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578 records · Page 29

Evaluating Crystallinity in Thermoplastic Composites for Aerospace Applications

Polymer matrix composites (PMCs) offer many benefits for the aerospace industry due to their potential for weight reduction when compared to metal or ceramic based materials. Most PMCs currently in flight use thermoset matrices, however, thermoplastic resins are being explored as alternatives due to their ability to be remelted, which is of particular interest due to the potential for in-situ repair and faster production. Most thermoplastic resins are semicrystalline polymers. The properties of semicrystalline thermoplastics are directly influenced by their crystallinity, which can vary due to many factors including thermal treatments, environmental conditions, and mechanical deformation. Within thermoplastic PMC parts, crystallinity gradients can arise due to variations in part geometry, across part thicknesses, and along bonded joints. Monitoring the crystallinity of thermoplastic composites is key to ensuring these materials meet the high demands required for aerospace. Several different analytical techniques exist that can be used to characterize the bulk crystallinity of thermoplastic materials. However, many existing methods lack the specificity required to identify the subtle variations in crystallinity that may play a significant role in the performance and durability of PMC parts. Because of this, a significant amount of work is still required to fully characterize and understand the crystallinity profiles of thermoplastic PMCs and the resulting impact to material properties. This talk discusses the use of multiple techniques such as Differential Scanning Calorimetry, Polarized Light Optical Microscopy, and Fourier-Transform Infrared Spectroscopy to characterize the crystallinity in carbon fiber/thermoplastic composites. Samples of different crystallinity profiles were manufactured using various cooling procedures. This work aims to provide the fundamental data necessary to understand the effects of crystallinity on thermoplastic PMCs, which is key to advancing their use in aerospace applications.

Thermoplastics

Improving Adhesive Bondline Time of Flight Predictions During Autoclave Cure Utilizing Machine Learning

Composite materials are increasingly being used in aerospace applications due to their superior strength-to-weight ratio compared to commonly used metals. A current limitation to widespread adoption is the certification of adhesively bonded joints. One approach to improving adhesive bonding in composites is accurately measuring the thickness of adhesive bondlines in composite laminates. Precise bondline thickness control is essential for aerospace applications where adhesive layer thickness directly affects joint fracture properties and structural performance. This study focused on implementing machine learning techniques to determine the ultrasonic time of flight (directly correlated to thickness) in adhesive bondlines throughout autoclave cure cycles. A high-temperature (use up to 180°C) ultrasonic scanning system was deployed in an autoclave to provide time of flight data through composite panels. Three experiments were conducted on the curing of 305 mm × 305 mm unidirectional composite panels. In the first experiment, a piecewise function was fit for the temperature correction factor to account for changing autoclave temperatures. Due to deficiencies in the first calibration experiment, a second experiment was run, and the results were used to train a machine learning model. The revised experiment, in combination with the machine learning model, significantly increased the accuracy of the bondline time of flight predictions (~14% error reduced to <1%). Data was processed using the Regression Learner Application in MATLAB®, with a Support Vector Machine selected for the model. The result was a machine learning algorithm capable of reliably quantifying ultrasonic time of flight through adhesive bondlines. The third experiment provided independent test data for the machine learning model, demonstrating that the model produces accurate predictions from data beyond its training set.

Machine Learning

Toward Large Field-of-view X-ray Spectrometers with Magnetic Microcalorimeters

A future X-ray telescope mission like Lynx, a X-ray flagship mission concept, requires a large field of view, high energy resolution, and high spatial resolution. The Magnetic Microcalorimeter (MMC) detectors we are developing for such a mission feature a 5-arcminute field of view, approximately 100,000 pixels, each spanning 0.5–1 arcsecond. These detectors require the readout of 8,000 sensors. Three different array types have been designed to meet scientific goals, two of which utilize thermal multiplexing to reduce the number of readout channels in a scheme called “Hydra.” We are currently fabricating detectors on a recently completed buried wiring wafer with connections to every sensor. The sensors are read out using a microwave multiplexer (μMUX) with flux ramp modulation. A single μMUX can read out approximately 1,000 sensors with only two feed lines. We will report on the test of the first two-dimensional μMUX chip, consisting of 78 resonators. μMUX chips that pass screening will be directly bonded to MMC array chips using indium bump bonding. In parallel, we have tested a kinetic inductance traveling wave parametric amplifier (KI-TWPA) to amplify signals at low temperatures. The KI-TWPA exhibits extremely low internal noise, approaching the standard quantum limit. Since the energy resolution of an MMC is primarily limited by the readout system, the KI-TWPA is an ideal amplifier for MMCs with μMUX readout. We recently measured the readout noise of a μMUX with a KI-TWPA, demonstrating its capability for reading out MMC arrays. We present the design and fabrication of the latest MMC detectors, along with its readout performance.

Magntic Microcalorimeters

Preliminary Findings of the Experimental Development Unit Cold Flow Test for a Generation Zero Nuclear Propulsion Engine

Nuclear thermal propulsion (NTP) technology will greatly benefit human travel to Mars by significantly shortening transit times, improving crew safety, and providing more mission flexibility than traditional chemical rockets. As part of DRACO follow-on work to develop, build, and fly a generation zero NTP engine, a full scale flight-like experimental design unit (EDU) reactor was constructed to collect sufficient on-ground performance data to characterize flow induced vibrations (FIV) of critical reactor structures/components, inform development of the engine and reactor control algorithm, and collect pressure drop and flow distribution data across the reactor. The fluid conditions for the test program were designed to achieve system responses equivalent to that of an operational engine through all phases of engine operation including reactor startup, mainstage operation, reactor shutdown, and reactor cooldown. Over 100 tests were executed, flowing either GN2 or GHe through the EDU at varying flow rates and pressures. This experiment provided early validation of flow behavior and vibration risks before nuclear testing, boosted critical subsystem TRLs, informed design iterations, and reduced future test costs. The steady-state flow parameters for the experiment were modeled in Ansys Thermal Desktop, allowing rapid tuning and experiment-informed updates to a flight-like test matrix. The EDU dynamic environment was characterized with accelerometers, strain gauges, and high-frequency pressure transducers all sampled at 20 kHz. While many narrow-band oscillations were identified, no significant FIV occurred; the reactor structural responses tend to be enveloped by typical launch vehicle ascent vibration environments (defined up to 2 kHz), although significant energy is also present at higher frequencies.

Flow Induced Vibration

Advanced Materials for the Lunar Surface: Multiscale Computational Design of Refractory Alloys and Carbides

Emerging operational environments, such as the lunar surface, present novel challenges for NASA and drive the need for advanced materials in applications like fission surface power systems. To address these demands, computational materials science is rapidly evolving to augment or replace costly and hazardous empirical testing. Although materials selection at NASA remains predominantly experimentally driven, advanced simulation methodologies are being steadily integrated into the engineering lifecycle. This work details the application of multiscale simulation techniques—including first-principles calculations, CALPHAD, dislocation dynamics, and molecular dynamics—at NASA's Ames Research Center to evaluate advanced materials for extreme environments. First, we present contributions to the Space Nuclear Propulsion Project. Be-cause propellant channel coatings in nuclear thermal rockets must withstand high-pressure, high-temperature hydro-gen, optimizing these materials is critical. First-principles calculations were employed to establish a rigorous quantitative and qualitative understanding of the behavior of the refractory carbides ZrC, NbC, and their mixtures in high-enthalpy hydrogen environments. This necessitated the generation of high-fidelity thermodynamic models for both stoichiometric and carbon-depleted carbides, both with and without the presence of hydrogen. Furthermore, we highlight efforts under the Refractory Alloy Additive Manufacturing Build Optimization (RAAMBO) project, where existing and novel alloy compositions were assessed for additive manufacturing printability and subsequent performance in applications such as heat pipes and rocket nozzle extensions. This was accomplished through a comprehensive multiscale simulation framework that bridged the gap from the nanometer to the millimeter scale. Across both initiatives, rigorous validation against empirical data was prioritized. By systematically employing a verified and validated computational frame-work, we demonstrate how simulation effectively supports multidisciplinary engineering efforts, builds project-wide confidence, and drives critical materials development.

computational materials

Plume Impingement Software Module for Real-Time Proximity Operations

Successfully executing proximity operations in space, such as docking or in-orbit servicing, requires sophisticated spacecraft design that accounts for induced environments. As a chaser vehicle’s attitude control thrusters fire, they create rarefied plumes that can impact the target vehicle, with the potential to overload components, exceed thermal limits, and spin the target vehicle out of control. High-fidelity simulations of the thruster plume impingement environment require the direct simulation Monte Carlo (DSMC) method, but DSMC is too computationally expensive to simulate proximity operations that involve thousands of thruster firings. For this analysis to be tractable, engineering models of the plume flowfield and impingement events are used to simulate these trajectories [1]. Currently, on-orbit plume impingement environments are modeled through an inefficient open-loop analysis cycle where the vehicle’s flight controller and plume impingement teams iterate on the trajectories until they pass the target vehicle’s plume requirements. As complex on-orbit missions evolve and become more frequent, lengthy design cycles will become operational bottlenecks. To address this gap, this work develops an advanced plume impingement module capable of operating at real-time scale that can be integrated with existing mission planning tools and onboard flight systems. The plume module leverages state-of-the-art plume simulation techniques [2] to deliver fast, physics-based impingement predictions in a software architecture that can be tailored to diverse proximity operations scenarios. A prototype of this plume impingement module is built to demonstrate the feasibility of real-time performance. This prototype completes plume impingement calculations in microseconds per target geometry mesh point. The software serves as a foundational capability for plume-aware trajectory design, operational risk assessment, and future autonomous decision-making systems.

Plume Impingement

Beyond Melting: Amorphous Bonding for Joining and Consolidation

Crystallization may be the hidden constraint in thermoplastic composite manufacturing. It requires tightly controlled cooling, induces residual stresses through shrinkage, and introduces path-dependent behavior that complicates predictive modeling yet remains essential for structural performance. This work asks: can bonding be achieved without relying on melt-driven crystallization? To address this, thin (5–20 μm) polyetherimide (PEI) interlayers are pre-healed to slow-cooled polyaryletherketone (PAEK) in two contexts. The first, Thermabond®, is sub-melt joining of low melt-PAEK laminates. Results show that bond quality is governed primarily by processing (i.e., adequate healing and film handling) rather than modest changes in interlayer thickness. This concept is then extended to laminate-scale manufacturing through an architecture known as OATMEAL (Out-of-autoclave Amorphous/semicrystalline Thermoplastic Material for Energy-efficient Aerospace-grade Laminates). PEI is healed to carbon fiber reinforced polyetheretherketone (PEEK) at the prepreg and excess PEI is then ablated from the surface. Crystallinity is developed off-line during prepreg fabrication, while subsequent consolidation occurs below the melt temperature to preserve it. Cross-ply warpage experiments show that, contrary to intuition, repeated amorphous interfaces reduce global curvature by lowering the effective stress lock-in temperature and eliminating crystallization shrinkage from the lamina response. Correspondingly, laminate behavior is accurately predicted using classical laminate theory (CLT) with a single effective stress-free temperature, whereas conventional CF/PEEK requires accounting for crystallization-driven effects. By decoupling interfacial healing from crystallization, OATMEAL enables sub-melt consolidation, reduces energy consumption by up to 75%, and increases manufacturing throughput by fivefold. These results demonstrate that amorphous bonding is not only a joining strategy, but a pathway to more predictable and scalable thermoplastic composite manufacturing.

solidification

Wave Rotor Enhanced Nuclear (WREN) Propulsion: NASA Innovative Advanced Concepts (NIAC) - Phase I Final Report

Nuclear Thermal Propulsion (NTP) is identified as one of the preferred propulsion technologies for manned missions throughout the solar system (NASA MSFC).[1, 2] The state-ofthe-art NTP cycle is based on a solid core Nuclear Engine for Rocket Vehicle Application (NERVA)[3] class technology (Fig. 1) that is envisioned to provide a specific impulse of 900 seconds doubling chemical rocket performance (450 seconds). Even with this impressive increase, the NTP NERVA designs still have issues providing adequate initial to final mass fractions for high ΔV missions.[4] Nuclear Electric Propulsion (NEP) can provide extremely high Isp (2,000 to over 10,000 seconds) but with only low thrust and limits on mass to power ratios. The need for an electric power source also adds the issue of heat rejection in space where thermal energy conversion is at best 30-40% under ideal conditions. NASA Space Technology Mission Directorate (STMD) has recently expressed interest in finding advanced nuclear propulsion technology through the NASA Go:Thrust RFI.[5, 6] A novel Wave Rotor (WR) topping cycle has been proposed for our NASA NIAC concept. It promises to deliver similar thrust as NERVA class NTP propulsion, but with Isp in the 1,200-2,000 second range. Coupled with an NEP cycle, the duty cycle Isp can further be increased (1,800-4,000 seconds) with minimal addition of dry mass. This bimodal design enables fast transit trajectories for manned missions to Mars and revolutionizes the deep space exploration of our solar system.

Nuclear Thermal Propulsion

Chapter 9 - Pre-Flight Tests

Pre-flight testing is critical to the success of any flight test program. Pre-flight tests are performed to measure and evaluate the characteristics of an aircraft in a non-flying environment and to verify that these characteristics are as desired. Since aircraft systems are becoming more and more complex, conducting proper pre-flight testing to help identify system characteristics and deficiencies prior to flight is more important now than ever before. Much flight test time has been lost fixing problems that should have been found and corrected prior to flight. Accidents have occurred because pre-flight tests and verification procedures were not conducted thoroughly enough to identify the aircraft's characteristics properly or to find system discrepancies. Proper pre-flight testing helps ensure that the aircraft is ready to fly and contributes toward an efficient, productive, and safe flight test program. The reader should be aware that this Section is dedicated to the testing that should take place prior to the first flight. There are other "pre-flight" tests that take place prior to each individual flight. These latter tests are not discussed in this Section. The following paragraphs of this Section describe significant tests that are usually accomplished prior to flying a new or highly modified aircraft. Test objectives, descriptions, products, and requirements are provided in the following subsections: 9.1 Wind tunnel tests 9.2 Simulation tests 9.3 Propulsion tests 9.4 Weight and balance tests 9.5 Ground vibration tests 9.6 Structural loads tests 9.7 Gain margin tests 9.8 Verification and calibration tests 9.9 Taxi tests The specific examples given and the test facilities mentioned in this Section will illustrate the approach taken and the techniques used by the US Air Force; however, they are typical of those used by other test organizations.

Paul W Kirsten

WINDSAT Free Flyer Using the Advanced TIROS-N Satellite

The results of this study show the feasibility of carrying a wind measuring lidar on an ATN-derivative free flying spacecraft. The overall configuration fits within the Shuttle bay and uses the same techniques for STS Launch as the proposed SAATN spacecraft. The lidar can be made light enough that the total weight of the satellite is well within the capability of the onboard propulsion system for transfers to a Sun synchronous orbit at 833 km attitude. The principal techniques for weight minimization are the use of the Perkin Elmer proprietary HIP process for the telescope, new packaging concepts for the laser and for the optics-laser interface, and the application of current technology to the signal processing hardware. Power minimization is achieved for the lidar primarily by use of a low pulse repetition frequency, i.e., 2pps, and again by the use of current processor technology. The power capability of the spacecraft is enhanced by increasing the ATN array size 25 percent, through the addition of two more solar array panels of the present size, and by limiting the range of Sun angles over which the spacecraft is operated. The same basic concept for the lidar as proposed in the Shuttle Windsat study is recommended here, but there are some changes in details to improve weight and power. No major technology break-throughs are required for the lidar, but some technology experiments are recommended for the laser subsystem to verify isotopic gas lifetime and performance, modulator life and weight, and for space qualification. Spacecraft changes are all natural modifications or growth to accommodate the payload. Overall, the proposed system provides substantial margin for the uncertainties for the future and for potential payload change, and also demonstrates the reasonableness of the Windsat Free Flyer concept.

Herbert M Gurk

Swamp Works Regolith Compaction Technologies

While the level of compaction below the lunar surface increases quickly after only a few cm of depth, in many cases during a construction mission there will be a need to excavate and transport regolith to a new location for cut-and-fill or horizontal construction of structures such as berms. In these cases to achieve high levels of bulk density, compaction must be per-formed. Additionally, in some cases surface technologies such as systems that sinter/melt the surface may desire the maximum possible compaction at the sur-face to improve melting/heating performance and the final material strength properties. Kennedy Space Center’s (KSC) Swamp Works has developed two means of compaction, lunar and mar-tian compaction. Planetary Autonomous Compaction Technology (PACT) which is part of the Multifunction End Effector for Regolith Compaction Acquisition and Transfer (MEERCAT) robotic arm end effector system’s capabilities and the Site Preparation Tooling for Operations on Mobility Platforms (STOMP) vibratory roller compactor. PACT on MEERCAT has been demonstrated to a TRL 5 and STOMP to a TRL 4 in ambient testing. The results of PACT on MEERCAT and STOMP testing will be shared with results for various simulants including BP-1, ICN-LHT-1G (aka CSM-LHT-1G), RDW-LHT-1GH (a simulant developed for the Mason Tipping Point to match characteristics of ICN-LHT-1G), and Exolith LHS-1E. This will also include discussions on methods used to verify relative density before and after compaction and means to verify density effects below depth. To calculate relative density, maximum and minimum densities for simulants were taken from literature and additional lab testing (publication in work).

redwire

Multi-Agent Swarm State of the Art Report

The Next-Generation Multi-Agent Swarm (NGS) Study conducted by NASA’s Ames Research Center for NASA’s Space Technology Mission Directorate (STMD) will develop a comprehensive understanding of emerging multi-agent swarm capabilities. The study aims to identify existing swarm capabilities and asses their potential for persistent lunar space situational awareness, surface monitoring, and distributed autonomy demonstrations. A key objective is to inform the design of a next-generation multi-agent swarm that can perform autonomous distributed remote sensing, position, navigation, and timing (PNT) services, automated deployment that leverages autonomy, edge computing, and interoperable networking to enable cooperative operations without the need for immediate human operation. This study will address specific shortfalls identified by STMD, including intelligent multi-agent constellations, autonomy, edge computation, position, navigation, and timing for small spacecraft, small spacecraft propulsion, and space situational awareness (1625, 1438, 1433, 1557, 1431, 1430, 1589). The NASA Ames Mission Design Center (MDC) will provide subject matter expertise to support systems engineering trades, while experts in autonomy and spacecraft swarms in NASA’s Intelligent Systems Division will lead the study and focus on identifying emerging next-generation swarm capabilities. The study objectives include: capturing the current state-of-the-art for multi-agent swarm capabilities, evaluating technologies and creating technology roadmaps, and developing at least one new technology demonstration mission concept. This initial NGS study report surveys the current state of the art in technology areas relevant for the next-generation multi-agent swarm design. Our primary focus is on surveying relevant deployed space systems1, supplemented with selective analysis of relevant proposed missions and technology developments that have yet to fly.

agent

Battery Pack Shape Optimization using Transient Heat Conduction Coupled with Cell-Discharge Analysis

Battery electric systems exhibit significant time-dependence, especially when evaluated in the context of an aircraft mission profile with continually changing power demands. Additionally, when evaluating battery-powered aircraft concepts, it is important to accurately compute the temperature of the batteries and properly characterize the thermal response of the system. The temperature of the batteries has a significant impact on cell performance, in addition to safety considerations of maintaining battery temperatures below their operating limit. Because of these considerations, battery models for preliminary design and optimization of aircraft should include the capability to accurately compute the temperature distribution within the battery pack. Furthermore, battery pack designs should be as light-weight as possible to maximize the pack energy density, while also considering battery temperature limits. Here, we demonstrate a simultaneous trajectory and shape optimization of a battery pack concept, using a transient heat transfer finite element model coupled with a time-varying cell-discharge battery model to provide this capability. Including the transient finite element problem in the loop enables accurate temperatures that can be passed back to the cell discharge model, while the cell discharge model can supply the finite element model with time-varying heat boundary conditions to the finite element problem, further benefiting the fidelity of the thermal response of the batteries. We first demonstrate the coupling capability between the battery cell-discharge model and the transient finite-element heat transfer through an optimization which computes the optimal current profile for the battery pack while ensuring the battery temperatures remain below their operational limit. We then build on this optimization by adding shape optimization to the problem, which allows us to consider a composite objective function which also minimizes the mass of the battery pack, while also producing an optimal current discharge profile.

Optimization

Designing a Propylene-Glycol Coolant Servicer System for Gateway’s Internal Active Thermal Control System

A human spacecraft ATCS—especially one using single-phase coolant loops exposed to cabin atmospheric conditions—requires periodic degassing and refilling to support long-duration missions of 15 to 30 years. During initial fill operations, system maintenance, gas permeation, and quick-disconnect mating or de-mating, small amounts of gas can gradually enter the coolant system over time. This can lead to degraded heat transfer performance, pump cavitation, and potentially pump vapor lock if a significant gas volume accumulates over time. Additionally, system leaks and routine fluid sampling can gradually reduce accumulator volumes to unacceptable levels, requiring periodic refills. In more severe cases, catastrophic changes in fluid composition may necessitate emergency draining, refilling, and degassing to ensure continued system functionality. These risks were identified and mitigated on the ISS ITCS through the development of a dual-membrane degasser ORU and a Fluid Servicer System ORU for coolant refilling. These systems were developed for the fully water-based ISS ITCS Coolant[1]. The Gateway space station, the first permanent human habitat in lunar orbit, uses a propylene-glycol/water coolant mixture, which has significantly different fluid properties compared to pure water. Because microgravity degassing technologies are sensitive to fluid surface tension and viscosity, existing ISS hardware is not suitable for servicing a propylene-glycol-based TCS. Unlike the ISS, the Gateway will operate in a higher-radiation environment and must meet stricter mass constraints due to its location outside of low earth orbit. This Government Furnished Equipment (GFE) flight hardware project aims to develop a lightweight, radiation-resistant Coolant Servicer System (CSS) capable of degassing and refilling Gateway’s propylene-glycol water-based IATCS.

Propylene Glycol Water

SERENE: Saturn Enceladus Return Explorer with Nuclear Electric Propulsion

A ‘quick’ Enceladus sample return mission concept was developed based on the scientist recommendations at the recent ‘Accelerating Space Science with Nuclear Technology Workshop’. The Nuclear Electric Propulsion spacecraft assumed a follow-on 40 kWe nuclear reactor using the demonstrated 40 kWe Fission Surface Power system, expected in the early 2030s. The NEP vehicle also utilized a set of NEXT-C ion thrusters as well as planned Artemis commercial launchers. By launching the 40 kW NEP vehicle on a Starship and adding the propellants of 15 tankers, the 27t probe could be sent on a direct trajectory to Saturn (no Earth or Jupiter flybys) where NEP was used for Saturn capture, spiral down, spiral up and return to the Earth. A small lander obtained the surface Enceladus sample. Using the 40 kW NEP provided a round-trip time of only 16.5 years. A second option was more attractive from a science perspective whereby the NEP vehicle would deliver a large, 6t chemical lander to low Enceladus orbit where it would grab and return a sample to Earth (similar to the recent Orbilander design but in reverse). After deploying the lander, the NEP vehicle would stay in Saturn space performing a moon tour by orbiting four more moons and mapping the large moon of Titan. This option took slightly longer (18.5 yrs) due to the chemical return leg limitations. Both options demonstrated the agility, payload capability, and sample return goals the workshop recommended. An all-chemical option with two stages was roughly analyzed but took 21.5 yrs and required a Jupiter gravity assist.

Nuclear Electric Propulsion

Designing a Propylene-Glycol Coolant Servicer System for Gateway’s Internal Active Thermal Control System

A human spacecraft ATCS—especially one using single-phase coolant loops exposed to cabin atmospheric conditions—requires periodic degassing and refilling to support long-duration missions of 15 to 30 years. During initial fill operations, system maintenance, gas permeation, and quick-disconnect mating or de-mating, small amounts of gas can gradually enter the coolant system over time. This can lead to degraded heat transfer performance, pump cavitation, and potentially pump vapor lock if a significant gas volume accumulates over time. Additionally, system leaks and routine fluid sampling can gradually reduce accumulator volumes to unacceptable levels, requiring periodic refills. In more severe cases, catastrophic changes in fluid composition may necessitate emergency draining, refilling, and degassing to ensure continued system functionality. These risks were identified and mitigated on the ISS ITCS through the development of a dual-membrane degasser ORU and a Fluid Servicer System ORU for coolant refilling. These systems were developed for the fully water-based ISS ITCS Coolant[1]. The Gateway space station, the first permanent human habitat in lunar orbit, uses a propylene-glycol/water coolant mixture, which has significantly different fluid properties compared to pure water. Because microgravity degassing technologies are sensitive to fluid surface tension and viscosity, existing ISS hardware is not suitable for servicing a propylene-glycol-based TCS. Unlike the ISS, the Gateway will operate in a higher-radiation environment and must meet stricter mass constraints due to its location outside of low earth orbit. This Government Furnished Equipment (GFE) flight hardware project aims to develop a lightweight, radiation-resistant Coolant Servicer System (CSS) capable of degassing and refilling Gateway’s propylene-glycol water-based IATCS.

Propylene Glycol Water

Effect of Microgravity on Several Visual Functions During STS Shuttle Missions

Many astronauts and cosmonauts have commented on apparent changes in their vision while on-orbit. Comments have included statements of supposed improved distance acuity to decreased near vision capability. The purpose of this study was to assess not only changes in visual acuity, but expand the assessment to several other visual functions for a comprehensive battery of tests. Vision was assessed using an innovative device, the Visual Function Tester - Model 1 (VFT-1), which presents the tests at optical infinity and includes critical flicker fusion, stereopsis to 10 seconds-of-arc, visual acuity in small steps to 20/7.7, cyclophoria, lateral and vertical phoria, and retinal rivalry. Vision was assessed 2 times prelaunch at L-14 days and L-7 days, 3-4 times while on-orbit, at landing, and 2 times postlanding at L+3 days and L+7 days. There were 26 STS astronauts that participated, with data on 20 astronauts used for analysis. There was a typical wide variability between subjects in baseline visual performance for each parameter at the prelaunch sessions. There was a slight but statistically significant decrease in visual acuity while on-orbit that was not clinically significant. For stereopsis (i.e. depth perception), there was a small improvement on-orbit that was not statistically significant. There were no changes during space flight for any of the other visual parameters tested. A few individuals showed apparent changes in acuity and stereopsis. The possibility exists that microgravity affects the visual system of some individuals differently, as with space adaptation syndrome. Repeat data on 2 astronauts showed good repeatability between the 2 flights. These results pertain to only short term space flight on the STS shuttle, and longer flights are necessary to determine if there is any relationship between mission duration and these visual functions.

Melvin R O'Neal

PERSIANN-Unet: A Global Deep Learning Framework for Near-Real-Time Precipitation Estimation Using Infrared Data

Access to high-quality, high-resolution, near-real-time precipitation data is essential for hydrological and meteorological research and disaster mitigation. Traditional tools such as rain gauges and radar networks, though effective, have limitations, including sparse coverage in remote areas and high operational costs. Satellite data, with its global coverage and high spatial and temporal resolutions, mitigates limitations in coverage. Satellite precipitation products like Hydro Estimator (HE), Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG), and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN) utilize both geosynchronous thermal infrared (IR) and passive microwave (PMW) data in their operation. PMW sensors offer detailed atmospheric profiles but suffer from higher latency, whereas IR sensors provide lower latency but only capture cloud-top information. Despite this constraint, IR data remains attractive for low-latency precipitation estimation. Recent advances in deep learning, particularly convolutional neural networks (CNNs), have further improved satellite precipitation retrievals. This study introduces PERSIANN-Unet (PUnet or PERSIANN V3), a quasi-global algorithm covering 60°N–60°S that combines IR data, monthly climatology, and the UNet architecture to produce half-hourly precipitation estimates at 0.04° resolution. The product is evaluated against HE, IMERG, and PDIR-Now for 2022–2023. Results show that PUnet closely matches its training target, IMERG V07 Final, at the global scale, and performance is further evaluated against Stage IV as a reference over CONUS. Training PUnet on IMERG (2016–2021) leverages a high-quality, integrated PMW IR-gauge precipitation product while developing an IR-based framework not reliant on PMW availability. By operating on a single global image, PUnet avoids tile partitioning and blending steps, reducing edge discontinuities, and produces more spatially consistent precipitation fields across hemispheres.

Phu Nguyen