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Spacecraft Fire Safety Predictions using Verified Saffire Model

A model developed using Fire Dynamics Simulator (FDS) that aimed to determine the effect of a fire in a spacecraft was validated by data collected during the Saffire campaign. The model used inlet and outlet temperatures and CO 2 concentrations of the Saffire payload where fire spread was taking place to determine the amount of heat and combustion products that made it into Northrop Grumman’s Cygnus vehicle. The model was then validated using six remote sensors in various places in the vehicle, as well as a far field device (FFD) in the open zenith section that was representative of average vehicle values. The current work focuses on using the model to predict fire safety scenarios. One simulation aimed to determine the fate of HCl, which sticks to surfaces. The model prediction showed that the HCl was removed from the atmosphere rapidly. This compared well against the FFD data in the Saffire VI campaign event where a bottle of 5% HCl was released into the vehicle. An additional simulation where the Environmental Control and Life Support System (ECLSS) was shut off once the FFD reached 5 ppm of HCl showed that HCl stayed in the atmosphere considerably longer. Continuing the simulation with the ECLSS activated and after temperatures returned to their initial conditions, resulted in a rapid removal of HCL similar to that observed in the original HCl release scenario model. Finally, a simulation that used the heat release rate from a lithium-ion battery test to determine the effect it would have on a spacecraft was performed. This simulation used a heat addition rate that is considerably higher than what was determined from the burning of solid fuels in the Saffire campaign and hence produced a non-trivial temperature increase in more locations within the vehicle.

Fire Safety

Model Spread in Tropical Low Cloud Feedback Tied to Overturning Circulation Response to Warming

Among models participating in the Coupled Model Intercomparison Project phase 6 (CMIP6), here we show that the magnitude of the tropical low cloud feedback, which contributes considerably to uncertainty in estimates of climate sensitivity, is intimately linked to tropical deep convection and its effects on the tropical atmospheric overturning circulation. First, a reduction in tropical ascent area and an increased frequency of heavy precipitation result in high cloud reduction and upper-tropospheric drying, which increases longwave cooling and reduces subsidence weakening, favoring low cloud reduction (Radiation-Subsidence Pathway). Second, increased longwave cooling decreases tropospheric stability, which also reduces subsidence weakening and low cloudiness (Stability-Subsidence Pathway). In summary, greater high cloud reduction and upper-tropospheric drying (negative longwave feedback) lead to a more positive cloud feedback among CMIP6 models by contributing to a greater reduction in low cloudiness (positive shortwave feedback). Varying strengths of the two pathways contribute considerably to the intermodel spread in climate sensitivity.

Atmospheric dynamics

Performance Assessment of LunaNet’s Augmented Forward Signal

LunaNet provides a common set of interoperable specifications for communication and position, navigation and time (PNT) services and interfaces soon to be implemented in lunar vicinity. The LunaNet Interoperability Specification (LNIS) provides the design for the GNSS-like Augmented Forward Signal (AFS), which enables orbiting and surface users in lunar space, such as Artemis, to estimate their position, velocity, and time. The specification of AFS defines two orthogonal signal components on a single carrier: the in-phase component (AFS-I), a lower-chip-rate data channel tailored for applications where low SWaP (Size, Weight, and Power) is critical (e.g., IoT devices or search and rescue), and the quadrature component (AFS-Q), a high-chip-rate data-less pilot signal for high-precision, robust lunar navigation and positioning applications. An initial description of AFS was provided in LNIS 2023, with initial analysis results shown in Dafesh 2024 and Dafesh 2025, and the current signal in space description provided in LNIS 2025. As part of NASA's Lunar Communication Relay and Navigation Systems (LCRNS) project, this work expands upon the initial analysis results and proposes a new expanded set of AFS-Q spreading codes that exceed the cross-correlation and autocorrelation sidelobe performance of L1C and other GNSS signals, while providing additional expansion capabilities for future service satellites. A set of 420 codes was selected from a Weil-based code derived from the prime number 10247, which is larger than the 10243 prime number used to derive BeiDou’s B1C Weil sequences. Both the initial set of 210 codes and the expanded set of 420 codes are shown to provide the best cross-correlation of any 10230-chip satellite navigation codes. The performance is demonstrated for hierarchical sets of spreading codes optimized and organized in sets of 30 codes. The work also compares LunaNet’s AFS to terrestrial GNSS signals in terms of acquisition, tracking, and data demodulation performance. Performance is evaluated for receivers that only track the 1.023 MCPS data channel spreading code for low SWaP IoT use cases, as well as for receivers that track both the 1.023 MCPS data channel and the 5.115 MCPS pilot channel spreading code for high-performance use cases. Performance is assessed in the presence of interference and thermal noise. The analysis is performed in terms of expected operating conditions on the lunar surface. Several unique flexibility aspects of the augmented forward signal are described, including the use of the Q channel’s secondary and tertiary codes to enable variable coherent integrations during acquisition. This is compared to GNSS signals such as L5/E5 and MBOC in terms of achievable processing gain for interference mitigation versus acquisition complexity. The work details acquisition and tracking techniques used to optimally acquire and track the primary, secondary, and tertiary codes on the Q channel, as well as acquisition of the I channel spreading code. Acquisition of the 8 ms, Q channel spreading code is also compared to joint acquisition of the I and Q channel primary codes in noise and interference environments

LCRNS

Performance Assessment of LunaNet’s Augmented Forward Signal

LunaNet provides a common set of interoperable specifications for communication and position, navigation and time (PNT) services and interfaces soon to be implemented in lunar vicinity. The LunaNet Interoperability Specification (LNIS) provides the design for the GNSS-like Augmented Forward Signal (AFS), which enables orbiting and surface users in lunar space, such as Artemis, to estimate their position, velocity, and time. The specification of AFS defines two orthogonal signal components on a single carrier: the in-phase component (AFS-I), a lower-chip-rate data channel tailored for applications where low SWaP (Size, Weight, and Power) is critical (e.g., IoT devices or search and rescue), and the quadrature component (AFS-Q), a high-chip-rate data-less pilot signal for high-precision, robust lunar navigation and positioning applications. An initial description of AFS was provided in [1], with initial analysis results shown in [2] and [3] and the current signal in space description provided in [4]. As part of NASA's Lunar Communication Relay and Navigation Systems (LCRNS) project, this work expands upon the initial analysis results and proposes a new expanded set of AFS-Q spreading codes that exceed the cross-correlation and autocorrelation sidelobe performance of L1C and other GNSS signals, while providing additional expansion capabilities for future provider satellites. A set of 420 codes was selected from a Weil-based code derived from the prime number 10247, which is larger than the 10243 prime number used to derive Beidou’s B1C Weil sequences. Both the initial set of 210 codes and the expanded set of 420 codes are shown to provide the best cross-correlation of any 10230-chip satellite navigation codes. The performance is demonstrated for hierarchical sets of spreading codes optimized and organized in sets of 30 codes. The new codes were developed using an optimization approach and correlation methodology described in [5]. The work also compares LunaNet’s AFS to terrestrial GNSS signals in terms of acquisition, tracking, and data demodulation performance. Performance is evaluated for receivers that only track the 1.023 MCPS data channel spreading code for low SWaP IoT use cases, as well as for receivers that track both the 1.023 MCPS data channel and the 5.115 MCPS pilot channel spreading code for high-performance use cases. Performance is assessed in the presence of interference and thermal noise. The analysis is performed in terms of expected operating conditions on the lunar surface. Several unique flexibility aspects of the augmented forward signal are described, including the use of the Q channel’s secondary and tertiary codes to enable variable coherent integrations during acquisition. This is compared to GNSS signals such as L5/E5 and MBOC in terms of achievable processing gain for interference mitigation versus acquisition complexity. The work details acquisition and tracking techniques used to optimally acquire and track the primary, secondary, and tertiary codes on the Q channel, as well as acquisition of the I channel spreading code. Acquisition of the 8 ms Q channel spreading code is also compared to joint acquisition of the I and Q channel primary codes in noise and interference environments.

LCRNS

Early Fire Detection System for Partial and Low Gravity Environments

We present preliminary results on the development of a fire detection system for partial and low gravity environments. A significant challenge is the design of a system with a low false alarm rate. The detection system therefore has to discriminate between combustion particles, cabin, and lunar dust. Aerosol properties are measured and cross referenced to the target detectors at the Gases and Aerosols from Smoldering Polymers (GASP) Laboratory located at the NASA Glenn Research Center. A computational fluid dynamics plume model is also employed to determine the smoke transport properties of the targeted habitats.

Early fire detectioin

Risks of Depress as a Fire Suppression Technique in Spacecraft

Spacecraft are designed to prevent fires through careful material selection and configuration control combined with electrical design controls and isolation of ignition sources. Despite these best efforts, fire risk still exists due to the potential for configuration changes with the introduction of crew and the potential for a ‘failure of imagination’ by designers in anticipating all fuel and ignition sources. Therefore, fire suppression is a critical capability for any crewed spacecraft as a last resort for crew survival. Many spacecraft suppression methods have relied on fire suppressants such as compressed carbon dioxide, nitrogen, and water. A proposed alternative is depressurization of the cabin as a method to extinguish a fire. Limited testing was conducted during Skylab and showed that depress could result in stirring the air flow and aggravating a fire before extinguishing. However, limited information was available on how the test was conducted. To better characterize the approach, testing was conducted at NASA’s White Sands Test Facility to evaluate the effect of depressurization on material extinguishment. The results showed that depressurization does not provide a safe and effective fire suppression capability. The testing approach, results, and conclusions are described and discussed.

Toni Griego

The Solid Surface Combustion Experiment Aboard the USML-1 Mission

AA Experimental results from the five experiments indicate that flame spread rate increases with increasing ambient oxygen content and pressure. An experiment was conducted aboard STS-50/USML-1 in the solid Surface Combustion Experiment (SSCE) hardware for flame spread over a thin cellulosic fuel in a quiescent oxidizer of 35% oxygen/65% nitrogen at 1.0 atm. pressure in microgravity. The USML-1 test was the fourth of five planned experiments for thin fuels, one performed during each of five Space Shuttle Orbiter flights. Data that were gathered include gas- and solid-phase temperatures and motion picture flame images. Observations of the flame are described and compared to theoretical predictions from steady and unsteady models that include flame radiation from CO2 and H2O. Experimental results from the five esperiments indicate that flame spread rate increases with increasing ambient oxygen content and pressure. The brightness of the flame and the visible soot radiation also increase with increasing spread rate. Steady-state numerical predictions of temperature and spread rate and flame structure trends compare well with experimental results near the flame's leading edge while gradual flame evolution is captured through the unsteady model.

Robert A Altenkirch

Advancing Wildfire Monitoring with TEMPO and ML tools: Hourly Smoke and Fire‑Front Mapping and Near‑Surface NO₂ Predictions

Wildfires impose substantial impacts on communities and regions downwind of wildfire smoke. We present a TEMPO‑enabled workflow that generates value‑added Level‑3 smoke‑plume masks and fire‑front maps for large wildfires, such as 2024 Park Fire, using the self‑supervised deep learning system SIT‑FUSE, along with near‑surface NO₂ predictions produced by a foundation model (Microsoft Aurora). We conclude by outlining a roadmap for expanding these capabilities to additional Western U.S. wildfire events and for delivering actionable tools to stakeholders. This open-source, reproducible workflow provides a scalable framework for cross-agency wildfire monitoring to overcome traditional limitations in smoke-cloud discrimination and air-quality forecasting by incorporating TEMPO data and beyond.

Xiaohua Pan

Timing the Flames: Geostationary Satellite Detection of Diurnally Shifting Stubble Burning in Northwestern India

Post-monsoon open-field stubble burning in northwestern (NW) India—a key agricultural region known as the “breadbasket”—is a longstanding practice used to clear fields. Satellite observations spanning over two decades have revealed significant upward trends in crop production, vegetative greenness, and the frequency of post-harvest fires, with this last contributing to hazardous air quality during the peak burning season (mid-October to mid-November). Since 2022, thermal anomaly data from Aqua-MODIS and SNPP-VIIRS sensors have shown a sharp decline in reported fire events—an observation that contrasts starkly with the concurrent rise in regional aerosol loading detected from space. This apparent discrepancy became particularly pronounced in 2024–2025, prompting a closer examination using high-temporal-resolution imagery from the Advanced Meteorological Imager (AMI) on the geostationary satellite GEO-KOMPSAT-2A. These observations revealed a clear spike in fire-related signals occurring around and after 4:00 p.m. local time, i.e., outside the typical noon to 2:00 p.m. detection window of the MODIS and VIIRS. A fire detection algorithm exploiting the fire-sensitive shortwave-infrared 3.8 μm signal and its contrast to 11.2 μm infrared observations is designed to adopt AMI observations and applied to its multi-year observations (2019–2025). The resulting fire dataset unambiguously shows a gradual shift in stubble burning activity toward the late afternoon hours beginning in 2022 which is underreported by polar-orbiting satellites. The orbital drift of NASA’s MODIS sensor on the Aqua platform allows detection of some of the gradually shifting fires during afternoon hours, but the MODIS still misses a large number of fires occurring around and after 4 p.m. The AMI’s relatively coarse spatial resolution (~4 km), a consequence of its slant viewing geometry over NW India, imposes inherent limitations on quantifying the full extent of fire occurrences. The operational air quality forecasting models currently assimilate satellite fire detections predominantly captured during early afternoon overpasses of the MODIS and VIIRS. The temporal shift in fire activity complicates such forecast, leading to a substantial underestimation of emissions. Intense stubble burning and the resulting air pollution highlight the need for effective crop residue management practices for mitigating the frequency of open biomass burning and thereby reducing episodic degradation of air quality and its associated public health and economic impacts.

post-monsoon stubble burning; northwestern India;

Fire-Resistant Textile Development for Exploration Vehicles With Enriched-Oxygen Cabin Environments

Material selection is a key part of the National Aeronautics and Space Administration (NASA) spacecraft fire safety management plan. Non-flammable textiles are necessary to ensure large-scale flame propagation events do not occur inside a spacecraft. An increased use of textiles and other softgood material is crucial to the pursuit of exploration spaceflight to reduce mass and volume. Exploration spaceflight missions benefit from enriched oxygen cabin environments (>21% O2) by allowing a reduced prebreathe protocol before Extravehicular Activity (EVA). However, materials become exponentially more flammable the higher the O2 levels become. Recent testing within the agency has revealed the lack of commercial-off-the-shelf (COTS) materials that can meet safety requirements in oxygen-enriched environments. Most of the fibers and textiles developed during Apollo (100% O2 cabin environment) and Skylab (>70% O2 cabin environment) are no longer commercially available due to those Programs ending and the discontinuation of raw materials or closure of the original manufacturers. As NASA returns to higher oxygen concentrations inside spacecraft, non-flammable textile development efforts have begun to meet the agency’s needs. This paper discusses those efforts including overall fire safety approach, priorities, interactions with industry, flammability testing and expected challenges.

Karim Aly

Flammability Test Method for Materials Intended for Use as Fire Barriers in Crewed Habitats

In some crewed-spacecraft applications, onboard materials are intentionally selected to function as hazard control barriers to prevent powered hardware and/or ignited flammable items from igniting nearby flammable materials by acting as non-breaching, non-flammable containment (e.g., cargo transfer bags, zero gravity stowage racks, and jettison stowage bags on the International Space Station). Historically, flammability self-extinguishment testing of broad acreage or outermost layer materials alone was believed to be sufficient to verify overall flammability compliance. Though required, testing on design features such as threaded seams and zippers was not performed due to the incorrect assumption that flammability performance would not be impacted. However, recent coupon level testing of layups and configurations consisting of multiple materials have revealed that these features may be more susceptible to ignition and fire propagation than the bulk material. Additionally, configurational coupon ignition and propagation testing does not explicitly determine a material’s ability to provide protection to vulnerable flammable hardware. The need to evaluate this gap in assessing material or layup effectiveness as fire barriers between ignition sources and flammable materials led to the development of a new configuration-based fire barrier test. Test setup, relevant configurations, and test validation are discussed. The new barrier test method establishes a configuration for the test apparatus, identifies a conservative ignitor configuration, and defines pass/fail criteria. Test setup, relevant configurations, and test validation are discussed.

Susana Harper

Fire-Resistant Textile Development for Exploration Vehicles With Enriched-Oxygen Cabin Environments

Material selection is a key part of the National Aeronautics and Space Administration (NASA) spacecraft fire safety management plan. Non-flammable textiles are necessary to ensure large-scale flame propagation events do not occur inside a spacecraft. An increased use of textiles and other softgood material is crucial to the pursuit of exploration spaceflight to reduce mass and volume. Exploration spaceflight missions benefit from enriched oxygen cabin environments (>21% O2) by allowing a reduced prebreathe protocol before Extravehicular Activity (EVA). However, materials become exponentially more flammable the higher the O2 levels become. Recent testing within the agency has revealed the lack of commercial-off-the-shelf (COTS) materials that can meet safety requirements in oxygen-enriched environments. Most of the fibers and textiles developed during Apollo (100% O2 cabin environment) and Skylab (>70% O2 cabin environment) are no longer commercially available due to those Programs ending and the discontinuation of raw materials or closure of the original manufacturers. As NASA returns to higher oxygen concentrations inside spacecraft, non-flammable textile development efforts have begun to meet the agency’s needs. This paper discusses those efforts including overall fire safety approach, state-of-the-art textile review and testing, an agency-wide assessment of textile needs performed by the NASA Engineering and Safety Center (NESC), the textile development strategy and expected challenges.

Mary Walker

Determination of Local Experimental Heat-Transfer Coefficients on Combustion Side of an Ammonia-Oxygen Rocket

Local experimental heat-transfer coefficients were measured in the chamber and throat of a 2400-pound-thrust ammonia-oxygen rocket engine with a nominal chamber pressure of 600 pounds per square inch absolute. Three injector configurations were used. The rocket engine was run over a range of oxidant-fuel ratio and chamber pressure. The injector that achieved the best performance also produced the highest rates of heat flux at design conditions. The heat-transfer data from the best-performing injector agreed well with the simplified equation developed by Bartz at the throat region. A large spread of data was observed for the chamber. This spread was attributed generally to the variations of combustion processes. The spread was least evident, however, with the best-performing injector.

Curt H Liebert