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534 records · Page 28

Model Correlation and Thermal Analysis of xEMU Boot at Lunar South Pole Temperatures

The National Aeronautics and Space Administration (NASA) Artemis program plans to send astronauts to the lunar south pole, a region of the moon that is colder than previous lunar missions and low earth orbit operations. The spacesuit boots that will be used on these missions will be directly impacted by these extremely cold temperatures (down to ~50 K). To assess the performance of the Exploration Extravehicular Mobility Unit (xEMU) lunar boot in these extreme temperatures, the boot was tested at the Jet Propulsion Lab (JPL) in the Cryogenic Ice Transfer, Acquisition Development, and Excavation Laboratory (CITADEL) thermal vacuum (TVAC) chamber. This data was used to correlate thermal models to predict operational performance of the boots on the lunar south pole. This paper documents the data analysis, thermal boot model correlation, and operational predictions conducted using data from the xEMU TVAC test. Data from the test series was used to determine expected thermal conductances within the boot and between the boot and environment. These conductances were used to correlate a Thermal Desktop model of the xEMU boot across 10 different test points which varied external temperature, internal boot ventilation flowrate, and contact pressure. The correlated model was then used to predict operational performance in the lunar south pole. While the predictions indicate promising evidence for performance of the boots at the 100K test point, there is still substantial uncertainty in performance, particularly at the 48K test point. The results of this test series and model correlation stress the importance of improved testing for characterizing the expected thermal resistance between the outside of the boot and the lunar surface.

thermal analysis

Technology Readiness Assessment for Stirling Power Convertor

Stirling-based power conversion system could represent a critical enabling technology for future NASA missions, offering significantly enhanced power efficiency over traditional thermoelectric systems. To ensure the successful infusion of this technology into deep space and planetary surface missions, a rigorous evaluation of its maturity and associated risks is essential. The objective of this Technology Readiness Assessment (TRA) is to determine the current technology readiness level (TRL) of the Stirling power convertor and identify key technical risks and challenges associated with its maturation and potential infusion into a targeted flight system. The evaluation process will rigorously follow the NASA TRA procedure: (1) determining the requirements that underpin the design, function, and performance; (2) finding and listing all new technology elements (NTEs) and critical technology elements (CTEs); (3) identifying the level of integration assumed for the assessment; and (4) assessing the TRL for each NTE and CTE. The overall subassembly TRL will then be determined via a roll-up using the “weakest link” criterion, culminating in a final (5) assessment of risks to further progression of maturity. This paper will present the results of a comprehensive technology readiness assessment (TRA) conducted on the Stirling-based dynamic power conversion subassembly, excluding the radioisotope heat source. The paper will also describe a detailed breakdown of the TRL roll-up and a matrix of identified risks and recommended mitigation paths, along with identified key technical risks and challenges to achieve the required long-duration performance. Key Words: Radioisotope Power Conversion, Technology Readiness Assessment

Radioisotope Power Conversion

Surprisingly Enriched CO and CH4 in Halley-type Comet 13P/Olbers: Clues to Its Interstellar Heritage

The native ice composition of Halley-type Comet 13P/Olbers (hereafter 13P) was measured post-perihelion, on UT 2024 August 16 using iSHELL, the 1–5 μm cross-dispersed, high-resolution facility spectrograph at the NASA InfraRed Telescope Facility. At that time, the heliocentric distance (Rh) of 13P was 1.37 au and the geocentric distance (Δ) was 1.99 au. Using a slit that delivered spectral resolving power RP λ/Δλ 4.5 × 104, two instrument settings targeted rovibrational emissions of seven parent molecules released into the coma through sublimation of ices in the nucleus. These settings provided broad and contiguous or nearly contiguous spectral coverage, one simultaneously measuring H2O, CO, and OCS, and the other simultaneously measuring CH4, C2H6, CH3OH, and H2CO. Meaningful abundances were obtained for all seven species. Our study revealed substantial enrichments of CO and CH4, the two most volatile species systematically targeted at IR wavelengths in comets. Relative to their respective mean abundance ratios among measured comets from the Oort cloud reservoir, CO in 13P was enriched by a factor of about six and CH4 was enriched by a factor of about three. Together with near-average abundances measured for CH3OH and C2H6, this suggests large endowments of CO and CH4 on interstellar grains, yet it could indicate inhibited surface chemistry on the pre-cometary grains subsequently contained in the nucleus or 13P. Assuming that this represents the primordial composition of 13P, it could reflect very low temperatures in its natal environment (∼10 K or lower).

Michael A Disanti

Multidisciplinary Design Optimization and Analysis of an Open Rotor Stage: Part 1

Successful design of open rotor propulsors requires effective analysis across multiple disciplines, including aerodynamics, acoustics, and structures. A viable design must not only be efficient but must also produce an acceptable level of noise and meet all static and dynamic structural requirements. For design and optimization, this is especially challenging because running high fidelity analyses is resource-intensive, and optimizing a design may require many thousands of cases to be analyzed. For this reason, the NASA team has applied design methodology that utilizes low-cost aerodynamic methods, machine learning models, and high-fidelity analyses when necessary. This includes standard two-dimensional methods such as throughflow analysis and quasi-3D blade-to-blade CFD, as well as some newly developed methods. Optimization using 3D CFD is necessary to maximize performance, and this is considered as well. All optimizations are carried out subject to structural constraints evaluated using finite element analysis. Doing this accurately requires a robust trunnion design, capable of pitching the blade between cruise and takeoff conditions while maintaining acceptable factor of safety. Hot to cold analysis must also be applied in order to correctly determine the as-manufactured shape. For acoustics, the unsteady pressures on the blade surfaces must be predicted, and this can be done either through full-annulus unsteady CFD or through a nonlinear harmonic method (NLH). NLH can run much faster, allowing some acoustic considerations to be made earlier in the design process. The design process is ongoing, and this presentation will review the current status and planned next steps. This part of the talk will focus on aerodynamic performance and be followed by a talk on structures and acoustics.

Design

Synchronized Eruptions on Io: Possible Evidence of Interconnected Subsurface Magma Reservoirs

On 27 December 2024, Juno's JIRAM (Jovian InfraRed Auroral Mapper) instrument observed an unprecedented volcanic event in Io's southern hemisphere, covering a vast region of ∼65,000 km2, near 73°S, 140°E. Within the imaged region, only one hot spot was previously known (Pfd454). This feature was earlier estimated to cover an area of 300 km2 with a total power output of 34 GW. JIRAM results show that the region produces a power output of 140–260 TW, over 1,000 times higher than earlier estimates and likely exceeding the brightest eruption ever recorded on Io, that of Surt in 2001 (∼80 TW). Three adjacent hot spots also exhibited dramatic power increases: P139, PV18, and an unnamed feature south of the main one that surged to ∼1 TW, placing all of them among the top 10 most powerful hot spots observed on Io. A temperature analysis of the features supports the simultaneous onset of these brightenings and suggests a single eruptive event propagating beneath the surface across hundreds of kilometers; this is the first time this has been observed on Io. This in turn would imply a connection among the hotspots' magma reservoirs, while other nearby hotspots that have been known to be active in the recent past, such as Kurdalagon Patera, appear unaffected. The simultaneity supports models of massive, interconnected magma reservoirs. The topology of these regional magma systems may resemble that of a large-scale sponge, in which the massive reservoirs are the pores, interconnected through a largely solid outer shell.

A Mura

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

Optimization of X-ray Absorbers for High-Resolution TES Detectors in NewATHENA X-IFU

NewATHENA’s X-ray Integral Field Unit (X-IFU) uses a large-format array of Transition Edge Sensor (TES) microcalorimeters coupled with absorbers made of gold and bismuth providing 4 eV FWHM resolution up to 7 keV in the 0.2- 12 keV band. X-ray absorbers must be thick enough for photon absorption, maintain low heat capacity for energy resolution, and have good thermalization properties. The X-IFU requires total Quantum Efficiency (QE) of 96%, 87%, and 63% at 1, 7, and 9.5 keV, respectively. Optimal thicknesses are 1.05 µm gold and 5.5 µm bismuth to achieve 0.731 pJ/K at 90 mK and 87% QE at 7 keV. While typical TES absorbers are 3-4 µm thick, producing the required 5.5 µm Bi absorbers via standard electroplating creates enlarged grains and surface roughness. The increased roughness and grain size variability produced with our standard recipe have resulted in instances of 1) low energy spectral tails 2) spectral broadening of the energy resolution and 3) thermal shorts between pixels when a large grain bridges the gap between absorbers. In this study, we have introduced a new fabrication process and altered the morphology of the thick Bi through changes in the electroplating process. The process changes are intended to address all three issues as well as reduce particulate contamination observed on the finished detector arrays.

Absorber

On-Orbit Calibration Assessment of NOAA-21 VIIRS Thermal Emissive Bands and Implications for JPSS-4 VIIRS

The Visible Infrared Imaging Radiometer Suite (VIIRS) instrument onboard the NOAA-21 (N21) satellite has been successfully operating for over three years collecting valuable scientific measurements. A large suite of weather forecasting models and scientific research applications are supported with the VIIRS measurements from N21 combined with those acquired from the VIIRS instrument onboard the S-NPP and NOAA-20 spacecraft. Among the 22 VIIRS spectral bands, there are seven thermal emissive bands (TEB) covering the 3.7 to 12.2 µm spectral range at two different spatial resolutions. The VIIRS TEB detectors are calibrated onboard using a blackbody at a controlled temperature and a space view for background signal measurement. In this paper, we discuss the on-orbit performance of the N21 VIIRS TEB using various parameters such as the detector gain, noise, and offset. This on-orbit assessment provides critical insights into instrument behavior and calibration performance that will inform pre-launch testing and post-launch validation strategies for the upcoming JPSS-4 VIIRS mission scheduled for launch in 2027. The methodologies and lessons learned from characterizing the N21 TEB performance will enable more efficient and comprehensive radiometric assessment of the next VIIRS instrument. Specific focus is placed on identifying performance trends and anomaly signatures observed during the N21 commissioning phase that can enhance the JPSS4 instrument checkout procedures and accelerate the transition to routine on-orbit operations. The established performance baselines and uncertainty estimates will serve as an acceptance criterion for the JPSS-4 commissioning activities, ensuring mission readiness and data continuity for operational users.

Amit Angal

Following the αCen Ab Candidate Using the Roman Coronagraph Instrument

The Roman Space Telescope Coronagraph offers a unique opportunity to observe our nearest solar twin, Alpha Centauri A, and characterize the habitable-zone gas giant candidate, Alpha Cen Ab. The candidate uniquely stands out among all imaged exoplanets to date as the one most similar in temperature, age and location to the planets in our own Solar System. Roman CGI offers the tantalizing opportunity to observe the candidate—determining its radius, temperature, and albedo—and to constrain its orbit. Observing Alpha Cen Ab with Roman would make it the first exoplanet to be imaged in both thermal emission and reflected light and would motivate an exciting search for habitable exomoons with the upcoming ELTs and HWO. In addition, this candidate will inform the planet formation history and current dynamics of the Alpha Centauri AB system, including potentially habitable planets around both stars. In this talk, we describe our plan to observe this target using the Roman CGI, including the timing strategy to minimize contrast and avoid background objects. We also describe the key technical insights about coronagraph performance that we aim to gain, such as measuring companion leakage intensity, evaluating the impact of the large stellar diameter, and assessing CGI performance on very bright targets. In subsequent observations, we aim to demonstrate Multi-Star Wavefront Control (MSWC) on-sky, observing Alpha Cen A using the Wide FoV Shaped Pupil MSWC contributed mode in the Roman CGI. The insights from these technology demonstrations are crucial preparation for the planned HWO mission.

Coronagraph

Long-Term Evaluation of Landsat 9 Oli Data Product Uniformity at Focal Plane Module-Boundaries Using Earth Scenes

The uniformity performance characteristic in remote sensing data products is a metric that helps evaluate how an image accurately represents radiometric responses to geophysical variability at the Earth’s surface or within the atmosphere. These uniformity attributes are used in Earth remote sensing science applications such as investigating water quality, land-cover/land-use classifications, and crop health assessments. To ensure these applications perform effectively, it is crucial to maintain and regularly assess the uniformity of calibrated remote sensing data products. In the Landsat missions, data from the onboard radiometric reference Solar diffuser device are used as the standard approach to derive the calibration parameters, ensuring the maintenance of both absolute radiance and radiometric uniformity through quarterly updates. This publication presents an alternative approach that leverages Earth scene data to assess the on-orbit uniformity performance of the Landsat 9 (L9) mission. The analysis characterizes uniformity at a specific set of spatial positions (the focal-plane boundary zones) that are intrinsic to the Operational Land Imager (OLI) focal plane design. By employing these Earth data statistics, the article further explores the temporal trends in the radiometric uniformity results. The results shown in this article demonstrate that for pushbroom imaging design systems with staggered sensor chip focal plane architectures, the co-registered pixels, i.e., overlapping measurements of the same ground target viewed by different detectors, offer a self-contained mechanism for assessing product uniformity. Remarkably, this alternative approach achieves a level of radiometric quality comparable to that delivered by a stable, well-characterized onboard Solar diffuser calibration device. The findings demonstrate the potential and capability of such Earth scene statistics in maintaining radiometric uniformity in calibrated data products to better than 1% (1-sigma) throughout the mission’s operational lifetime.

trend

Enabling Reliable, Fault-Tolerant Autonomous Lunar Habitats with High-Performance Spaceflight Computing

The lunar surface presents unfavorable constraints and harsh living conditions. To address these challenges, autonomous habitats will require complex integrated systems that combine advanced software, high-performance hardware, and cutting-edge sensors to ensure sustainability, safety, and operational efficiency. Consequently, maintaining a sustainable presence on the Moon requires reliable infrastructure and efficient development, precise monitoring, and utilization of resources within a lunar installation. These elements are essential not only to ensure that lunar settlement can be long-term, self-sustaining, and resource-efficient, but also to serve as a foundation for future missions and eventual human habitation on Mars. Humans are not native to the Moon; therefore, our survival and ability to thrive will depend on autonomous systems that can foster safety and resilience through high-availability architectures, graceful degradation, and highly fault-tolerant spaceflight hardware capable of continuing operation during failures. This requires advanced human-rated distributed systems architectures with specialized electronics, scalable capabilities, and an integrated design approach. Unlike current practices focused on short-term missions and regularly maintained components, permanent lunar compute systems must be designed for extended operations beyond mission durations. This paper explores the necessity of transitioning toward fault- tolerant, highly autonomous hardware systems designed for multi-year missions. It also identifies critical subsystems that require high levels of autonomy, supported by radiation-hardened processors and extreme thermal loads, which are essential to mitigate long-term degradation and ensure sustainable lunar habitation. Finally, the paper aligns with NASA’s identified Civil Space Shortfalls, particularly in high-performance onboard computing, advanced data acquisition, extreme-environment avionics, radiation monitoring and countermeasures, and autonomous health management. It proposes NASA’s new High-Performance Spaceflight Computing (HPSC) processor as a turnkey solution, delivering 100 times the performance-per-watt of legacy rad-hard CPUs and enabling onboard AI, edge computing, and fault-tolerant features essential for sustained lunar autonomy and beyond.

Sarkis S Mikaelian

Benchmarking Bayesian Optimization Frameworks and Acquisition Strategies for Materials Discovery and Autonomous Laboratories

Bayesian optimization (BO) can accelerate materials discovery by guiding expensive experiments toward the most promising processing conditions. We systematically compare five BO surrogate and framework combinations (Gaussian processes in Ax, Gaussian processes and Monte-Carlo neural networks in BayBE, random forests in Lolopy, and tree-structured Parzen (TPE) estimators in Hyperopt) on three benchmarks that mimic common materials design tasks (a discrete solid-electrolyte composition space, a hybrid discrete/continuous laminate-composite design problem solved with micromechanics modeling, and the continuous Ishigami analytic function which is a standard optimization benchmark). Each BO surrogate is paired with posterior mean, probability of improvement, and expected improvement acquisition functions and run for 100 trials from randomized initial samples with uniform random search providing a control. Across five random seeds per setting, BayBE’s Gaussian-process surrogate with expected improvement consistently reached ≥95 % of the known optimum in the fewest evaluations, while Lolopy’s random forest matched or exceeded GP performance on purely categorical or mixed spaces at a higher computational cost. Posterior mean alone often stagnated at local optima, underscoring the need for exploration, whereas probability and expected improvement balanced exploration and exploitation leading to better optimization in fewer trials. Execution times ranged from milliseconds for TPE to minutes for neural-network and random-forest surrogates. These results establish baseline expectations for BO in automated materials laboratories and highlight expected improvement with Gaussian processes as a reliable first choice, with random forests offering a strong alternative when categorical variables dominate. The benchmark suite and code are released to facilitate future surrogate, acquisition, and constraint-handling research in data-driven materials optimization.

Bayesian optimization

Mass Economy Evaluation for Integrated ECLSS and Propulsion Architecture

As missions in Low Earth Orbit (LEO) lengthen and extend to deep space, minimizing resupply needs becomes vital for sustaining crewed operations. Traditional life support systems depend on consumables resupplied from Earth, a method that is increasingly impractical for missions beyond LEO, such as lunar outposts or Mars transit. Long-duration missions require more efficient, autonomous systems that can recycle essential resources, particularly water and oxygen, to minimize the frequency and mass of resupply missions. The Environmental Control and Life Support System (ECLSS) is essential to such missions, with the International Space Station (ISS) serving as a testbed for advanced water recovery and partial oxygen recycling via physico-chemical methods. Yet, ECLSS and propulsion subsystems generally operate independently, despite overlapping requirements and potential areas for synergy. For instance, ECLSS byproducts, water, CO₂, and hydrogen, could be repurposed for propulsion, potentially reducing dedicated propellant mass and increasing overall system efficiency. One promising approach is to develop shared-resource architectures that integrate ECLSS with propulsion systems. This study examines the potential of such integration through the Sabatier CO₂ reduction process, focusing on water management as a key factor in system mass trade-offs. The Sabatier reaction produces water and methane from metabolic CO₂ and electrolytic hydrogen, partially closing the life support loop and providing methane, which could serve as a propellant. This integration could minimize waste, reduce resupply requirements, and enhance mission mass efficiency. A dynamic modeling framework will be used to simulate resource flows over long missions, capturing interactions between life support and propulsion. By comparing integrated versus separate system configurations, the study aims to quantify mass benefits and penalties, informing future habitat designs and trade studies for missions prioritizing autonomy and mass efficiency.

ECLSS

Evidence for the Interaction of the IRS 16 Wind With the Ionized and Molecular Gas at the Galactic Center

We present a number of high-resolution radio images showing evidence for the dynamical interaction of the outflow arising from the IRS 16 complex with the ionized gas associated with the Northern Arm of Sgr A West, and with the northwestern segment of the circumnuclear molecular disk which engulfs the inner few parsecs of the Galactic center. These interactions offer an opportunity to explain some important aspects of the complex morphology of ionized and molecular gas at the Galactic center. In particular we suggest that the wind disturbs the dynamics of the Northern Arm within 0.1 pc of the center, is responsible for the waviness of the arm at larger distances and is collimated by Sgr A West and the circumnuclear disk. The waviness is discussed in terms of the Rayleigh-Taylor instability induced by the ram pressure of the wind incident on the surface of the Northern Arm. Another consequence of this interaction is the strong mid IR polarization of the Northern Arm in the vicinity of the IRS 16 complex which is explained as a result of the ram pressure of the wind compressing the gas and the magnetic field. The IRS 16 complex must therefore lie close to the Northern Arm. On a large scale we argue that the wind has swept up the diffuse material in the inner parsec of the Galactic center and that the interaction with the inner part of the northwestern part of the circumnuclear ring is responsible for the H 2 v = 1-0 emission and the ionized streamers. Lastly, we discuss the possibility that the outflow from IRS 16 could be responsible for eating away the inner edge of the circumnuclear disk and provide friction needed for the infall of the material in the arms of Sgr A West.

IRS 16

Mass Economy Evaluation for Integrated ECLSS and Propulsion Architecture

As missions in low Earth orbit (LEO) lengthen and extend to deep space, minimizing resupply needs becomes vital for sustaining crewed operations. Traditional life support systems depend on consumables resupplied from Earth, a method that is increasingly impractical for missions beyond LEO, such as lunar outposts or Mars transit. Long-duration missions require more efficient, autonomous systems that can recycle essential resources, particularly water and oxygen, to minimize the frequency and mass of resupply missions. The Environmental Control and Life Support System (ECLSS) is essential to such missions, with the International Space Station (ISS) serving as a testbed for advanced water recovery and partial oxygen recycling via physico-chemical methods. Yet, ECLSS and propulsion subsystems generally operate independently, despite overlapping requirements and potential areas for synergy. For instance, ECLSS byproducts, water, CO 2 , and hydrogen, could be repurposed for propulsion, potentially reducing dedicated propellant mass and increasing overall system efficiency. One promising approach is to develop shared-resource architectures that integrate ECLSS with propulsion systems. This study examines the potential of such integration through the Sabatier CO₂ reduction process, focusing on water management as a key factor in system mass trade-offs. The Sabatier reaction produces water and methane from metabolic CO 2 and electrolytic hydrogen, partially closing the life support loop and providing methane, which could serve as a propellant. This integration could minimize waste, reduce resupply requirements, and enhance mission mass efficiency. A dynamic modeling framework will be used to simulate resource flows over long missions, capturing interactions between life support and propulsion. By comparing integrated versus separate system configurations, the study aims to quantify mass benefits and penalties, informing future habitat designs and trade studies for missions prioritizing autonomy and mass efficiency.

ECLSS

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

Ranger Spacecraft

The thermal-control philosophy of the spacecraft currently under development by the Jet Propulsion Laboratory is design by passive means to maintain all components within the tolerances specified by cognizant engineers. Due to the complexity of the configurations, calculations are) of necessity, fairly generalized and final design is based upon tests in an environmental chamber. The Ranger series spacecraft is designed with a basic structure which is common to all models, with additional hardware to suit the individual mission. This basic structure of Rangers A-1 and A-2 is seen as the hexagonal instrument section, the erectable solar panels, the movable antenna, and the omniantenna. The Ranger A-1 and A-2 configuration is for engineering tests and space-exploration, with the scientific instrumentation isolation requirement dictating the spread-out design. The spacecraft stands 12 feet high, weighs 700 to 800 pounds, and has an internal power of 150 watts. Rangers A-3, A-4, and A-5 are designed to rough land a capsule on the moon. For these, a capsule and retrorocket replace the scientific instruments, occupying the space inside the tower structure. The spacecraft must survive many environments. Chronologically they are: 1) Folded configuration inside an aerodynamic shroud on the pad. 2) Thermal flux from shroud aerodynamically heated during boost phase. 3) Coasting up to 30 minutes attached to Agena stage after booster and shroud are separated. 4) Agena stage burning. 5) Coasting and tumbling after separation from Agena until it passes from earth's shadow. 6) Upon reaching sunlight, panels open and begin sun acquisition. 7) Antenna seeks earth after spacecraft locks onto sun. 8) Space phase- "steady state" with vehicle's vertical axis locked on sun, communicating with earth. The philosophy is to design for the sun-acquired mode, making allowances for the transient conditions.

T. O. Thostesen

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