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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.

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At least 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
NASA NTRS2021

Three-dimensional estimation of deciduous forest canopy structure and leaf area using multi-directional, leaf-on and leaf-off airborne lidar data

Airborne laser scanning (ALS) has been widely used to map gap probability and leaf area index (LAI) distribution at plot and landscape scales. As an indirect measurement, most ALS methods to estimate LAI combine waveform or point density information with supporting field measurements such as the leaf angle distribution, gap probability, or direct LAI measures. The development of a more independent estimation approach would facilitate more widespread use of existing ALS data to investigate patterns of forest structure and build realistic 3-D vegetation scenes to simulate remote sensing imagery and energy balance. Here, we develop a data processing workflow (named PVlad) using ALS point cloud apparent reflectance to estimate LAI and voxel-based leaf area density (LAD), aiming to reduce the need for associated field measurements such as the gap probability. The adaptation of the path volume (PV) concept derived from apparent reflectance integrates information from multi-directional ALS pulses, and quantifies the percentage exploration of each voxel for classification and occlusion correction, such that rigorous volumetric sampling approaches can be developed to derive LAI and LAD. The PVlad workflow was applied to discrete-return lidar data (Riegl VQ480i) acquired by NASA Goddard's LiDAR, Hyperspectral and Thermal Imager (G-LiHT) Airborne Imager during leaf-on (summer) and leaf-off (spring) conditions at the Smithsonian Environmental Research Center (SERC). The estimates of LAI and LAD captured structural differences between mature, logged, and intermediate-aged stands over eight deciduous forest plots. The derived LAI values were compared to field litter collection measurements, and the derived LAD vertical distribution was compared to the output of the VoxLAD model using terrestrial laser scan (TLS) field survey data. Using voxel sizes ranging from 0.5 m to 5 m, overall LAI estimation showed linear fitting coefficient bias and for 1 and 2 m voxel sizes, and vertical LAD distribution showed strong correlation with and for 0.5 and 1m voxel sizes. For every forest stand, upper-canopy LAD had a low variance for voxel sizes of ≤ . Application of PVlad to the G-LiHT and other similar ALS data archives enables the development of fine-resolution LAI map products, including voxelization of LAD for ecosystem science and radiative transfer simulations of remote sensing imagery or surface energy balance.

Tiangang Yin↗
NASA NTRSDate not supplied

Advancing Autonomy in Distributed Space Systems: Insights From on-Orbit Testing with the Starling 1.0 Mission

Autonomous decision-making is crucial for enhancing mission effectiveness in Distributed Space Systems (DSS), particularly in multi-spacecraft operations where communication constraints and mission complexity pose challenges. The Distributed Spacecraft Autonomy (DSA) team at NASA’s Ames Research Center is advancing autonomy in DSS through five key technical areas: distributed resource and task management, reactive operations, system modeling and simulation, human-swarm interaction, and ad hoc network communications. The DSA experiment onboard the Starling 1.0 Mission showcases collaborative resource allocation for multi-point science data collection with four small spacecraft. Autonomy in decision-making is highlighted as a crucial factor for multi-spacecraft missions, enabling spacecraft to operate independently, reducing reliance on ground control. This capability is particularly significant for future deep-space missions, where communication delays and limited data transmission capacity make traditional command and control approaches impractical. This demonstration focuses on a GPS Channel Selection Experiment, leveraging emergent capabilities like "shared sampling" and "simultaneous sampling" to optimize channel selection across the spacecraft swarm. The experiment aims to capture ionospheric phenomena such as the Equatorial Ionization Anomaly and Polar Patches. The DSA system's autonomous reconfiguration ability is showcased, emphasizing its adaptability to natural phenomena without significant integration efforts. The GPS Channel Selection Experiment utilizes a dual-band GPS receiver to estimate plasma density in the ionosphere. Explorative and exploitative channel selections are employed based on the nature of observed phenomena. The performance of DSA algorithms is evaluated in terms of optimal channel allocations and responsiveness to changes in observed features. The DSA Flight Software utilizes the Core Flight System (cFS) framework, ensuring compatibility with the Starling 1.0 flight mission software. DSA showcases results from RTI’s Connext DDS Micro communication middleware, enabling message routing over the Ad-Hoc Network of Starling 1.0. This paper provides a comprehensive overview of the DSA experiment's initial results, emphasizing the advancements in autonomy for Distributed Space Systems and the successful collaboration with the Starling 1.0 mission.

Caleb Ashmore Adams↗
NASA NTRS1981

Additional uses of the facility

The adaptability and utility of the Orbiting Quarantine Facility (OQF) for purposes other than the quarantine mission are considered. One option in the quarantine testing protocol calls for performing a long-term, complete study of the Martian sample in space, rather than releasing the sample to an Earth-based laboratory. It is also possible that the studies prescribed in the protocol will not detect any life forms, in which case the mission will be completed as early as 60 to 90 days from the initial receipt of the Martian sample. It is because of this latter possibility that options for other uses of the facility were considered.

Source record↗
NASA NTRS2002

Mass Spectrometers in Deep Space Missions

Mass spectrometers have been included in the payloads of several deep space missions over the past three decades. Our laboratory has designed and developed mass spectrometers for the Galileo Probe into the atmosphere of Jupiter, the Pioneer Venus Orbiter, the Cassini Orbiter Mission to Saturn, the Cassini/Huygens Probe Mission to Saturn's moon Titan, the Nozomi Mission to Mars, and most recently the CONTOUR comet nucleus flyby mission. Each mission has required attention to miniaturization, autonomous sampling, and consideration of the special hazards and measurement requirements of the target environment. Development ongoing in our laboratory includes further miniaturization, improved performance in the areas of sensitivity and precision for the important isotope measurements, and adaptation for the unusual environments to be encountered in locations such as the surface or subsurface of Europa or Mars. Various aspects of both the technical implementation of these delivered and planned experiments and the science drivers will be described.

Mahaffy, Paul↗
NASA NTRS2005

An Ensemble Approach to Building Mercer Kernels with Prior Information

This paper presents a new methodology for automatic knowledge driven data mining based on the theory of Mercer Kernels, which are highly nonlinear symmetric positive definite mappings from the original image space to a very high, possibly dimensional feature space. we describe a new method called Mixture Density Mercer Kernels to learn kernel function directly from data, rather than using pre-defined kernels. These data adaptive kernels can encode prior knowledge in the kernel using a Bayesian formulation, thus allowing for physical information to be encoded in the model. Specifically, we demonstrate the use of the algorithm in situations with extremely small samples of data. We compare the results with existing algorithms on data from the Sloan Digital Sky Survey (SDSS) and demonstrate the method's superior performance against standard methods. The code for these experiments has been generated with the AUTOBAYES tool, which automatically generates efficient and documented C/C++ code from abstract statistical model specifications. The core of the system is a schema library which contains templates for learning and knowledge discovery algorithms like different versions of EM, or numeric optimization methods like conjugate gradient methods. The template instantiation is supported by symbolic-algebraic computations, which allows AUTOBAYES to find closed-form solutions and, where possible, to integrate them into the code.

Srivastava, Ashok N.↗
NASA NTRS2009

A Local Scalable Distributed Expectation Maximization Algorithm for Large Peer-to-Peer Networks

This paper offers a local distributed algorithm for expectation maximization in large peer-to-peer environments. The algorithm can be used for a variety of well-known data mining tasks in a distributed environment such as clustering, anomaly detection, target tracking to name a few. This technology is crucial for many emerging peer-to-peer applications for bioinformatics, astronomy, social networking, sensor networks and web mining. Centralizing all or some of the data for building global models is impractical in such peer-to-peer environments because of the large number of data sources, the asynchronous nature of the peer-to-peer networks, and dynamic nature of the data/network. The distributed algorithm we have developed in this paper is provably-correct i.e. it converges to the same result compared to a similar centralized algorithm and can automatically adapt to changes to the data and the network. We show that the communication overhead of the algorithm is very low due to its local nature. This monitoring algorithm is then used as a feedback loop to sample data from the network and rebuild the model when it is outdated. We present thorough experimental results to verify our theoretical claims.

Bhaduri, Kanishka↗
NASA NTRSDate not supplied

Biological Research and Space Health Enabled by Machine Learning to Support Deep Space Missions

A key science goal of the NASA “Moon to Mars” campaign is to understand how biology responds to the Lunar, Martian, and deep space environments in order to advance fundamental knowledge and support human space missions. Through artificial intelligence (AI) and machine learning (ML), a paradigm shift has begun in space biosciences and engineered astronaut health systems, to enable Earth-independence and mission operations autonomy. We describe current AI/ML methods to support 1) fundamental biology, 2) in situ analytics, 3) high performance computing, 4) automated science, 5) self-driving labs, 6) remote data management, 7) integrated mission biomonitoring, and 8) a Precision Space Health system. AI/ML approaches that can be integrated to support these domains include active learning, explainable AI, adaptive learning, causal inference, knowledge graphs, federated learning, transfer learning, and large language models. Finally, we present results from several current ML projects that are underway in the space biology field to address key challenges of small sample n, high feature count, heterogeneity, and sparse data. These include 1) connecting omics to phenotypic data using an ensemble model to infer causality of rodent liver health disruption, 2) usage of explainable ML to interrogate muscular underpinnings of muscle atrophy, 3) ML models analyzing and determining directed acyclic graphs of human health risk leveraging rodent bone datasets, 4) usage of large pre-trained models connecting biomedical knowledgebases with small spaceflight datasets to understand gene-to-gene interactions, and 5) a suite of benchmarked open science datasets enabling programmers to identify best algorithms to answer space biology questions.

space biology↗
NASA NTRS1994

On-line, adaptive state estimator for active noise control

Dynamic characteristics of airframe structures are expected to vary as aircraft flight conditions change. Accurate knowledge of the changing dynamic characteristics is crucial to enhancing the performance of the active noise control system using feedback control. This research investigates the development of an adaptive, on-line state estimator using a neural network concept to conduct active noise control. In this research, an algorithm has been developed that can be used to estimate displacement and velocity responses at any locations on the structure from a limited number of acceleration measurements and input force information. The algorithm employs band-pass filters to extract from the measurement signal the frequency contents corresponding to a desired mode. The filtered signal is then used to train a neural network which consists of a linear neuron with three weights. The structure of the neural network is designed as simple as possible to increase the sampling frequency as much as possible. The weights obtained through neural network training are then used to construct the transfer function of a mode in z-domain and to identify modal properties of each mode. By using the identified transfer function and interpolating the mode shape obtained at sensor locations, the displacement and velocity responses are estimated with reasonable accuracy at any locations on the structure. The accuracy of the response estimates depends on the number of modes incorporated in the estimates and the number of sensors employed to conduct mode shape interpolation. Computer simulation demonstrates that the algorithm is capable of adapting to the varying dynamic characteristics of structural properties. Experimental implementation of the algorithm on a DSP (digital signal processing) board for a plate structure is underway. The algorithm is expected to reach the sampling frequency range of about 10 kHz to 20 kHz which needs to be maintained for a typical active noise control application.

Lim, Tae W.↗
NASA NTRS1981

AgRISTARS: Foreign commodity production forecasting. The 1980 US corn and soybeans exploratory experiment

The U.S. corn and soybeans exploratory experiment is described which consisted of evaluations of two technology components of a production forecasting system: classification procedures (crop labeling and proportion estimation at the level of a sampling unit) and sampling and aggregation procedures. The results from the labeling evaluations indicate that the corn and soybeans labeling procedure works very well in the U.S. corn belt with full season (after tasseling) LANDSAT data. The procedure should be readily adaptable to corn and soybeans labeling required for subsequent exploratory experiments or pilot tests. The machine classification procedures evaluated in this experiment were not effective in improving the proportion estimates. The corn proportions produced by the machine procedures had a large bias when the bias correction was not performed. This bias was caused by the manner in which the machine procedures handled spectrally impure pixels. The simulation test indicated that the weighted aggregation procedure performed quite well. Although further work can be done to improve both the simulation tests and the aggregation procedure, the results of this test show that the procedure should serve as a useful baseline procedure in future exploratory experiments and pilot tests.

Malin, J. T.↗
NASA NTRS1987

Design of force/position controllers for manipulators

The paper presents simple methods for the design of adaptive force and position controllers for robot manipulators within the hybrid control architecture. The force controller is composed of an adaptive PID feedback controller, an auxiliary signal and a force feedforward term, and achieves tracking of desired force setpoints in the constraint directions. The position controller consists of adaptive feedback and feedforward controllers and an auxiliary signal; and accomplishes tracking of desired position trajectories in the free directions. The controllers are capable of compensating for dynamic cross-couplings that exist between the position and force control loops in the hybrid control architecture. The adaptive controllers do not require knowledge of the complex dynamic model or parameter values of the manipulator or the environment. The proposed control schemes are computationally fast and suitable for implementation in on-line control with high sampling rates.

Seraji, H.↗
NASA NTRS1987

Adaptive hybrid control of manipulators

Simple methods for the design of adaptive force and position controllers for robot manipulators within the hybrid control architecuture is presented. The force controller is composed of an adaptive PID feedback controller, an auxiliary signal and a force feedforward term, and it achieves tracking of desired force setpoints in the constraint directions. The position controller consists of adaptive feedback and feedforward controllers and an auxiliary signal, and it accomplishes tracking of desired position trajectories in the free directions. The controllers are capable of compensating for dynamic cross-couplings that exist between the position and force control loops in the hybrid control architecture. The adaptive controllers do not require knowledge of the complex dynamic model or parameter values of the manipulator or the environment. The proposed control schemes are computationally fast and suitable for implementation in on-line control with high sampling rates.

Seraji, H.↗
NASA NTRS2003

Autotrophic Ecosystems on the Early Earth

Ophiolite sequences, sections of lower oceanic crust and upper mantle that have been thrust onto continental craton, are located in northern and central California and provide easily accessible areas that serve as good analogs for similar, more extensive areas of the early Earth. We have begun investigating and characterizing these sites in order to understand better the processes that may be responsible for the water chemistry, mineralogy and biology of similar environments on the early Earth. The geophysical and geochemical processes in these terranes provide niches for unique communities of extremeophiles and likely provide a good analog to the location that first gave rise to life on Earth. The ophiolites found in northern and central California include the Trinity, Josephine, Coast Range and Point Sal, all of which are approximately 160 million years old. Fluids from serpentinizing springs are generally alkaline with high pH and H2 contents, indicating that the mafic rock compositions control the fluid composition through water-rock reactions during relatively low-grade hydrothermal processes. There are significant amounts of primary mineralogy remaining in the rocks, meaning that substantial alteration processes are still occurring in these terranes. The general reaction for serpentinization of olivine is given by one of the authors. olivine + H2O = serpentine + brucite + magnetite + H2. We have analyzed the mineralogical composition of several rock samples collected from the Coast Range Ophiolite near Clear Lake, CA by electron microprobe. The remnant primary mineralogy is fairly urnform in composition, with an olivine composition of Fo(sub 90), and with pyroxene compositions of En(sub 90) for orthopyroxene and En(sub 49)Wo(sub 48)Fs(sub 03) for the clinopyroxene. Other primary phases observed include chromites and other spinels. Examination of petrographic thin sections reveals that serpentinization reactions have occurred in these locations. The serpentine resulting from aqueous alteration of olivine resides in veins that are see to cross cut the primary mineral grains. There are several generations of alteration products, comprised mostly of serpentines that are magnesium rich, with magnetite, brucite and carbonates observed as accessory minerals. The formation of carbonates can be taken to indicate the presence of CO2 in the altering fluids. We collected samples from a spring in the Coast Range Ophiolite in order to determine whether the geochemical environment serves as a habitat for chemotrophic microorganisms. DNA was extracted from the sediment samples and the 16s rRNA gene was PCR amplified using universal Archaeal primers. Denaturing gradient gel electrophoresis (DGGE) was used to determine the community of Archaea thriving in these samples. Our results indicate that there were 8 different genera of Archaea from a single sample. A sequence was obtained from one of these eight. The sequence is of an organism similar to Halorubrum tibetense, and alkalophilic Archaeon. This result suggests that these environments are likely hosts for communities of organisms that are adapted for the unique chemistry provided by the alkaline spring.

Schulte, M.↗
NASA NTRS2007

An Adaptive Cross-Correlation Algorithm for Extended-Scene Shack-Hartmann Wavefront Sensing

This viewgraph presentation reviews the Adaptive Cross-Correlation (ACC) Algorithm for extended scene-Shack Hartmann wavefront (WF) sensing. A Shack-Hartmann sensor places a lenslet array at a plane conjugate to the WF error source. Each sub-aperture lenslet samples the WF in the corresponding patch of the WF. A description of the ACC algorithm is included. The ACC has several benefits; amongst them are: ACC requires only about 4 image-shifting iterations to achieve 0.01 pixel accuracy and ACC is insensitive to both background light and noise much more robust than centroiding,

Terrestrial Planet Finder (TPF)↗
NASA NTRS2012

NASA Tech Briefs, June 2012

Topics covered include: iGlobe Interactive Visualization and Analysis of Spatial Data; Broad-Bandwidth FPGA-Based Digital Polyphase Spectrometer; Small Aircraft Data Distribution System; Earth Science Datacasting v2.0; Algorithm for Compressing Time-Series Data; Onboard Science and Applications Algorithm for Hyperspectral Data Reduction; Sampling Technique for Robust Odorant Detection Based on MIT RealNose Data; Security Data Warehouse Application; Integrated Laser Characterization, Data Acquisition, and Command and Control Test System; Radiation-Hard SpaceWire/Gigabit Ethernet-Compatible Transponder; Hardware Implementation of Lossless Adaptive Compression of Data From a Hyperspectral Imager; High-Voltage, Low-Power BNC Feedthrough Terminator; SpaceCube Mini; Dichroic Filter for Separating W-Band and Ka-Band; Active Mirror Predictive and Requirement Verification Software (AMP-ReVS); Navigation/Prop Software Suite; Personal Computer Transport Analysis Program; Pressure Ratio to Thermal Environments; Probabilistic Fatigue Damage Program (FATIG); ASCENT Program; JPL Genesis and Rapid Intensification Processes (GRIP) Portal; Data::Downloader; Fault Tolerance Middleware for a Multi-Core System; DspaceOgreTerrain 3D Terrain Visualization Tool; Trick Simulation Environment 07; Geometric Reasoning for Automated Planning; Water Detection Based on Color Variation; Single-Layer, All-Metal Patch Antenna Element with Wide Bandwidth; Scanning Laser Infrared Molecular Spectrometer (SLIMS); Next-Generation Microshutter Arrays for Large-Format Imaging and Spectroscopy; Detection of Carbon Monoxide Using Polymer-Composite Films with a Porphyrin-Functionalized Polypyrrole; Enhanced-Adhesion Multiwalled Carbon Nanotubes on Titanium Substrates for Stray Light Control; Three-Dimensional Porous Particles Composed of Curved, Two-Dimensional, Nano-Sized Layers for Li-Ion Batteries 23 Ultra-Lightweight; and Ultra-Lightweight Nanocomposite Foams and Sandwich Structures for Space Structure Applications.

Source record↗
NASA NTRS2022

An Overview of Contamination Control for the James Webb Space Telescope Launch Campaign

The James Webb Space Telescope (JWST) is a large, infrared space telescope operating at Lagrange point 2. JWST is a joint effort between NASA, ESA, and CSA and was launched from the Centre Spatial Guyanais (CSG) on an Ariane 5 rocket in December 2021. The three-month launch campaign utilized enhanced contamination controls to meet JWST’s strict cleanliness requirements. Prior to launch, JWST was permitted to only be exposed to ISO Class 7 cleanrooms, whereas the processing facilities at CSG are ISO Class 8. NASA, ESA, Arianespace, and CNES implemented temporary upgrades to the nominal contamination control operations for the launch campaign unique to JWST, including the use of vetted, portable High Efficiency Particulate Air (HEPA) filter walls, pre-entrance cleanliness acceptance surveys of each facility and the intra-plant transporter, tightened cleanroom protocols, upgraded garmenting and laundering techniques, cleaning of Self-Contained Atmospheric Protection Ensemble (SCAPE) suits, increased maintenance, staffed pre-cleaning stations, adaptation of the house purge network, and a contamination control enclosure atop the Ariane 5 launcher prior to fairing encapsulation. The Ariane 5 fairing interior and Vehicle Equipment Bay membrane also received multiple cleanings, detailed inspections, and verification sampling to achieve necessary cleanliness levels. The fairing itself was specially sealed to protect the inner environment with just a small, door porthole accessible via diving board for final closeout of the purge interface. All of these enhancements together allowed JWST to meet its contamination requirements for launch, ensuring successful post-separation deployments and mission science.

Contamination Control↗
NASA NTRSDate not supplied

Spacecraft Material Characterization Using Reflectance Spectra Extracted from RGB/IR Color Images

The space environment is detrimental to the exterior of the spacecraft and imposes stringent requirements on spacecraft materials. Space materials are often expected to perform for 15-20 years in the harsh space environment without significant degradation of their optical, electrical, mechanical and thermal properties. Further, as commercial activities increase in the space domain, development of predictive capability for material evolution is critical for agile adaption of novel materials. Therefore, it is very important to understand the effects of the space environments on the spacecraft materials. The Materials on the International Space Station Experiment Flight Facility (MISSE-FF) has flown numerous material samples to investigate the effect of LEO space weather exposure on the performance and durability of materials and devices. We are manifest on the MISSE-16 mission, scheduled to launch in June 2022, to fly fifteen novel and well-characterized materials in the LEO environment for a duration of six months. Changes in spectral reflectivity will be measured in real time throughout the mission with an RGB/IR camera. These time-resolved data will function as a "space-truth" reference for our team's ongoing laboratory-based space weather-material interaction experiments. Correlation of the MISSE-16 data with extensive ground testing of duplicate samples under simulated space weather conditions will enable development of fundamental chemical models for material degradation. This paper discusses preliminary results from the ground test campaign to collect the RGB/IR images for pristine and damaged materials and the development of machine learning algorithms to extract reflectance spectra from the color images.

Jainisha R. Shah↗
NASA NTRSDate not supplied

Overview of Contamination Control for the James Webb Space Telescope Launch Campaign

The James Webb Space Telescope (JWST) is a large, infrared space telescope operating at Lagrange point 2. JWST is a joint effort between NASA, ESA, and CSA and was launched from the Centre Spatial Guyanais (CSG) on an Ariane 5 rocket in December 2021. The three-month launch campaign utilized enhanced contamination controls to meet JWST’s strict cleanliness requirements. Prior to launch, JWST was permitted to only be exposed to ISO Class 7 cleanrooms, whereas the processing facilities at CSG are ISO Class 8. NASA, ESA, Arianespace, and CNES implemented temporary upgrades to the nominal contamination control operations for the launch campaign unique to JWST, including the use of vetted, portable High Efficiency Particulate Air (HEPA) filter walls, pre-entrance cleanliness acceptance surveys of each facility and the intra-plant transporter, tightened cleanroom protocols, upgraded garmenting and laundering techniques, cleaning of Self-Contained Atmospheric Protection Ensemble (SCAPE) suits, increased maintenance, staffed pre-cleaning stations, adaptation of the house purge network, and a contamination control enclosure atop the Ariane 5 launcher prior to fairing encapsulation. The Ariane 5 fairing interior and Vehicle Equipment Bay membrane also received multiple cleanings, detailed inspections, and verification sampling to achieve necessary cleanliness levels. The fairing itself was specially sealed to protect the inner environment with just a small, doored porthole accessible via diving board for final closeout of the purge interface. All these enhancements together allowed JWST to meet its contamination requirements for launch, ensuring successful post-separation deployments and mission science.

James Webb Space Telescope↗
NASA NTRS2022

Overview of Contamination Control for the James Webb Space Telescope Launch Campaign

The James Webb Space Telescope (JWST) is a large, infrared space telescope operating at Lagrange point 2. JWST is a joint effort between NASA, ESA, and CSA and was launched from the Centre Spatial Guyanais (CSG) on an Ariane 5 rocket in December 2021. The three-month launch campaign utilized enhanced contamination controls to meet JWST’s strict cleanliness requirements. Prior to launch, JWST was permitted to only be exposed to ISO Class 7 cleanrooms, whereas the processing facilities at CSG are ISO Class 8. NASA, ESA, Arianespace, and CNES implemented temporary upgrades to the nominal contamination control operations for the launch campaign unique to JWST, including the use of vetted, portable High Efficiency Particulate Air (HEPA) filter walls, pre-entrance cleanliness acceptance surveys of each facility and the intra-plant transporter, tightened cleanroom protocols, upgraded garmenting and laundering techniques, cleaning of Self-Contained Atmospheric Protection Ensemble (SCAPE) suits, increased maintenance, staffed pre-cleaning stations, adaptation of the house purge network, and a contamination control enclosure atop the Ariane 5 launcher prior to fairing encapsulation. The Ariane 5 fairing interior and Vehicle Equipment Bay membrane also received multiple cleanings, detailed inspections, and verification sampling to achieve necessary cleanliness levels. The fairing itself was specially sealed to protect the inner environment with just a small, doored porthole accessible via diving board for final closeout of the purge interface. All these enhancements together allowed JWST to meet its contamination requirements for launch, ensuring successful post-separation deployments and mission science.

James Webb Space Telescope, launch, contamination,↗