancy. When injection ceases, the CO 2 migrates vertically to establish large saturations within local traps and residual saturation elsewhere. At large gravity numbers, the CO 2 invades a smaller portion of the perforated interval. Within this smaller swept zone the local barriers are not invaded, but local traps are filled to large saturation during injection and remain during post-injection gravity-driven migration. The small gravity number behavior is expected in the region within 100 m of a vertical injection well at anticipated rates of injection for commercial GCS. Simulations of leakage scenarios (through-going region of large permeability imposed in overlying seal) indicate that LCT persists (i.e. CO 2 remains held in a large fraction of the local iv traps) and the persistence is independent of injection rate during storage. Simulations of leakage for the limiting case of CO 2 migrating vertically from an areally extensive emplacement in the lower portion of a reservoir showed similar strong persistence of LCT. This research has two broad implications for GCS. The first is that LCT can retain a significant fraction of the CO 2 stored in a reservoir – above and beyond the residual saturation -- if the overlying seal were to fail. Thus frameworks for risk assessment should be extended to account for LCT. The second implication is that compared to pressure driven flow in reservoirs, CO 2 migration and trapping behave in a qualitatively different manner in heterogeneous reservoirs when buoyancy is the dominant driving force for flow. Thus simulations of GCS that neglect capillary heterogeneity will fail to capture important features of the CO 2 plume. While commercial reservoir simulation software can account for fine scale capillary heterogeneity, it has not been designed to work efficiently with such domains, and no simulators can handle fine-scale resolution throughout the reservoir. A possible way to upscale the migration and trapping is to apply an “effective residual saturation” to coarse-scale grids. While the extent of overall immobilization can be correlated in this way, all coarser grids failed to capture the distance traveled by the migrating CO 2 for large gravity number. Thus it remains unclear how best to account for LCT in the routine simulation work-flow that will be needed for large-scale GCS. Alternatives meriting investigation include streamline methods, reduced-physics proxies (e.g. particle tracking), and biased invasion percolation algorithms, which are based on precisely the capillary heterogeneity essential for LCT.

58 GEOSCIENCES↗

An Upgrade of the Imaging for Hypersonic Experimental Aeroheating Testing (IHEAT) Software

The Imaging for Hypersonic Experimental Aeroheating Testing (IHEAT) code is used at NASA Langley Research Center to analyze global aeroheating data on wind tunnel models tested in the Langley Aerothermodynamics Laboratory. One-dimensional, semi-infinite heating data derived from IHEAT are used to design thermal protection systems to mitigate the risks due to the aeroheating loads on hypersonic vehicles, such as re-entry vehicles during descent and landing procedures. This code was originally written in the PV-WAVE programming language to analyze phosphor thermography data from the two-color, relativeintensity system developed at Langley. To increase the efficiency, functionality, and reliability of IHEAT, the code was migrated to MATLAB syntax and compiled as a stand-alone executable file labeled version 4.0. New features of IHEAT 4.0 include the options to batch process all of the data from a wind tunnel run, to map the two-dimensional heating distribution to a three-dimensional computer-aided design model of the vehicle to be viewed in Tecplot, and to extract data from a segmented line that follows an interesting feature in the data. Results from IHEAT 4.0 were compared on a pixel level to the output images from the legacy code to validate the program. The differences between the two codes were on the order of 10-5 to 10-7. IHEAT 4.0 replaces the PV-WAVE version as the production code for aeroheating experiments conducted in the hypersonic facilities at NASA Langley.

Mason, Michelle L.↗

MO-FG-CAMPUS-TeP1-03: Pre-Treatment Surface Imaging Based Collision Detection

Purpose: Modern radiotherapy increasingly employs large immobilization devices, gantry attachments, and couch rotations for treatments. All of which raise the risk of collisions between the patient and the gantry / couch. Collision detection is often achieved by manually checking each couch position in the treatment room and sometimes results in extraneous imaging if collisions are detected after image based setup has begun. In the interest of improving efficiency and avoiding extra imaging, we explore the use of a surface imaging based collision detection model. Methods: Surfaces acquired from AlignRT (VisionRT, London, UK) were transferred in wavefront format to a custom Matlab (Mathworks, Natick, MA) software package (CCHECK). Computed tomography (CT) scans acquired at the same time were sent to CCHECK in DICOM format. In CCHECK, binary maps of the surfaces were created and overlaid on the CT images based on the fixed relationship of the AlignRT and CT coordinate systems. Isocenters were added through a graphical user interface (GUI). CCHECK then compares the inputted surfaces to a model of the linear accelerator (linac) to check for collisions at defined gantry and couch positions. Note, CCHECK may be used with or without a CT. Results: The nominal surface image field of view is 650 mm × 900 mm, with variance based on patient position and size. The accuracy of collision detections is primarily based on the linac model and the surface mapping process. The current linac model and mapping process yield detection accuracies on the order of 5 mm, assuming no change in patient posture between surface acquisition and treatment. Conclusions: CCHECK provides a non-ionizing method to check for collisions without the patient in the treatment room. Collision detection accuracy may be improved with more robust linac modeling. Additional gantry attachments (e.g. conical collimators) can be easily added to the model.

60 APPLIED LIFE SCIENCES↗

Collaborative Systems Engineering in the Ascent Abort-2 Crew Module/Separation Ring Project

Generally speaking, systems engineering (SE) tool-sets face a dilemma balancing power and accessibility. High-powered SE tools (MagicDraw, Cradle, Core, etc.) tend to be specialized and are available only to highly trained Systems Engineers, and/or through the use of a 'back room' developer team making the output products available to the broader team. On the other hand, highly accessible tools (MS Word, Excel, etc.) do not have the power to implement SE in a rigorous manner. NASA has to test all aspects of the new human-rated Orion Multi-Purpose Crew Vehicle spacecraft prior to its first crewed mission. The test program includes uncrewed launch abort flight tests to demonstrate the capability to save the crew in the event that a launch failure occurs. Orion's second abort flight test will be a low-altitude flight test known as "Ascent Abort 2 (AA-2)." This test is currently scheduled to be carried out at Cape Canaveral Air Force Station's Space Launch Complex 46 (SLC-46) in Florida in 2019. NASA's in-house AA-2 Crew Module and Separation Ring (CSR) Team is producing the crew module and separation ring. Operating jointly as both an Advanced Exploration Systems (AES) Project and an Orion Project, the CSR project charter includes development of innovative, streamlined and generally more efficient practices for creation of flight hardware and software. One result of this tasking has been development of a collaborative and data-centric systems engineering environment within the team's shared web environment (Microsoft SharePoint). Through the use of built-in, 'out of the box capabilities' present in MS SharePoint, the CSR Systems Engineering team has created (with some limited developer support) a data-centric architecture for the project's SE implementation, including functional and interface analysis, requirements development and management, risk management, verification planning and management, test results, and end item management. Data elements are linked between data structures so as to define and control relationships between item types, link requirements to parents and children, and link tests to the requirements that they verify. The overall project team integration is increased by also linking SE content to project management content over the project life cycle, including team communication, action items, configuration management, decisional and meeting materials, and life cycle reviews. This presentation will provide an overview of the collaborative SE environment, showing how it provides the power for a number of SE tasks while still providing the accessibility and transparency to allow the full project team to collaborate and succeed. Given the project phase, we'll be able to present a nearly full lifecycle discussion, from concept through verification and approaching delivery.

Systems Engineering environments↗

The Ejectable Data Recorder: A Lean, Risk-Informed Approach for Hardware Development

NASA is developing the Orion spacecraft to transport crew from the Earth to the Moon as part of the Artemis series of missions. To provide a crew escape capability from pre-launch through ascent, the Orion vehicle is equipped with a Launch Abort System (LAS), built by Lockheed Martin, which pulls the capsule away from the launch vehicle in the event of an abort scenario. The Ascent Abort 2 (AA-2) test flight occurred on July 2, 2019,and tested a production version of the LAS to ensure that it can operate as intended, and to collect a large data set from hundreds of sensors on the vehicle to support Orion flight certification. In the original AA-2 architecture, a single-string set of communications antennas on the LAS would downlink all of the in-flight test data to ground stations. However, that communications architecture was predicted to have data dropouts during abort and jettison of the LAS, and would not support data transmission at all after LAS jettison. As a result, a comprehensive trade study was completed, yielding the addition of antennas on the crew module (CM), a buffer/rebroadcast capability for key portions of the flight, and an ejectable data recorder (EDR) subsystem. This EDR subsystem would serve as a backup to the radio frequency (RF) communications system, and would be non-flight critical, providing a unique capability that enabled management to take a different approach with the hardware and software development. The Crew Module and Separation Ring were developed as “Class 1”Flight Hardware, albeit with some tailoring approaches to enable efficiencies. The Class 1 designation requires full rigor for flight hardware and software, documenting everything that happens to a piece of hardware from procurement through disposal, requiring a full spectrum of acceptance tests, and the highest rigor of quality assurance processes. At the other end of the spectrum, Class 3hardware is controlled, but not intended for flight, and leaves the level of rigor up to the project manager. This classification is often used for research and development projects. Similarly,Class-1E has been recently defined at NASA for ISS payloads and technology development projects that are not flight critical and do not need the full rigor of Class 1 to be successful. The EDR subsystem was challenged at commencement to adopt a skunkworks and agile-like approach to hardware development, allowing for a different risk posture than the rest of the AA-2 hardware. After initially pursuing Class 1 processes, the EDR subsystem design evolved to incorporating numerous commercial components, leading to re-designation as a Class-1E subsystem. The resulting EDR subsystem was fully successful in meeting all flight system requirements, and achieved 100% retrieval of flight test data. This paper will discuss the risk posture of the EDR subsystem and the subsequent tailoring that was enacted as part of its Class-1E status.

EDR↗

Numerical Investigation of Heat Transfer and Fluid Flow within Electrochemical Hydrogen Peroxide Generation Unit

Long-term manned space missions require the onboard production of disinfectants essential for maintaining crew health and supporting life systems. Currently, disinfection aboard the International Space Station (ISS) relies on disposable wetted wipes, which are regularly resupplied from Earth. This approach imposes a significant burden on resupply logistics, storage, and waste management. To address these challenges and support future missions, efforts are underway to develop an in-situ solution that electrochemically generates hydrogen peroxide disinfectant using onboard resources. In collaboration with NASA, Faraday Technology, Inc. has advanced this concept through a series of Small Business Innovation Research (SBIR) projects, resulting in the development of a Peroxide Generation Unit (PGU). The PGU can produce up to 3 wt.% hydrogen peroxide on-demand at a rate of 1 liter per day, providing a sustainable alternative to Earth-dependent supplies. The resulting aqueous hydrogen peroxide (H₂O₂) is an effective disinfectant, safe for crew use, compatible with spacecraft systems, and free from volatiles, off-gassing, or residues. This innovation offers a reliable, efficient solution for onboard disinfection, reducing dependence on Earth-based resupply while ensuring the health and safety of space crews. Generating hydrogen peroxide at the required rate needs high voltages and currents, exceeding 20V and 2A respectively, which leads to significant heat generation from Joule heating. This temperature rise poses a risk to sensitive system components, especially critical and expensive membranes that can degrade under thermal stress. To mitigate this risk, the thermal, fluid, and electrical flows within the system are modeled computationally using the commercial software COMSOL. The numerical simulations are validated against experimental data from both sub-scale and alpha-scale systems. Once verified, the model is employed to identify thermal hotspots, investigate their underlying causes, and explore solutions to prevent them.

Life Support Systems (LSS)↗

Structural reliability methods: Code development status

The Probabilistic Structures Analysis Method (PSAM) program integrates state of the art probabilistic algorithms with structural analysis methods in order to quantify the behavior of Space Shuttle Main Engine structures subject to uncertain loadings, boundary conditions, material parameters, and geometric conditions. An advanced, efficient probabilistic structural analysis software program, NESSUS (Numerical Evaluation of Stochastic Structures Under Stress) was developed as a deliverable. NESSUS contains a number of integrated software components to perform probabilistic analysis of complex structures. A nonlinear finite element module NESSUS/FEM is used to model the structure and obtain structural sensitivities. Some of the capabilities of NESSUS/FEM are shown. A Fast Probability Integration module NESSUS/FPI estimates the probability given the structural sensitivities. A driver module, PFEM, couples the FEM and FPI. NESSUS, version 5.0, addresses component reliability, resistance, and risk.

Millwater, Harry R.↗

Making or Breaking a Rover: System Engineering Parameters On-Board the Mars 2020 Perseverance Rover

On February 18, 2021, Perseverance, NASA’s Jet Propulsion Laboratory’s (JPL’s) Mars 2020 Rover, successfully landed on Mars with all systems nominal, despite the risk surrounding the over 200,000 internal flight parameters that had to be properly configured. The Perseverance team defines these parameters as software variables that are configurable, commandable and retrievable from Earth. In 2015, the Mars 2020 project leaders focused on improving systems engineering of parameters based on their experiences from parameter management on previous Mars rovers (Curiosity, Opportunity, Spirit, and Pathfinder) and parameter failures of past missions, such as the mission-ending parameter of the Mars Climate Orbiter. The new rigorous development process allowed for efficient certification and effective implementation of the parameters, allowing the rover to approach and land on the red planet (the most challenging phase of the mission) with zero parameter issues. Although successful, the Perseverance team learned many lessons for how to better manage parameters for the continued surface operations of the Mars 2020 mission and future missions. This paper will discuss eight parameter-management topics for the Perseverance Mission. The first is parameter definition: how we define parameters on our mission, where they are physically located on the vehicle, and why we have so many of them. The second topic is the updated parameter flight software module from Curiosity, including details on the 99% reduction in parameter commands, new bulk configuration capabilities, and improved parameter traceability. The third topic is parameter selection for different mission phases; this includes improving and tweaking our preferred parameter settings until they become certification candidates and managing parameter configurations based on test venue throughout the mission life cycle. The fourth topic is our flight certification process; this includes certification of flight values for four different epochs in the mission: Launch, Entry Decent and Landing (EDL) - 6days, Landing + 5 Sols (Martian Days, still on Cruise Flight Software), and once are on Surface Flight Software (FSW). The fifth topic covers in-flight command implementation, along with details on testing, validation, and verification of those commands. In the sixth section, we will explain our use of open-source management tools, including how we used GitHub for version control and management approvals. The seventh topic will describe the ground tools used in operations, including capabilities of the in-house built tool called Parasol. The eighth and final topic will dig into lessons learned for improving parameter management in the future of this mission and others.

Roth, Brian↗