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At least 145 records · Page 8

Mesoscale Variations of Biogeochemical Properties in the Sargasso Sea

A mesoscale resolution biogeochemical survey was carried out in the vicinity of the US Joint Global Ocean Flux Study Bermuda Atlantic Time-Series Study (BATS) site during the summer of 1996. Real-time nowcasting and forecasting of the flow field facilitated adaptive sampling of several eddy features in the area. Variations in upper ocean nutrient and pigment distributions were largely controlled by vertical isopycnal displacements associated with the mesoscale field. Shoaling density surfaces tended to introduce cold, nutrient-rich water into the euphotic zone, while deepening isopycnals displaced nutrient-depleted water downward. Chlorophyll concentration was generally enhanced in the former case and reduced in the latter. Eddy-induced upwelling at the base of the euphotic zone was affected by features of two different types captured in this survey: (1) a typical mid-ocean cyclone in which doming of the main thermocline raised the near-surface stratification upward; and (2) a mode water eddy composed of a thick lens of 18 C water, which pushed up the seasonal thermocline and depressed the main thermocline. Model hindcasts using all available data provide a four-dimensional context in which to interpret temporal trends at the BATS site and two other locations during the two weeks subsequent to the survey. Observed changes in near-surface structure at the BATS site included shoaling iscpycnals, increased nutrient availability at the base of the euphotic zone, and enhanced chlorophyll concentration within the euphotic zone. These trends are explicable in terms of a newly formed cyclone that impinged upon the site during this time period. These observations reveal that eddy upwelling has a demonstrable impact on the way in which the nitrate-density relationship changes with depth from the aphotic zone into the euphotic zone. A similar transition is present in the BATS record, suggesting that eddy-driven upwelling events are present in the time series of upper ocean biogeochemical properties. The variability in main thermocline temperature and nitrate in this synoptic spatial survey spans the range observed in these quantities in the 10-year time series available at BATS to date (1988-1998).

McGillicuddy Dennis J., Jr.↗

Mesoscale Variations of Biogeochemical Properties in the Sargasso Sea

A mesoscale resolution biogeochemical survey was carried out in the vicinity of the U.S. Joint Global Ocean Flux Study Bermuda Atlantic Time-series Study (BATS) site during the summer of 1996. Real-time nowcasting and forecasting of the flow field facilitated adaptive sampling of several eddy features in the area. Variations in upper ocean nutrient and pigment distributions were largely controlled by vertical isopycnal displacements associated with the mesoscale field. Shoaling density surfaces tended to introduce cold, nutrient-rich water into the euphotic zone, while deepening isopycnals displaced nutrient-depleted water downward. Chlorophyll concentration was generally enhanced in the former case and reduced in the latter. Eddy-induced upwelling at the base of the euphotic zone was affected by features of two different types captured in this survey-, (1) a typical mid-ocean cyclone in which doming of the main thermocline raised the near-surface stratification upward and (2) a mode water eddy composed of a thick lens of 18C water, which pushed up the seasonal thermocline and depressed the main thermocline. Model hindcasts using all available data provide a four-dimensional context in which to interpret temporal trends at the BATS site and two other locations during the 2 weeks subsequent to the survey. Observed changes in near-surface structure at the BATS site included shoaling isopycnals, increased nutrient availability at the base of the euphotic zone, and enhanced chlorophyll concentration within the cuphotic zone. These trends are explicable in terms of a newly formed cyclone that impinged upon the site during this time period. These observations reveal that eddy upwelling has a demonstrable impact on the way in which the nitrate-density relationship changes with depth from the aphotic zone into the euphotic zone. A similar transition is present in the BATS record, suggesting that eddy-driven upwelling events are present in the time series of upper ocean biogeochemical properties. The variability in main thermocline temperature and nitrate in this synoptic spatial survey spans the range observed in these quantities in the 10-year time series available at BATS to date (1988-1998).

McGillicuddy, D. J.↗

NASA Tech Briefs, November 2012

The topics include: Visual System for Browsing, Analysis, and Retrieval of Data (ViSBARD); Time-Domain Terahertz Computed Axial Tomography NDE System; Adaptive Sampling of Time Series During Remote Exploration; A Tracking Sun Photometer Without Moving Parts; Surface Temperature Data Analysis; Modular, Autonomous Command and Data Handling Software with Built-In Simulation and Test; In-Situ Wire Damage Detection System; Amplifier Module for 260-GHz Band Using Quartz Waveguide Transitions; Wideband Agile Digital Microwave Radiometer; Buckyball Nucleation of HiPco Tubes; FACT, Mega-ROSA, SOLAROSA; An Integrated, Layered-Spinel Composite Cathode for Energy Storage Applications; Engineered Multifunctional Surfaces for Fluid Handling; Polyolefin-Based Aerogels; Adjusting Permittivity by Blending Varying Ratios of SWNTs; Gravity-Assist Mechanical Simulator for Outreach; Concept for Hydrogen-Impregnated Nanofiber/Photovoltaic Cargo Stowage System; DROP: Durable Reconnaissance and Observation Platform; Developing Physiologic Models for Emergency Medical Procedures Under Microgravity; Spectroscopic Chemical Analysis Methods and Apparatus; Low Average Sidelobe Slot Array Antennas for Radiometer Applications; Motion-Corrected 3D Sonic Anemometer for Tethersondes and Other Moving Platforms; Water Treatment Systems for Long Spaceflights; Microchip Non-Aqueous Capillary Electrophoresis (MicronNACE) Method to Analyze Long-Chain Primary Amines; Low-Cost Phased Array Antenna for Sounding Rockets, Missiles, and Expendable Launch Vehicles; Mars Science Laboratory Engineering Cameras; Seismic Imager Space Telescope; Estimating Sea Surface Salinity and Wind Using Combined Passive and Active L-Band Microwave Observations; A Posteriori Study of a DNS Database Describing Super critical Binary-Species Mixing; Scalable SCPPM Decoder; QuakeSim 2.0; HURON (HUman and Robotic Optimization Network) Multi-Agent Temporal Activity Planner/Scheduler; MPST Software: MoonKommand

Source record↗

NASA Tech Briefs, April 2013

Topics covered include: Fully Integrated, Miniature, High-Frequency Flow Probe Utilizing MEMS Leadless SOI Technology; Nanoscale Surface Plasmonics Sensor With Nanofluidic Control; Advanced Dispersed Fringe Sensing Algorithm for Coarse Phasing Segmented Mirror Telescopes; Neural Network Back-Propagation Algorithm for Sensing Hypergols; Bulk Moisture and Salinity Sensor; Change-Based Satellite Monitoring Using Broad Coverage and Targetable Sensing; Circularly Polarized Microwave Antenna Element with Very Low Off-Axis Cross-Polarization; Ultra-Low Heat-Leak, High-Temperature Superconducting Current Leads for Space Applications; Flash Cracking Reactor for Waste Plastic Processing; An Automated Safe-to-Mate (ASTM) Tester; Wireless Chalcogenide Nanoionic-Based Radio-Frequency Switch; Compute Element and Interface Box for the Hazard Detection System; DOT Transmit Module; Composite Aerogel Multifoil Protective Shielding; Li-Ion Electrolytes with Improved Safety and Tolerance to High-Voltage Systems; Polymer-Reinforced, Non-Brittle, Lightweight Cryogenic Insulation; Controlled, Site-Specific Functionalization of Carbon Nanotubes with Diazonium Salts; Regenerable Sorbent for CO2 Removal; Sprayable Aerogel Bead Compositions With High Shear Flow Resistance and High Thermal Insulation Value; Lexan Linear Shaped Charge Holder with Magnets and Backing Plate; Robotic Ankle for Omnidirectional Rock Anchors; Wind, Wave, and Tidal Energy Without Power Conditioning; An Active Heater Control Concept to Meet IXO Type Mirror Module Thermal-Structural Distortion Requirement; Waterless Clothes-Cleaning Machine; Integrated Electrical Wire Insulation Repair System; LVGEMS Time-of-Flight Mass Spectrometry on Satellites; Surface Inspection Tool for Optical Detection of Surface Defects; Per-Pixel, Dual-Counter Scheme for Optical Communications; Certification-Based Process Analysis; Surface Navigation Using Optimized Waypoints and Particle Swarm Optimization; Smart-Divert Powered Descent Guidance to Avoid the Backshell Landing Dispersion Ellipse; Estimating Foreign-Object-Debris Density from Photogrammetry Data; Adaptive Sampling of Spatiotemporal Phenomena with Optimization Criteria; Building a 2.5D Digital Elevation Model From 2D Imagery; Eyes on the Earth 3D; Target Trailing With Safe Navigation for Maritime Autonomous Surface Vehicles; Adams-Based Rover Terramechanics and Mobility Simulator - ARTEMIS; ISTP CDF Skeleton Editor; Uplink Summary Generator (ULSGEN) Version 1.0; Robotics On-Board Trainer (ROBoT); Software Engineering Tools for Scientific Models; Automatic Data Filter Customization Using a Genetic Algorithm; Tracker Toolkit; Towards Efficient Scientific Data Management Using Cloud Storage; On a Formal Tool for Reasoning About Flight Software Cost Analysis; A Nanostructured Composites Thermal Switch Controls Internal and External Short Circuit in Lithium Ion Batteries; Spacecraft Crew Cabin Condensation Control; and Functional Near-Infrared Spectroscopy Signals Measure Neuronal Activity in the Cortex.

Source record↗

Orion MPCV Touchdown Detection Threshold Development and Testing

A robust method of detecting Orion Multi-Purpose Crew Vehicle (MPCV) splashdown is necessary to ensure crew and hardware safety during descent and after touchdown. The proposed method uses a triple redundant system to inhibit Reaction Control System (RCS) thruster firings, detach parachute risers from the vehicle, and transition to the post-landing segment of the Flight Software (FSW). An in-depth trade study was completed to determine optimal characteristics of the touchdown detection method resulting in an algorithm monitoring filtered, lever-arm corrected, 200 Hz Inertial Measurement Unit (IMU) vehicle acceleration magnitude data against a tunable threshold using persistence counter logic. Following the design of the algorithm, high fidelity environment and vehicle simulations, coupled with the actual vehicle FSW, were used to tune the acceleration threshold and persistence counter value to result in adequate performance in detecting touchdown and sufficient safety margin against early detection while descending under parachutes. An analytical approach including Kriging and adaptive sampling allowed for a sufficient number of finite element analysis (FEA) impact simulations to be completed using minimal computation time. The combination of a persistence counter of 10 and an acceleration threshold of approximately 57.3 ft/s2 resulted in an impact performance factor of safety (FOS) of 1.0 and a safety FOS of approximately 2.6 for touchdown declaration. An RCS termination acceleration threshold of approximately 53.1 ft/s(exp)2 with a persistence counter of 10 resulted in an increased impact performance FOS of 1.2 at the expense of a lowered under-parachutes safety factor of 2.2. The resulting tuned algorithm was then tested on data from eight Capsule Parachute Assembly System (CPAS) flight tests, showing an experimental minimum safety FOS of 6.1. The formulated touchdown detection algorithm will be flown on the Orion MPCV FSW during the Exploration Flight Test 1 (EFT-1) mission in the second half of 2014.

Daum, Jared↗

OpenMDAO: Framework for Flexible Multidisciplinary Design, Analysis and Optimization Methods

The OpenMDAO project is underway at NASA to develop a framework which simplifies the implementation of state-of-the-art tools and methods for multidisciplinary design, analysis and optimization. Foremost, OpenMDAO has been designed to handle variable problem formulations, encourage reconfigurability, and promote model reuse. This work demonstrates the concept of iteration hierarchies in OpenMDAO to achieve a flexible environment for supporting advanced optimization methods which include adaptive sampling and surrogate modeling techniques. In this effort, two efficient global optimization methods were applied to solve a constrained, single-objective and constrained, multiobjective version of a joint aircraft/engine sizing problem. The aircraft model, NASA's nextgeneration advanced single-aisle civil transport, is being studied as part of the Subsonic Fixed Wing project to help meet simultaneous program goals for reduced fuel burn, emissions, and noise. This analysis serves as a realistic test problem to demonstrate the flexibility and reconfigurability offered by OpenMDAO.

Kriging↗

Testing Surrogate-Based Optimization with the Fortified Branin-Hoo Extended to Four Dimensions

Some popular functions used to test global optimization algorithms have multiple local optima, all with the same value, making them all global optima. It is easy to make them more challenging by fortifying them via adding a localized bump at the location of one of the optima. In previous work the authors illustrated this for the Branin-Hoo function and the popular differential evolution algorithm, showing that the fortified Branin-Hoo required an order of magnitude more function evaluations. This paper examines the effect of fortifying the Branin-Hoo function on surrogate- based optimization, which usually proceeds by adaptive sampling. Two algorithms are considered. The EGO algorithm, which is based on a Gaussian process (GP) and an algorithm based on radial basis functions (RBF). EGO is found to be more frugal in terms of the number of required function evaluations required to identify the correct basin, but it is expensive to run on a desktop, limiting the number of times the runs could be repeated to establish sound statistics on the number of required function evaluations. The RBF algorithm was cheaper to run, providing more sound statistics on performance. A four-dimensional version of the Branin-Hoo function was introduced in order to assess the effect of dimensionality. Furthermore, it was found that the difference between the ordinary function and the fortified one was much more pronounced for the four-dimensional function compared to the two dimensional one.

97 MATHEMATICS AND COMPUTING↗

"Hybrid fracture/matrix modeling for well completion options evaluation"

Orientation and completion for well pairs that have been subjected to multi-zonal stimulation play a critical role in the long-term performance of an Enhanced Geothermal Reservoir. Here we present the development of a methodology to rapidly and efficiently numerically simulate mixed fracture-matrix flow systems for evaluation of well design and completion options. The methodology is based on a loose coupling framework, allowing the fracture and matrix systems to be meshed separately. The fracture system includes the integration of fracture growth and aperture data from well stimulation simulations of stochastically generated fracture networks. Automatic mesh refinement is used in the matrix simulation to resolve heat transfer near the fracture network. This simulation framework is used to efficiently determine optimal production and injection well placement using adaptive sampling.

15 GEOTHERMAL ENERGY↗

Adaptive stratified importance sampling: hybridization of extrapolation and importance sampling Monte Carlo methods for estimation of wind turbine extreme loads

Wind turbine extreme load estimation is especially difficult because turbulent inflow drives nonlinear turbine physics and control strategies; thus there can be huge differences in turbine response to essentially equivalent environmental conditions. The two main current approaches, extrapolation and Monte Carlo sampling, are both unsatisfying: extrapolation-based methods are dangerous because by definition they make predictions outside the range of available data, but Monte Carlo methods converge too slowly to routinely reach the desired 50-year return period estimates. Thus a search for a better method is warranted. We introduce an adaptive stratified importance sampling approach that allows for treating the choice of environmental conditions at which to run simulations as a stochastic optimization problem that minimizes the variance of unbiased estimates of extreme loads. Furthermore, the framework, built on the traditional bin-based approach used in extrapolation methods, provides a close connection between sampling and extrapolation, and thus allows the solution of the stochastic optimization (i.e., the optimal distribution of simulations in different wind speed bins) to guide and recalibrate the extrapolation. Results show that indeed this is a promising approach, as the variance of both the Monte Carlo and extrapolation estimates are reduced quickly by the adaptive procedure. We conclude, however, that due to the extreme response variability in turbine loads to the same environmental conditions, our method and any similar method quickly reaches its fundamental limits, and that therefore our efforts going forward are best spent elucidating the underlying causes of the response variability.

17 WIND ENERGY↗

Improved Sampling Algorithms in the Risk-Informed Safety Margin Characterization Toolkit

The RISMC approach is developing advanced set of methodologies and algorithms in order to perform Probabilistic Risk Analyses (PRAs). In contrast to classical PRA methods, which are based on Event-Tree and Fault-Tree methods, the RISMC approach largely employs system simulator codes applied to stochastic analysis tools. The basic idea is to randomly perturb (by employing sampling algorithms) timing and sequencing of events and internal parameters of the system codes (i.e., uncertain parameters) in order to estimate stochastic parameters such as core damage probability. This approach applied to complex systems such as nuclear power plants requires to perform a series of computationally expensive simulation runs given a large set of uncertain parameters. These types of analysis are affected by two issues. Firstly, the space of the possible solutions (a.k.a., the issue space or the response surface) can be sampled only very sparsely, and this precludes the ability to fully analyze the impact of uncertainties on the system dynamics. Secondly, large amounts of data are generated and tools to generate knowledge from such data sets are not yet available. This report focuses on the first issue and in particular employs novel methods that optimize the information generated by the sampling process by sampling unexplored and risk-significant regions of the issue space: adaptive (smart) sampling algorithms. They infer system response from surrogate models constructed from existing samples and predict the most relevant location of the next sample. It is therefore possible to understand features of the issue space with a small number of carefully selected samples. In this report, we will present how it is possible to perform adaptive sampling using the RISMC toolkit and highlight the advantages compared to more classical sampling approaches such Monte-Carlo. We will employ RAVEN to perform such statistical analyses using both analytical cases but also another RISMC code: RELAP-7.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

ADAPTIVE ANNEALED IMPORTANCE SAMPLING FOR MULTIMODAL POSTERIOR EXPLORATION AND MODEL SELECTION WITH APPLICATION TO EXTRASOLAR PLANET DETECTION

We describe an algorithm that can adaptively provide mixture summaries of multimodal posterior distributions. The parameter space of the involved posteriors ranges in size from a few dimensions to dozens of dimensions. This work was motivated by an astrophysical problem called extrasolar planet (exoplanet) detection, wherein the computation of stochastic integrals that are required for Bayesian model comparison is challenging. The difficulty comes from the highly nonlinear models that lead to multimodal posterior distributions. We resort to importance sampling (IS) to estimate the integrals, and thus translate the problem to be how to find a parametric approximation of the posterior. To capture the multimodal structure in the posterior, we initialize a mixture proposal distribution and then tailor its parameters elaborately to make it resemble the posterior to the greatest extent possible. We use the effective sample size (ESS) calculated based on the IS draws to measure the degree of approximation. The bigger the ESS is, the better the proposal resembles the posterior. A difficulty within this tailoring operation lies in the adjustment of the number of mixing components in the mixture proposal. Brute force methods just preset it as a large constant, which leads to an increase in the required computational resources. We provide an iterative delete/merge/add process, which works in tandem with an expectation-maximization step to tailor such a number online. The efficiency of our proposed method is tested via both simulation studies and real exoplanet data analysis.

79 ASTRONOMY AND ASTROPHYSICS↗

Smart Scattering Scanning Near-Field Optical Microscopy

Scattering scanning near-field optical microscopy (s-SNOM) provides spectroscopic imaging from molecular to quantum materials with few nanometer deep subdiffraction limited spatial resolution. However, in its conventional implementation s-SNOM is slow to effectively acquire a series of spatio-spectral images, especially with large fields of view. This problem is further exacerbated for weak resonance contrast or when using light sources with limited spectral irradiance. Indeed, the generally limited signal-to-noise ratio prevents sampling a weak signal at the Nyquist sampling rate. Here, we demonstrate how acquisition time and sampling rate can be significantly reduced by using compressed sampling, matrix completion, and adaptive random sampling, while maintaining or even enhancing the physical or chemical image content. We use fully sampled real data sets of molecular, biological, and quantum materials as ground-truth physical data and show how deep under-sampling with a corresponding reduction of acquisition time by 1 order of magnitude or more retains the core s-SNOM image information. We demonstrate that a sampling rate of up to 6× smaller than the Nyquist criterion can be applied, which would provide a 30-fold reduction in the data required under typical experimental conditions. Furthermore, our smart s-SNOM approach is generally applicable and provides systematic full spatio-spectral s-SNOM imaging with a large field of view at high spectral resolution and reduced acquisition time.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Laser dissection sampling modes for direct mass spectral analysis [using a hybrid optical microscopy/laser ablation liquid vortex capture/electrospray ionization system

Here, laser microdissection coupled directly with mass spectrometry provides the capability of on-line analysis of substrates with high spatial resolution, high collection efficiency, and freedom on shape and size of the sampling area. Establishing the merits and capabilities of the different sampling modes that the system provides is necessary in order to select the best sampling mode for characterizing analytically challenging samples. The capabilities of laser ablation spot sampling, laser ablation raster sampling, and laser 'cut and drop' sampling modes of a hybrid optical microscopy/laser ablation liquid vortex capture electrospray ionization mass spectrometry system were compared for the analysis of single cells and tissue. Single Chlamydomonas reinhardtii cells were monitored for their monogalactosyldiacylglycerol (MGDG) and diacylglyceryltrimethylhomo-Ser (DGTS) lipid content using the laser spot sampling mode, which was capable of ablating individual cells (4-15 m) even when agglomerated together. Turbid Allium Cepa cells (150 m) having unique shapes difficult to precisely measure using the other sampling modes could be ablated in their entirety using laser raster sampling. Intact microdissections of specific regions of a cocaine-dosed mouse brain tissue were compared using laser 'cut and drop' sampling. Since in laser 'cut and drop' sampling whole and otherwise unmodified sections are captured into the probe, 100% collection efficiencies were achieved. Laser ablation spot sampling has the highest spatial resolution of any sampling mode, while laser ablation raster sampling has the highest sampling area adaptability of the sampling modes. In conclusion, laser ablation spot sampling has the highest spatial resolution of any sampling mode, useful in this case for the analysis of single cells. Laser ablation raster sampling was best for sampling regions with unique shapes that are difficult to measure using other sampling modes. Laser 'cut and drop' sampling can be used for cases where the highest sensitivity is needed, for example, monitoring drugs present in trace amounts in tissue.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

SAChES: Scalable Adaptive Chain-Ensemble Sampling.

We present the development of a parallel Markov Chain Monte Carlo (MCMC) method called SAChES, Scalable Adaptive Chain-Ensemble Sampling. This capability is targed to Bayesian calibration of com- putationally expensive simulation models. SAChES involves a hybrid of two methods: Differential Evo- lution Monte Carlo followed by Adaptive Metropolis. Both methods involve parallel chains. Differential evolution allows one to explore high-dimensional parameter spaces using loosely coupled (i.e., largely asynchronous) chains. Loose coupling allows the use of large chain ensembles, with far more chains than the number of parameters to explore. This reduces per-chain sampling burden, enables high-dimensional inversions and the use of computationally expensive forward models. The large number of chains can also ameliorate the impact of silent-errors, which may affect only a few chains. The chain ensemble can also be sampled to provide an initial condition when an aberrant chain is re-spawned. Adaptive Metropolis takes the best points from the differential evolution and efficiently hones in on the poste- rior density. The multitude of chains in SAChES is leveraged to (1) enable efficient exploration of the parameter space; and (2) ensure robustness to silent errors which may be unavoidable in extreme-scale computational platforms of the future. This report outlines SAChES, describes four papers that are the result of the project, and discusses some additional results.

97 MATHEMATICS AND COMPUTING↗

Mars 2020 Rover Adaptive Caching Assembly: Caching Martian Samples for Potential Earth Return

The Adaptive Caching Assembly, part of the Sampling and Caching System on the Mars 2020 Rover, consists of multiple stations that together process sample tubes containing collected Martian material, either rock cores or soil samples, and prepares hermetically-sealed sample tubes for caching on the surface of Mars. There are 7 active degrees-of-freedom, as well as a large number of passive mechanisms within the Adaptive Caching Assembly that must operate in extreme Mars conditions (i.e., temperature and pressure). Hardware cleanliness requirements significantly drove design, assembly, and test operations of the Adaptive Caching Assembly, and were found to adversely affect hardware in some cases such that late design changes and revised cleanliness operations had to be implemented. While Adaptive Caching Assembly hardware was designed to accommodate dust, testing in a representative environment is important to validate functionality is not compromised.

Silverman, Milo↗

Mars 2020 Rover Adaptive Caching Assembly: Caching Martian Samples for Potential Earth Return

The Adaptive Caching Assembly (ACA) is part of the Sampling and Caching System on the Mars 2020 Perseverance Rover, and consists of multiple stations that process, hermetically seal, and store sample tubes containing collected Martian material, either rock cores or regolith samples, in preparation for caching on the surface of Mars. The ACA stations consist of seven active degrees-of-freedom, as well as a large number of passive mechanisms that must operate in extreme Mars temperature and pressure conditions. A robotic arm within the Rover manipulates the sample tubes between ACA stations as part of an end-to-end sampling sequence, and utilizes a compliant end effector to accommodate misalignments during station interactions. Stringent hardware cleanliness requirements were dictated to ensure collected samples would not be compromised, which significantly impacted the design, assembly, and test operations of the ACA. Three ACAs were assembled to support ground testing and flight operations, which were exposed to environmental testing to validate functionality in Mars-like conditions. A number of challenges existed from design through test, including volume constraints, mechanism controllability and operation, the effects of tight tolerances, and cleanliness requirements.

Lin, Justin↗