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NASA NTRS2026

Hybrid Thermally Efficient Core (HyTEC) Phase 1 3-Stage Compressor Rig Final Report - Unlimited Rights

The HyTEC Phase 1 3-Stage Compressor Rig project was conducted to mature and validate front-stage aerodynamic technologies in support of HyTEC Phase 2 and GEA’s Compact Core compressor. Building on the prior ERA Phase 2 Baseline Rig, GEA and NASA collaborated on the design and testing of the HyTEC rig, incorporating advanced technologies such as increased radius ratio, higher aerodynamic loading, and advanced casing treatment. The HyTEC test campaign leveraged similar design and instrumentation philosophy, test execution approach, and the same facility (NASA W-7) to enable clear comparison with the legacy ERA rig results. The HyTEC rig was designed to deliver benefits in efficiency, tip loading, operability, and aeromechanics, with success measured against defined TPMs that were anchored to the ERA baseline rig data.

Axial Compressors↗

NASA NTRS1969

Battery case shear

Hand operated shear removes a battery case without disturbing the internal components which are to be tested. It consists of three tool-steel elements, the cutter blade, and a hand lever that provides the mechanical advantage required to cut steel.

Patro, S.↗

NASA NTRS1991

Augmentation of the Space Station Module Power Management and Distribution Breadboard

The space station module power management and distribution (SSM/PMAD) breadboard models power distribution and management, including scheduling, load prioritization, and a fault detection, identification, and recovery (FDIR) system within a Space Station Freedom habitation or laboratory module. This 120 VDC system is capable of distributing up to 30 kW of power among more than 25 loads. In addition to the power distribution hardware, the system includes computer control through a hierarchy of processes. The lowest level consists of fast, simple (from a computing standpoint) switchgear that is capable of quickly safing the system. At the next level are local load center processors, (LLP's) which execute load scheduling, perform redundant switching, and shed loads which use more than scheduled power. Above the LLP's are three cooperating artificial intelligence (AI) systems which manage load prioritizations, load scheduling, load shedding, and fault recovery and management. Recent upgrades to hardware and modifications to software at both the LLP and AI system levels promise a drastic increase in speed, a significant increase in functionality and reliability, and potential for further examination of advanced automation techniques. The background, SSM/PMAD, interface to the Lewis Research Center test bed, the large autonomous spacecraft electrical power system, and future plans are discussed.

Bryan Walls↗

NASA NTRS1992

Summary of LDEF battery analyses

Tests and analyses of NiCd, LiSO2, and LiCf batteries flown on the Long Duration Exposure Facility (LDEF) includes results from NASA, Aerospace, and commercial labs. The LiSO2 cells illustrate six-year degradation of internal components acceptable for space applications, with up to 85 percent battery capacity remaining on discharge of some returned cells. LiCf batteries completed their mission, but lost any remaining capacity due to internal degradation. Returned NiCd batteries tested an GSFC showed slight case distortion due to pressure build up, but were functioning as designed.

Johnson, Chris↗

NASA NTRS2026

X-Ray Polarization of Z-Type Neutron Star Low-Mass X-Ray Binaries II. Spectropolarimetric Analysis

IXPE has provided for the first time detailed energy- and time-resolved X-ray polarimetry of Z-type neutron star low-mass X-ray binaries (NS-LMXBs) as they move along their color-color diagrams (CCDs). These sources can reach the highest polarization observed for NS-LXMBs in the 2–8 keV range when they move along the horizontal branch. In a previous paper, we characterized the spectral state of a sample of Z-sources using the CCD and estimated the polarization with model-independent analysis. Here, we present detailed spectropolarimetric analysis for each source on each branch using data from IXPE, NICER, and NuSTAR. The continuum X-ray emission of all the sources is well described with a combination of thermal accretion disk emission plus a harder Comptonized component. In addition, reflection features, in particular the relativistically broadened Fe Kα line, are observed for our sources, except GX 5–1. For most of the sources and branches, the main contribution to the X-ray emission and polarization is due to Comptonization: moving from the horizontal branch (HB) to the normal branch (NB), the polarization degree (PD) in the 2–8 keV band varies from about 6% to 3–4%, while the PD is loosely constrained in the flaring branch (FB), due to the shorter exposures. These PD values are significantly higher than theoretical expectations for typical spreading or boundary layer configurations. The polarization of the disk is generally lower (below 3%) but still higher than predictions for an electron scattering-dominated, plane-parallel atmosphere above the disk observed at the corresponding inclination. Moreover, the polarization angle (PA) of the disk seems to be significantly misaligned and not perpendicular to that of Comptonization. We find no correlation between the polarization signal and the inclination, nor with the contribution of reflected photons throughout the Z-track.

accretion↗

NASA NTRS2001

Performance of Li-Ion Cells Under Battery Voltage Charge Control

A study consisting of electrochemical characterization and Low-Earth-Orbit (LEO) cycling of Li-Ion cells from three vendors was initiated in 1999 to determine the cycling performance and to infuse the new technology in the future NASA missions. The 8-cell batteries included in this evaluation are prismatic cells manufactured by Mine Safety Appliances Company (MSA), cylindrical cells manufactured by SAFT and prismatic cells manufactured by Yardney Technical Products, Inc. (YTP). The three batteries were cycle tested in the LEO regime at 40% depth of discharge, and under a charge control technique that consists of battery voltage clamp with a current taper. The initial testing was conducted at 20 C; however, the batteries were cycled also intermittently at low temperatures. YTP 20 Ah cells consisted of mixed-oxide (Co and Ni) positive, graphitic carbon negative, LIPF6 salt mixed with organic carbonate solvents. The battery voltage clamp was 32 V. The low temperature cycling tests started after 4575 cycles at 20 C. The cells were not capable of cycling. at low temperature since the charge acceptance at battery level was poor. There was a cell in the battery that showed too high an end-of-charge (EOC) voltage thereby limiting the ability to charge the rest of the cells in the battery. The battery has completed 6714 cycles. SAFT 12 Ah cells consisted of mixed-oxide (Co and NO positive, graphitic carbon negative, LiPF6 salt mixed with organic carbonate solvents. The battery voltage clamp was for 30.8 V. The low temperature cycling tests started after 4594 cycles at 20 C. A cell that showed low end of discharge (EOD) and EOC voltages and three other cells that showed higher EOC voltages limited the charge acceptance at the selected voltage limit during charge. The cells were capable of cycling at 10 C and 0 C but the charge voltage limit had to be increased to 34.3 V (4.3 V per cell). The low temperature cycling may have induced poor chargeability since the voltage had to be increased to achieve the required charge input. The battery has completed 6226 cycles. MSA 10 Ah cells consisted of Co oxide positive, graphitic carbon negative, LiPF6 salt mixed with organic carbonate solvents. The battery voltage clamp was 30.8 V. The low temperature cycling tests were started after 2182 cycles at 20 C. The cells were capable of cycling at 10 C and 0 C. Like SAFT, the voltage limit on charge had to be increased to 36 V (4.5 V per cell). There was a cell (cell S/N 13) in the battery that showed poor performance features such as low EOD voltage and high EOC voltage. The battery has completed 3441 cycles. A reconditioning procedure that consisted of C15 charge to a taper current of C/100 and C/20 discharge improved the voltage behavior of SAFT and MSA cells with no significant effect on YTP cells. We have demonstrated that the charge operation with VT clamp at battery rather than at cell level is feasible for onboard Li-Ion battery operation.

Rao, Gopalakrishna M.↗

NASA NTRS2026

Characterizing the subglacial environment of lower Thwaites Glacier using radar modeling

Understanding the spatial heterogeneity beneath Thwaites Glacier, West Antarctica, is vital to projecting its impact on future sea levels. Radar-echo sounding (RES) is commonly used to infer subglacial conditions, but these data can be challenging to interpret. We assess basal heterogeneity across Thwaites Glacier by comparing RES returns to a radar backscattering simulator for over 400 km of RES data. The modeled variations in bed returned power exhibited a strong correlation with actual RES data in 40% of our simulated flight segments, which we consider evidence for a relatively homogeneous glacier bed. Other sites (40%) demonstrated improved fit quality when hydrology or substrate transitions were introduced in the bed material model. The remaining simulated segments (20%) were diagnosed as having more complex basal heterogeneity. The spatial distribution of complex heterogeneity appears to coincide with asymmetric patterns in the RES specularity content, which has been interpreted in previous studies as a signature for channelized hydrology. Conversely, the homogeneous substrate locations coincide with areas of fast-moving ice in western Thwaites. Our simulation method can isolate power variations induced by material heterogeneity vs topography, which is an important limitation of existing RES analysis methods.

Antarctic glaciology↗

NASA NTRSDate not supplied

Predicting Team Functioning in Long Term Space Missions Using Acoustic and Linguistic Measures

Maintaining optimal team functioning is critical for long-duration space exploration missions, yet traditional monitoring methods, such as self-reports and wearable sensors, often impose operational burdens or suffer from bias. This paper investigates a non-intrusive speech-based artificial intelligence (AI) framework to predict degradations in team functioning using data from the Human Exploration Research Analog (HERA) of the U.S. National Aeronautics and Space Administration (NASA). Using acoustic features, linguistic descriptors, and semantic embeddings, we evaluate static non-linear and temporal machine learning models to predict both objective (task accuracy) and subjective (self-reported efficacy and cohesion) team functioning outcomes. Results indicate that temporal models outperform static approaches, with prediction of objective task accuracy in Team Interaction Battery (TIB) improving from near chance to 71%. Self-reported outcomes, including team efficacy and cohesion, are predicted more reliably than task performance, achieving balanced accuracies of up to 85.56% and 78.12%, respectively, and are found to be most strongly associated with acoustic features. In a second interdependent task, the MMSEV–EVA, accuracies of up to 78% are achieved using temporal models with acoustic features. Furthermore, incorporating just 1–2 days of team-specific historical data systematically improved performance, and acoustic markers from informal pre-task interactions provided modest predictive gains. Finally, while automated preprocessing yielded viable accuracy, humancorrected data provided moderate performance gains, though transcription error rates did not significantly correlate with model performance. These findings highlight the potential of speech as a passive, high-fidelity monitoring tool for autonomous habitats.

Temporal modeling↗

NASA NTRS1995

Transitional Flow in Thin Tubes for Space Station Freedom Radiator

A two dimensional finite volume method is used to predict the film coefficients in the transitional flow region (laminar or turbulent) for the radiator panel tubes. The code used to perform this analysis is CAST (Computer Aided Simulation of Turbulent Flows). The information gathered from this code is then used to augment a Sinda85 model that predicts overall performance of the radiator. A final comparison is drawn between the results generated with a Sinda85 model using the Sinda85 provided transition region heat transfer correlations and the Sinda85 model using the CAST generated data.

Patrick Loney↗

NASA NTRS1974

Skylab Experiment M552: Exothermic Brazing

The M552 Skylab experiment reveals that brazing in space is feasible. It successfully demonstrated the ability to retain molten metal within a braze tube joint system. Surface energy was the dominant operative force system controlling liquid metal for this experiment. The zero gravity environment for brazing resulted in several differences; increased solubility, increased liquid spreading, more uniform menisci (liquid/vapor interface) and a reduction of braze alloy shrinkage defects. The residual radioactive intensity and location of the redistributed isotope was interpreted to provide a sequential history of braze alloy movement during the melt-flow-solidification stages of the process. Convection theory applied to M552 was validated but some results were not explainable by it, i.e., increased nickel transport and the radial mixing of the silver isotope on samples SLN-2 and SLN-4. All characteristics of thermal analysis appeared to react as expected but heat conduction rates increased because of increased extent, rate and uniformity of braze alloy spreading.

J R Williams↗

NASA NTRSDate not supplied

Kalman Filtering and RTS Smoothing for Arc-Jet Sample Edge Tracking

Accurate and temporally consistent measurements of test-article recession are required to characterize material response during arc-jet ablation experiments. However, image-based boundary measurements are often affected by segmentation noise, brightness variations, and frame-to-frame variability. This work extends arcjetCV [1] with filtering methods for tracking the evolving boundaries of hemispherical and ISO-Q test articles. Two boundary-tracking approaches based on Kalman filtering [2] were implemented. The first applies a point-wise Kalman filter followed by a Rauch–Tung–Striebel smoother [3] to individual boundary-point locations. The second applies the same filtering and smoothing framework to a reduced set of geometry-dependent shape parameters. The point-wise method reduces local frame-to-frame fluctuations while preserving spatial details along the detected boundary. The shape-parameter method provides a compact and geometrically constrained estimate of the sample contour. Figure 1 illustrates the two approaches for a hemispherical test article. Both methods improve temporal consistency and support more robust estimation of surface recession from arc-jet imagery. The two filtering approaches provide complementary representations of boundary evolution and improve the reliability of image-based recession measurements during arc-jet experiments.

recession measurement↗

NASA NTRSDate not supplied

BEAST: Expanding Sustainable Data Infrastructure for High-Enthalpy Facilities

Reproducible, data-driven thermal protection system (TPS) research requires that experimental records from high-enthalpy testing be consistently structured, traceable, and accessible across campaigns and institutions. In practice, however, arcjet and plasma facilities data remain largely fragmented: raw diagnostics are stored in ad hoc formats, material sample histories are disconnected from test conditions, and metadata standards are absent, precluding systematic cross-campaign analysis and long-term reuse. BEAST (Backend for Experiment Analysis, Storage, and Traceability) is an open-source, web-based platform that addresses these limitations by providing a unified, queryable infrastructure for high-enthalpy ground-test data [1]. First presented at the 15th Ablation Workshop [2], BEAST has since undergone significant development. The platform ingests and structures multi-channel time-series diagnostics, facility configurations, and material property records within a common provenance model, ensuring end-to-end traceability from raw sensor acquisition to reduced experimental quantities. A versioned material library links specimen identity and processing history to the specific runs in which each sample was tested. An integrated modeling workbench enables training and evaluation of regression models directly on archived experimental data, supporting condition interpolation and the construction of empirical material response databases. Beyond its original deployment at NASA Ames Research Center, BEAST has been designed to be facility-agnostic, with ongoing efforts to extend its adoption to other facilities. Its modular architecture accommodates heterogeneous diagnostic setups and facility types, and its future open-source distribution allows institutions to build on a common data standard rather than maintaining isolated, bespoke solutions. BEAST is further integrated within a broader ecosystem of companion tools: arcjetCV [3] extracts recession rates and shock standoff distances from high-speed video using computer vision, and miniSTARscan [4] provides sub-minute, portable photogrammetric surface reconstruction of test articles before and after exposure. All tools share a common data schema, enabling seamless ingestion of surface geometry, imagery, and time-series data into a single, coherent experimental record.

Database↗

NASA NTRSDate not supplied

BEAST: Expanding Sustainable Data Infrastructure for High-Enthalpy Facilities

Database↗

NASA NTRS2026

Proactive Wildfire Management: A Remote Sensing and Multimodal CNN-MLP Architecture for Ignition Risk Forecasting

As the frequency and intensity of wildfires increase, with fire seasons now starting earlier and ending later than they have over the past decades, current monitoring systems, such as lookout towers and satellites, are hindered by cloud cover, low-resolution imagery, and static data gaps that fail to track vegetation moisture levels fast enough to catch rapid pre-ignition changes. This report proposes a Machine Learning-enabled Wildfire Ignition Prediction framework that combines satellite monitoring with dynamic and high-resolution remote sensing from Unmanned Aerial Vehicle (UAV) swarms. The method would use multispectral and thermal data from the Landsat program to create a baseline for vegetation health, calculating a two-band Enhanced Vegetation Index (EVI2) and the moisture content of the vegetation. These inputs will later be fused with microscale UAV weather data, including thermal hotspots found through thick canopies, hyperspectral chemical signatures of pre-visual combustion, and local weather streams. The multispectral satellite, multispectral Light Detection and Ranging (LiDAR), and thermal data would then be processed through a Convolutional Neural Network (CNN), alongside a Multilayer Perceptron (MLP) for the micro-weather telemetry. The outputs of these networks would be fused into a single feature representation and passed through a final prediction network to generate real-time ignition risk scores and hotspot alerts. Model performance would be assessed using standard classification metrics, including a Receiver Operating Characteristic - Area Under the Curve (ROC AUC) and F1 score. This system would allow first responders to identify high-risk zones and intervene before ignition occurs, improving emergency response time compared to current approaches.

machine learning↗

NASA NTRS2014

Online Prediction of Battery Discharge and Estimation of Parasitic Loads for an Electric Aircraft

Predicting whether or not vehicle batteries contain sufficient charge to support operations over the remainder of a given flight plan is critical for electric aircraft. This paper describes an approach for identifying upper and lower uncertainty bounds on predictions that aircraft batteries will continue to meet output power and voltage requirements over the remainder of a flight plan. Battery discharge prediction is considered here in terms of the following components; (i) online battery state of charge estimation; (ii) prediction of future battery power demand as a function of an aircraft flight plan; (iii) online estimation of additional parasitic battery loads; and finally, (iv) estimation of flight plan safety. Substantial uncertainty is considered to be an irremovable part of the battery discharge prediction problem. However, high-confidence estimates of flight plan safety or lack of safety are shown to be generated from even highly uncertain prognostic predictions.

Battery Discharge Prediction↗

NASA NTRS1982

Nickel-hydrogen bipolar battery systems

Nickel-hydrogen cells are currently being manufactured on a semi-experimental basis. Rechargeable nickel-hydrogen systems are described that more closely resemble a fuel cell system than a traditional nickel-cadmium battery pack. This has been stimulated by the currently emerging requirements related to large manned and unmanned low earth orbit applications. The resultant nickel-hydrogen battery system should have a number of features that would lead to improved reliability, reduced costs as well as superior energy density and cycle lives as compared to battery systems constructed from the current state-of-the-art nickel-hydrogen individual pressure vessel cells.

Thaller, L. H.↗

NASA NTRS2026

Influence of Processing Parameters on the Mechanical Properties of 3D Printed Borosilicate Particulate Reinforced Polymer Composites

Emerging composite materials are expanding the potential of additive manufacturing and enabling applications previously restricted by traditional manufacturing methods. The multi-phase nature of these composite materials combined with the complex in-ternal geometry of additively manufactured parts have enabled unique behavior, and potentially new applications. Additionally, these materials can be pyrolyzed to create dense metal, ceramic, and glass parts with geometries typically not achievable by tra-ditional processes. Additive manufacturing of borosilicate glass-based systems can open new applications in nuclear engineering, astronomy, and bone regrowth therapy. To elucidate the process-parameter relationship of borosilicate-polylactic acid (PLA) composites, mechanical testing was conducted and compared with a pure polylactic acid polymer baseline. Test specimens were fabricated by fused-filament fabrication with minimal post-processing. Yield strength, ultimate strength, and elastic modulus were calculated from stress-strain curves. Optical and scanning electron microscopy were conducted to observe the specimen microstructure before and after testing. The highest compressive yield strength for the composite was 28.22 MPa, and the highest compressive yield strength for PLA was 49.30 MPa. Print orientation was found to benefit the composite material but have a detrimental effect on the pure matrix material. An elastic modulus of 2.66 GPa was recorded for the borosilicate-PLA composite at 100% infill, 1 shell wall, and layer lines parallel to compression axis. Microscopy revealed that lower modulus composite specimens had the particulates re-distributed within the matrix. Tensile testing was done according to a polymer testing standard, which caused difficulties obtaining consistent fracture within the gauge length.

mechanical testing↗

NASA NTRSDate not supplied

Revisiting the Soyuz-1 Parachute Failure in the Context of Safety in the Modern Era

The Soyuz‑1 accident remains one of the most consequential parachute related failures in human spaceflight history and provides enduring lessons for modern Entry, Descent, and Landing (EDL) system design. Occurring during the height of the Cold War and the Space Race, the mission unfolded under extraordinary political and schedule pressure as the Soviet Union sought to maintain its early leadership in space achievements following the death of chief designer Sergei Korolev. Despite unresolved propulsion, electrical, and parachute system deficiencies, Soyuz‑1 proceeded to launch and immediately encountered critical inflight anomalies, including a failed solar panel deployment, attitude control issues, and communication dropouts. Upon reentry, a malfunction in the parachute system, driven by a primary main canopy that failed to deploy, and subsequent entanglement of the reserve main canopy with the primary drogue parachute, resulted in insufficient deceleration and the fatal crash of cosmonaut Vladimir Komarov. Subsequent investigations revealed deep rooted cultural and organizational issues within the Soviet space program, including inadequate testing, suppression of dissent, undocumented last minute design changes, and the absence of integrated parachute system verification. More than 200 design flaws were identified after the accident, and firsthand accounts, including those from Yuri Gagarin, highlighted widespread concern prior to launch. Over time, the Soviet program implemented substantial reforms: systematic design corrections, rigorous process documentation, and an extensive series of drop tests that ultimately transformed the Soyuz system into one of the world’s most reliable human-rated return vehicles. This paper examines the technical architecture of the Soyuz‑1 parachute system, reconstructs the likely deployment sequence and failure mechanism, and analyzes the cultural contributors that shaped the accident. The study draws parallels to modern spacecraft parachute development, emphasizing the critical importance of integrated system testing, transparent engineering culture, and continuous hardware surveillance. These lessons remain directly relevant to today’s NASA and Commercial Crew Programs (CCP), where the Government continues to refine its understanding of aggregate risk and strengthen overall astronaut safety in the face of increasingly complex parachute systems.

Aaron L Morris↗