SEARCH · Search NASA

Results for “progressive failure analysis”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 361 records · Page 20

All sources NASA NTRS DOE OSTI

NASA NTRSDate not supplied

Tribological Prospects and Progress for NiTi Bearings for Aerospace Applications

Rolling element and sliding bearings made from dimensionally stable, nickel-rich NiTi alloys have been successfully manufactured, tested and applied in several different aerospace applications. In this presentation, the development history and material properties of NiTi alloys is reviewed and its behavior in sliding and rolling contacts is examined. Key material characteristics such as superelasticity and fracture toughness and their effects on bearing applications are considered. With proper application engineering, it is shown that NiTi bearings can resolve longstanding and persistent bearing problems related to heavy loads and operation in corrosive and debris contaminated environments.

Bearings↗

DOE OSTI2025

Electric Vehicle and Charging Infrastructure Assessment in Cold-Weather Climates: A Case Study of Fairbanks, Alaska

The purpose of this report is to determine the effects that extreme cold temperatures have on electric vehicles (EVs) and electric vehicle supply equipment (EVSE). The adoption of EVs in extreme cold weather presents challenges that require careful analysis of efficiency and charging infrastructure. This report, "Electric Vehicle and Charging Infrastructure Assessment in Cold-Weather Climates: A Case Study of Fairbanks, Alaska," explores how EVs and EVSE perform in temperatures as low as -40 degrees C (-40 degrees F), focusing on real-world data from Teslas in Alaskan winter conditions. The findings indicate that EVs can successfully function in extreme cold, though efficiency is significantly affected. Vehicles stored in heated environments outperformed those stored outdoors, with efficiency dropping by up to 69% for outdoor storage. Despite these challenges, none of the vehicles experienced failures that prevented travel. Storing EVs indoors led to benefits such as faster preconditioning and improved efficiency, while charging in extreme cold, though slower, remained functional. Ultimately, the report concludes that with proper precautions and best practices, EVs are viable transportation solutions in cold climates. Investing in enclosed, heated storage is recommended to maximize efficiency and minimize battery strain. As advancements in battery chemistry and thermal management progress, EV adoption in extreme climates is expected to become even more feasible.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2020

Linking classical PRA models to a dynamic PRA

Here, this paper presents a series of methods designed to incorporate classical Probabilistic Risk Assessment (PRA) models such as Event Trees (ETs) and Fault Trees (FTs) into dynamic PRA. In contrast to classical PRA, dynamic PRA couples stochastic methods with system simulators to determine the risks associated with complex systems such as nuclear power plants. Compared with classical PRA methods, they can evaluate with higher resolution the safety impact of timing and sequencing of events on the progression of the accident. As part of a dynamic PRA analysis, it is not uncommon that parts of the system to be analyzed might not require a computationally expensive simulation model. These parts could be in fact modeled by employing classical PRA models (e.g., a FT). Here, we present a set of methods and tools that can be used to link the most common classical PRA models (ETs, FTs, reliability block diagrams and Markov models) to simulation codes such as RELAP5-3D: creating a “hybrid PRA.” In order to show the potential of such an hybrid PRA we employ this method to verify ET modeling assumptions (e.g., success criteria) using a large break loss of coolant accident initiating event as a test case. In this respect, we link a set of FTs from the original PRA to the RELAP5-3D code and perform a hybrid PRA. The FTs are employed to model the control logic of several safety systems and to propagate component failures throughout the system. Provided the generated dynamic PRA data, we show how conservative assumptions in the original PRA can be identified and how such original PRA can be modified by updating success criteria captured by the set of RELAP5-3D simulation runs.

97 - MATHEMATICS AND COMPUTING↗

NASA NTRS2011

Advanced Gear Alloys for Ultra High Strength Applications

Single tooth bending fatigue (STBF) test data of UHS Ferrium C61 and C64 alloys are presented in comparison with historical test data of conventional gear steels (9310 and Pyrowear 53) with comparable statistical analysis methods. Pitting and scoring tests of C61 and C64 are works in progress. Boeing statistical analysis of STBF test data for the four gear steels (C61, C64, 9310 and Pyrowear 53) indicates that the UHS grades exhibit increases in fatigue strength in the low cycle fatigue (LCF) regime. In the high cycle fatigue (HCF) regime, the UHS steels exhibit better mean fatigue strength endurance limit behavior (particularly as compared to Pyrowear 53). However, due to considerable scatter in the UHS test data, the anticipated overall benefits of the UHS grades in bending fatigue have not been fully demonstrated. Based on all the test data and on Boeing s analysis, C61 has been selected by Boeing as the gear steel for the final ERDS demonstrator test gearboxes. In terms of potential follow-up work, detailed physics-based, micromechanical analysis and modeling of the fatigue data would allow for a better understanding of the causes of the experimental scatter, and of the transition from high-stress LCF (surface-dominated) to low-stress HCF (subsurface-dominated) fatigue failure. Additional STBF test data and failure analysis work, particularly in the HCF regime and around the endurance limit stress, could allow for better statistical confidence and could reduce the observed effects of experimental test scatter. Finally, the need for further optimization of the residual compressive stress profiles of the UHS steels (resulting from carburization and peening) is noted, particularly for the case of the higher hardness C64 material.

Shen, Tony↗

NASA NTRS2010

Project Interface Requirements Process Including Shuttle Lessons Learned

Most failures occur at interfaces between organizations and hardware. Processing interface requirements at the start of a project life cycle will reduce the likelihood of costly interface changes/failures later. This can be done by adding Interface Control Documents (ICDs) to the Project top level drawing tree, providing technical direction to the Projects for interface requirements, and by funding the interface requirements function directly from the Project Manager's office. The interface requirements function within the Project Systems Engineering and Integration (SE&I) Office would work in-line with the project element design engineers early in the life cycle to enhance communications and negotiate technical issues between the elements. This function would work as the technical arm of the Project Manager to help ensure that the Project cost, schedule, and risk objectives can be met during the Life Cycle. Some ICD Lessons Learned during the Space Shuttle Program (SSP) Life Cycle will include the use of hardware interface photos in the ICD, progressive life cycle design certification by analysis, test, & operations experience, assigning interface design engineers to Element Interface (EI) and Project technical panels, and linking interface design drawings with project build drawings

Bauch, Garland T.↗

DOE OSTI2023

Why is the winner the best?

International benchmarking competitions have become fundamental for the comparative performance assessment of image analysis methods. However, little attention has been given to investigating what can be learnt from these competitions. Do they really generate scientific progress? What are common and successful participation strategies? What makes a solution superior to a competing method? To address this gap in the literature, we performed a multi- center study with all 80 competitions that were conducted in the scope of IEEE ISBI 2021 and MICCAI 2021. Statistical analyses performed based on comprehensive descriptions of the submitted algorithms linked to their rank as well as the underlying participation strategies revealed common characteristics of winning solutions. These typically include the use of multi-task learning (63%) and/or multi-stage pipelines (61%), and a focus on augmentation (100%), im- age preprocessing (97%), data curation (79%), and post- processing (66%). The “typical” lead of a winning team is a computer scientist with a doctoral degree, five years of experience in biomedical image analysis, and four years of experience in deep learning. Two core general development strategies stood out for highly-ranked teams: the reflection of the metrics in the method design and the focus on analyzing and handling failure cases. According to the organizers, 43% of the winning algorithms exceeded the state of the art but only 11% completely solved the respective domain problem. The insights of our study could help researchers (1) improve algorithm development strategies when approaching new problems, and (2) focus on open research questions revealed by this work.

Eisenmann, Matthias↗

DOE OSTI2026

Prioritizing Uncertainties in Hydrogen Contribution to Risk in Post-Crash Outcomes for Rail

This report presents analysis from Sandia National Laboratories predicting contributions to risk associated with the use of hydrogen technology for rail. Event sequence diagrams are used to describe possible accident scenarios and progressions. Initiating event frequencies and branch event probabilities for each scenario are quantified with uncertainty using distributions fit to Federal Railroad Administration and U.S. Department of Transportation Pipeline and Hazardous Materials Safety Administration data on applicable accidents from 2000 to 2020. Uncertainty is propagated through the event sequence diagram to estimate the frequency and conditional probability of accident end states. The analysis identifies four scenarios with significant contributions to risk from hydrogen that are predicted to occur relatively frequently, which may inform priorities for reducing uncertainty. These scenarios are 1) overpressure events resulting from collisions with hydrogen release due to mechanical damage and delayed ignition, 2) jet fire events resulting from collisions with hydrogen release due to mechanical damage and immediate ignition, 3) jet fires resulting from fire or explosion initiating events involving the hydrogen tank and correct operation of the thermally-activated pressure relief device (TPRD) subsequent to the thermal insult, and 4) pressure burst resulting from fire or explosion initiating events involving the hydrogen tank and failure of the TPRD. Delayed and immediate hydrogen ignition probabilities are identified as being highly uncertain and potential candidates for reducing conservatism in the predicted frequencies for these two scenarios.

08 HYDROGEN↗

DOE OSTI2024

Assessment and validation of NEAMS tools for high-fidelity multiphysics transient modeling of microreactors: Application of NEAMS codes to perform multiphysics modeling analyses of micro-reactor concepts

The NEAMS Multiphysics Applications team aims at providing assessment of code useability and functionality for microreactor design and analyses, together with demonstration of their capabilities to properly capture the steady-state and time-dependent behavior of different microreactor concepts. In FY-24, significant progress was achieved in improving multi-physics models of several microreactors systems: HP-MR, GC-MR and KRUSTY. These efforts focused on solving more complex multiphysics problems enabled by enhanced tools capability, verifying and validating results obtained, providing feedback to developers for suggested improvements, and sharing these models to facilitate user training. A series of new multiphysics transients were completed on the HP-MR (using Griffin/BISON/Sockeye) with core startup transient, control drum inadvertent rotation accident, and hydrogen leakage from hydride moderator (also including SWIFT). On the GC-MR, a new full-core model was developed and analyzed through a series of new multiphysics (Griffin/BISON/SAM) transients to simulate moderator leakage (also including SWIFT), flow blockage and coolant depressurization. Additional and updated TRISO failure analyses were completed on the HP-MR unit-cell and GC-MR assembly models leveraging improved TRISO modeling capabilities. The amount of SiC failure following accidental transients at end-of-life was null. However, GC-MR assembly TRISO analysis highlighted Pd penetration rate can be problematic and may require design changes on the studied microreactor concept. The neutronics discrepancies observed on the KRUSTY model in previous years were resolved using hybrid set of Monte Carlo/Deterministic cross-sections. The multiphysics (Griffin neutronics / BISON thermal-mechanics) 15₵ insertion transient simulation displayed good agreement when comparing with experimental data. Initial modeling of the 30 ₵ reactivity insertion also displays promising results. Such close agreement provides important validation data that can be leveraged by the NEAMS program and by microreactor vendors to support licensing of their technology. Finally, important experience was gathered with the NEAMS tools leading to several user feedback shared with tools developers, especially with regards to MOOSE mesh generator and Griffin. This project led to many publications demonstrating modeling capabilities, and to three models shared on the Virtual Test Bed.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2022

Towards Low-Overhead Resilience for Data Parallel Deep Learning

Data parallel techniques have been widely adopted both in academia and industry as a tool to enable scalable training of deep learning models. At scale, DL training jobs can fail due to software or hardware bugs, may need to be preempted or terminated due to unexpected events, or may perform suboptimally because they were misconfigured. Under such circumstances, there is a need to recover and/or reconfigure data-parallel DL training jobs on-the-fly, while minimizing the impact on the accuracy of the DNN model and the runtime overhead. In this regard, state-of-art techniques adopted by the HPC community mostly rely on checkpoint-restart, which inevitably leads to loss of progress, thus increasing the runtime overhead. In this paper we explore alternative techniques that exploit the properties of modern deep learning frameworks (overlapping of gradient averaging and weight updates with local gradient computations through pipeline parallelism) to reduce the overhead of resilience/elasticity. To this end we introduce a failure simulation framework and two resilience strategies (immediate mini-batch rollback and lossy forward recovery), which we study compared with checkpoint-restart approaches in a variety of settings in order to understand the trade-offs between the accuracy loss of the DNN model and the runtime overhead.

data-parallel training↗

NASA NTRS1984

Failure analysis of a graphite/epoxy laminate subjected to bolt bearing loads

Quasi-isotropic graphite/epoxy laminates (T300/5208) were tested under bolt bearing loads to study failure modes, strengths, and failure energy. Specimens had a range of configurations to produce failures by the three nominal failure modes: tension, shearout, and bearing. Radiographs were made after damage onset and after ultimate load to examine the failure modes. Also, the laminate stresses near the bolt hole calculated for each test specimen configuration, and then used with a failure criterion to analyze the test data. Failures involving extensive bearing damage were found to dissipate significantly more energy than tension dominated failures. The specimen configuration influenced the failure modes and therefore also influenced the failure energy. In the width-to-diameter ratio range of 4 to 5, which is typical of structural joints, a transition from the tension mode to the bearing mode was shown to cause a large increase in failure energy. The failure modes associated with ultimate strength were usually different from those associated with the damage onset. Typical damage sequences involved bearing damage onset at the hole boundary followed by tension damage progressing from the hole boundary.

Crews, J. H., Jr.↗

NASA NTRS2018

A Nonlocal Progressive Damage Model for Composite Materials

Fiber reinforced composite materials are widely used in aerospace structures due to their high specific stiffness and strength. These materials exhibit complex deformation, damage and failure mechanisms under high strain rate loading conditions. Many different failure criteria have been proposed in literature to describe the damage initiation and evolution of fiber reinforced composite materials. Most of these damage models are based on a local framework. In a local framework, the material behavior is based on a point-wise constitutive relation which is independent of the effect of the surrounding points. These models include stiffness degradation when damage initiates in the material, which within a local framework leads to a highly mesh dependent result. This could be overcome using a nonlocal finite element approach. In the current work, a nonlocal formulation based on the work by Andrade et al [1] is adapted to describe composite material behavior. The LS-DYNA rate dependent progressive damage model, MAT162 is employed to detect the initiation and evolution of damage in orthotropic composite materials. This model is developed as a FORTRAN user material subroutine in the LS-DYNA environment. The results of MAT162 with and without the nonlocal formulation are compared at different mesh densities to validate the model. The numerical analysis exhibits the advantages of the nonlocal formulation.

Kodagali, Karan↗

NASA NTRS1986

Failure analysis of a graphite/epoxy laminate subjected to bolt-bearing loads

Quasi-isotropic graphite-epoxy laminates (T300/5208) were tested under bolt bearing loads to study failure modes, strengths, and failure energy. Specimens had a range of configurations to produce failures by the three nominal failure modes: tension, shearout, and bearing. Radiographs were made after damage onset and after ultimate load to examine the failure modes. Also, the laminate stresses near the bolt hole calculated for each test specimen configuration, and then used with a failure criterion to analyze the test data. Failures involving extensive bearing damage were found to dissipate significantly more energy than tension dominated failures. The specimen configuration influenced the failure modes and therefore also influenced the failure energy. In the width-to-diameter ratio range of 4 to 5, which is typical of structural joints, a transition from the tension mode to the bearing mode was shown to cause a large increase in failure energy. The failure modes associated with ultimate strength were usually different from those associated with the damage onset. Typical damage sequences involved bearing damage onset at the hole boundary followed by tension damage progressing from the hole boundary.

Crews, J. H., Jr.↗

NASA NTRS1994

Nondestructive evaluation of fatigue damage in aluminum 2024 by x-ray diffraction

Aluminum alloys are widely used in the automobile and aerospace industries. This is due to their attractive low density-high modulus and low density-high strength characteristics. Unfortunately, cyclic stress-strain deformations alter the microstructure of aluminum alloys when they are placed into service. These structural changes can lead to fatigue damage and ultimately service failure. Since x-ray diffraction analysis is known to be a sensitive nondestructive indicator of structural changes due to deformations, this technique is being used to evaluate changes in the microstructure of cycled aluminum 2024 commercial alloys. Line shapes, widths, and positions in an x-ray diffraction pattern depend on microstructural properties such as grain size, grain orientation, residual stress, microstrain, etc. Changes in the microstructure due to fatigue will appear as changes in the diffraction pattern. One parameter used to characterize a reflection in a diffraction pattern is the full width at half maximum (FWHM). Preliminary x-ray diffraction results on cycled Al 2024 indicate that the (111) and (222) reflections of the matrix phase do not show any variations in the FWHM due to an increase in the fatigue cycles. However, the FWHM of the (200) and (400) reflections of the same phase unexpectedly showed a dramatic decrease. These results can be interpreted as due to the relaxation of some initial nonuniform residual stresses in the matrix phase lattice. Further work is in progress to evaluate the FWHM of the second phase of the cycled alloys.

Ferguson, Milton W.↗

NASA NTRS2019

Simulated Weightlessness Alters Cardiomyocyte Structure and Transcriptional Regulation of Mediators Related to Immunity and Cardiovascular Disease

Spaceflight and the ensuing fluid shifts, together with an overall reduction in physical activity, lead to acute and latent effects on the cardiovascular system. This current study makes use of the rodent hindlimb unloading (HU) model to determine how factors such as sex, age, and duration of exposure impact cardiac responses to weightlessness. We hypothesize that extended exposure to simulated weightlessness and the ensuing recovery alters cardiac structure and expression of select genes, including those involved in redox signaling which together, negatively impact long-term cardiac tissue health. To begin to test this hypothesis, male and female rats underwent HU at various durations up to 90 days, with a subset reambulated after 90 days of HU. Physiological stress or contractility changes lead to alterations in ventricular cardiomyocyte size and ventricular wall thickness to adapt to greater functional demand and mitigate mechanical stress to ventricular tissue; under certain conditions, these changes also may mark progression to cardiac failure. Hence, left ventricular cardiomyocyte size (cardiomyocyte cross sectional area, CSA) was quantified to determine if HU leads to structural adaptation responses in cardiac tissue and if age and sex had any impact on this outcome. Cardiomyocyte CSA of older males (9 months) were altered by HU in a time-dependent manner, where HU led to decreases in CSA at 14 days and increases at 90 days. In contrast, younger males (3 months) did not show any changes at day 14 of HU. CSA of females (3 months) was increased in response to short-term HU (14 days) suggesting sex-dependence of structural changes. In older HU males, cardiomyocyte CSA was comparable to controls after 90 days of re-ambulation. Levels of the DNA oxidative damage marker, 8-hydroxydeoxyguanosine (8-OHdG) were greater in left ventricular tissue of females that underwent HU compared to sex-matched controls, while there were no such differences in older or younger males. To gain insight into the signals that drive cardiac adaptations to HU, global transcriptomic analysis (RNAseq) was performed on left ventricular tissue of older males that underwent 14 days of HU. Short-term simulated weightlessness led to differential expression of genes involved in immune and pro-inflammatory signaling. A subset of these genes play a role in autoimmune and cardiovascular disease and are targets of current drugs used to treat bradycardia, hypertension, atherosclerosis and rheumatoid arthritis, amongst others. Oxidative damage/redox signaling pathways were not enriched at the timepoint tested in older males. Since young females displayed greater oxidative damage to DNA, activation of oxidative stress responses at earlier or later time points cannot be ruled out. In summary, simulated weightlessness in adult rats caused changes in cardiomyocyte structure in a sex and age-dependent manner, and the transcriptional regulation of key mediators of immunity and cardiovascular disease, meriting further study to define cardiac risks for interplanetary travel of human crew. Our findings also confirm the value of the rat HU model for cardiac health and countermeasure research.

Tahimic, Candice↗

DOE OSTI2022

Metrics for Intercomparison of Remapping Algorithms (MIRA) protocol applied to Earth system models

Abstract. Strongly coupled nonlinear phenomena such as those described by Earth system models (ESMs) are composed of multiple component models with independent mesh topologies and scalable numerical solvers. A common operation in ESMs is to remap or interpolate component solution fields defined on their computational mesh to another mesh with a different combinatorial structure and decomposition, e.g., from the atmosphere to the ocean, during the temporal integration of the coupled system. Several remapping schemes are currently in use or available for ESMs. However, a unified approach to compare the properties of these different schemes has not been attempted previously. We present a rigorous methodology for the evaluation and intercomparison of remapping methods through an independently implemented suite of metrics that measure the ability of a method to adhere to constraints such as grid independence, monotonicity, global conservation, and local extrema or feature preservation. A comprehensive set of numerical evaluations is conducted based on a progression of scalar fields from idealized and smooth to more general climate data with strong discontinuities and strict bounds. We examine four remapping algorithms with distinct design approaches, namely ESMF Regrid (Hill et al., 2004), TempestRemap (Ullrich and Taylor, 2015), generalized moving least squares (GMLS) (Trask and Kuberry, 2020) with post-processing filters, and WLS-ENOR (Li et al., 2020). By repeated iterative application of the high-order remapping methods to the test fields, we verify the accuracy of each scheme in terms of their observed convergence order for smooth data and determine the bounded error propagation using challenging, realistic field data on both uniform and regionally refined mesh cases. In addition to retaining high-order accuracy under idealized conditions, the methods also demonstrate robust remapping performance when dealing with non-smooth data. There is a failure to maintain monotonicity in the traditional L2-minimization approaches used in ESMF and TempestRemap, in contrast to stable recovery through nonlinear filters used in both meshless GMLS and hybrid mesh-based WLS-ENOR schemes. Local feature preservation analysis indicates that high-order methods perform better than low-order dissipative schemes for all test cases. The behavior of these remappers remains consistent when applied on regionally refined meshes, indicating mesh-invariant implementations. The MIRA intercomparison protocol proposed in this paper and the detailed comparison of the four algorithms demonstrate that the new schemes, namely GMLS and WLS-ENOR, are competitive compared to standard conservative minimization methods requiring computation of mesh intersections. The work presented in this paper provides a foundation that can be extended to include complex field definitions, realistic mesh topologies, and spectral element discretizations, thereby allowing for a more complete analysis of production-ready remapping packages.

58 GEOSCIENCES↗

DOE OSTI2023

Natural Language Processing-Enhanced Nuclear Industry Operating Experience Data Analysis: Aggregation and Interpretation of Multi-Report Analysis Results

Industry-wide operating experience is a critical source of raw data for reliability and risk model parameter estimations for nuclear power plants. A large portion of operating experience data are failure events stored as reports that contain unstructured data, such as narratives. In current practice, a failure report is usually reviewed and manually coded by analysts. The coding is based on extracting several event characteristics such as system name, component type, sub-part type, failure mode, and failure cause. Event narratives are mostly used to help understand events and extract their characteristics. In this line of research, we aim to maximize the usage of event narratives by leveraging natural language processing (NLP) methods to automatically convert an event narrative to a causal graph. This research has promise to improve physical understanding of failure initiation and propagation and to facilitate use of non-failure data (e.g., near-misses and degradations) to complement the limited data pool of failures. In our previous work, we developed an NLP tool and applied it to analyze a number of licensee event reports submitted by U.S. nuclear power plants to the Nuclear Regulatory Commission. In this paper, we will report our recent research progress in aggregating the results of multiple reports, developing network model(s), and drawing statistical insights.

99 GENERAL AND MISCELLANEOUS↗

NASA NTRS2014

Aperture Valve for the Mars Organic Molecule Analyzer (MOMA)

NASA's participation in the multi-nation ExoMars 2018 Rover mission includes a critical astrobiology Mass Spectrometer Instrument on the Rover called the Mars Organic Molecule Analyzer (MOMA). The Aperture Valve is a critical electromechanical valve used by the Mass Spectrometer to facilitate the transfer of ions from Martian soil to the Mass Spectrometer for analysis. The MOMA Aperture Valve development program will be discussed in terms of the Initial valve design and subsequent improvements that resulted from prototype testing. The Initial Aperture Valve concept seemed promising, based on calculations and perceived merits. However, performance results of this design were disappointing, due to delamination of TiN and DLC coatings applied to the Titanium base metals, causing debris from the coatings to seize the valve. While peer reviews and design trade studies are important forums to vet a concept design, results from testing should not be underestimated.Despite the lack of development progress to meet requirements, valuable information from weakness discovered in the Initial Valve design was used to develop a second, more robust Aperture valve. Based on a check-ball design, the ETU flight valve design resulted in significantly less surface area to create the seal. Moreover, PVD coatings were eliminated in favor of hardened, nonmagnetic corrosion resistant alloys. Test results were impressive, with the valve achieving five orders of magnitude better sealing leak rate over end of life requirements. Cycle life was equally impressive, achieving 280,000 cycles without failure.

Mars↗

NASA NTRS2014

Aperture Valve for the Mars Organic Molecule Analyzer (MOMA)

NASA's participation in the multi-nation ExoMars 2018 Rover mission includes a critical astrobiology Mass Spectrometer Instrument on the Rover called the Mars Organic Molecule Analyzer (MOMA). The Aperture Valve is a critical electromechanical valve used by the Mass Spectrometer to facilitate the transfer of ions from Martian soil to the Mass Spectrometer for analysis. The MOMA Aperture Valve development program will be discussed in terms of the Initial valve design and subsequent improvements that resulted from prototype testing. The Initial Aperture Valve concept seemed promising, based on calculations and perceived merits. However, performance results of this design were disappointing, due to delamination of TiN and DLC coatings applied to the Titanium base metals, causing debris from the coatings to seize the valve. While peer reviews and design trade studies are important forums to vet a concept design, results from testing should not be underestimated. Despite the lack of development progress to meet requirements, valuable information from weakness discovered in the Initial Valve design was used to develop a second, more robust Aperture valve. Based on a check-ball design, the ETU /flight valve design resulted in significantly less surface area to create the seal. Moreover, PVD coatings were eliminated in favor of hardened, nonmagnetic corrosion resistant alloys. Test results were impressive, with the valve achieving five orders of magnitude better sealing leak rate over end of life requirements. Cycle life was equally impressive, achieving 280,000 cycles without failure.

00000↗