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407 records · Page 13

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

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

General Purpose Data-Driven Monitoring for Space Operations

As modern space propulsion and exploration systems improve in capability and efficiency, their designs are becoming increasingly sophisticated and complex. Determining the health state of these systems, using traditional parameter limit checking, model-based, or rule-based methods, is becoming more difficult as the number of sensors and component interactions grow. Data-driven monitoring techniques have been developed to address these issues by analyzing system operations data to automatically characterize normal system behavior. System health can be monitored by comparing real-time operating data with these nominal characterizations, providing detection of anomalous data signatures indicative of system faults or failures. Data-driven techniques have a number of advantages over other methods for monitoring complex space vehicles. Unlike model-based systems, the developer does not need to understand or encode the internal operation of the system. The knowledge required to monitor the system is automatically derived from archived data from system operation. Unlike rule-based systems, data-driven systems do not require system analysts to define nominal relationships among sensors. Analysts can and often do determine these relationships for a system with few sensors; it is more difficult to analytically determine the nominal relationship among a large number of sensors. Data-driven techniques are not limited to low-dimensional spaces and work as effectively with dozens of parameters as they do with a few. Knowledge bases formed by data-driven techniques are also easy to update. As the operating envelope of the monitored system is expanded, data-driven techniques can be quickly retrained to incorporate the new behavior into the knowledge base. The expertise and time-consuming process of updating a model or rule base to maintain consistency with the new operation is not required. The Inductive Monitoring System (IMS) is a data-driven system health monitoring software tool that has been successfully applied to several aerospace applications. IMS uses a data mining technique called clustering to analyze archived system data and characterize normal interactions between parameters. This characterization, or model, of nominal operation is stored in a knowledge base that can be used for real-time system monitoring or analysis of archived events. System data is compared with the nominal IMS model to produce a measure of how well current system behavior matches the normal behavior defined by the training data. Significant deviations from the nominal system model can provide alerts to system malfunctions or precursors of significant failures. The scope of IMS based data-driven monitoring applications continues to expand with current development activities. Successful IMS deployment in the International Space Station (ISS) flight control room to monitor ISS attitude control systems has led to applications in other ISS flight control disciplines, such as thermal control. It has also generated interest in data-driven monitoring capability for Constellation, NASA's program to replace the Space Shuttle with new launch vehicles and spacecraft capable of returning astronauts to the moon, and then on to Mars. Several projects are currently underway to evaluate and mature the IMS technology and complementary tools for use in the Constellation program. These include an experiment on board the Air Force TacSat-3 satellite, and ground systems monitoring for NASA's Ares I-X and Ares I launch vehicles. The TacSat-3 Vehicle System Management (TVSM) project is a software experiment to integrate fault and anomaly detection algorithms and diagnosis tools with executive and adaptive planning functions contained in the flight software on-board the Air Force Research Laboratory TacSat-3 satellite. The TVSM software package will be uploaded after launch to monitor spacecraft subsystems such as power and guidance, navigation, and control (GN&C). It will analyze data in real-time to demonstrate detection of faults and unusual conditions, diagnose problems, and react to threats to spacecraft health and mission goals. The experiment will demonstrate the feasibility and effectiveness of integrated system health management (ISHM) technologies with both ground and on-board experiments. Initially, the TVSM software will run open loop, providing system health information and recommendations to ground operators, without automatically performing fault-mitigating corrective actions. After the end of the satellite's mission, closed loop tests combining TVSM monitoring and diagnosis with reactive capabilities by the flight software will be performed. In addition to monitoring for long periods of actual operation, the experiment will include fault injection into TacSat-3 data as well as commanded operations to test and evaluate automatic ISHM monitoring and recovery under controlled conditions.

Satellites

Preparation of the Ice Certification of the Dornier 328 Regional Airliner By Numerical Simulation and By Ground Test

The Dornier 328, a new regional airliner, is to be qualified to FAR25/JAR25 requirements for operation into known icing conditions. All lifting surfaces are pneumatically deiced. Impingement limits were determined using a validated computational fluid dynamic (CFD) code. Wind tunnel tests with a model of the whole aircraft and the isolated empennage equipped with artificial ice shapes showed a degradation of handling characteristics due to ice accretion. Extensive two and three dimensional CFD calculations evaluated ice accretion at the deflection elevator horn. Icing tunnel tests were performed with a model of the horizontal tail with icing similitude fulfilled. The Dornier Do328 powerplant air induction system has successfully completed a program of icing tests in support of aircraft certification for operation into known icing conditions. Potential flight icing conditions were extensively analyzed using a CFD potential flow code and 3-D particle tracking routine to identify critical flight icing conditions. The tunnel test program verified the analytically predicted critical ice accretion surfaces of the air induction system, the adequacy of the ice protection provisions and demonstrated compliance with the applicable (JAR25) regulatory material.

D Welte

The Solid Surface Combustion Experiment Aboard the USML-1 Mission

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

Robert A Altenkirch

Controls for Electrified Aircraft Propulsion

Advanced electrified aircraft propulsion (EAP) concepts with integrated power, propulsion, and thermal systems require the development of equally sophisticated controllers to fly safe and efficient missions. Hybrid electric aircraft utilize electric machines mechanically coupled to the engine shafts to extract and insert power for a variety of purposes. Additionally, electric machines may drive propulsive fans pulling from a combination of on-board energy storage devices and engine extracted power. NASA’s investment in hybrid electric aircraft hardware-in-the-loop testing enables controls research on representative engine models using a novel emulation and scaling methodology. High-voltage, high-power electrical powertrain presents several technical risks at altitude. High-power requires high efficiency to minimize losses. Superconducting electric machines and power distribution research at NASA has identified key challenges with potential controls solutions. These risks necessitate the development of controllers robust to model uncertainty, disturbances, and fault conditions. System health management and fault detection schemes play an important role in a multi-layer controls approach that utilizes a supervisor which oversees inner loops for the highly coupled power, propulsion, and thermal systems. Such a supervisory controller enables coordinates energy transfer between engines, energy storage devices, electric machines, propulsors, and heat exchangers. Existing methods have shown an improvement in engine operability using the hybrid electric powertrain.

Halle E Buescher

Behavior of Ullage Bubbles During Blowdown in Low-g Experiment (BUBBLE): Overview of a Cryogenic Tank Depressurization Test

Behavior of Ullage Bubbles during Blowdown in Low-g Experiment (BUBBLE) is a cryogenic tank depressurization drop tower experiment currently being designed at NASA Glenn Research Center. There is a need for liquid level rise data while venting a cryogenic propellant tank below the liquid saturation pressure in a reduced gravity environment. When a cryogenic tank is vented to a vapor pressure below the liquid saturation pressure, bubbles become entrained in the liquid causing the bulk liquid-vapor interface to rise. In reduced gravity, bubble rise velocity is diminished leading to a larger liquid level rise compared to a 1g environment. The purpose of the experiment is to gain further understanding of tank depressurization fluid physics and obtain high-fidelity data for model validation in 1g and reduced gravity environments. On-orbit cryogenic propellant tanks operating at high fill levels must efficiently manage venting operations to avoid the risk of liquid entrainment in the vent line, which could lead to asymmetric control thruster loads, freezing and clogging, and loss of liquid propellant. Validated models could be used to design settling and venting profiles to reduce risk and increase efficiency for cryogenic storage and transfer operations.

tank venting

Avalanche Photodiode Statistics in Triggered-Avalanche Detection Mode

The output of a triggered avalanche mode avalanche photodiode is modeled as Poisson distributed primary avalanche events plus conditionally Poisson distributed trapped carrier induced secondary events. The moment generating function as well as the mean and variance of the diode output statistics are derived. The dispersion of the output statistics is shown to always exceed that of the Poisson distribution. Several examples are considered in detail.

H H Tan

Cammatic: an Approach to Improve DSS 13 Antenna Gravity-Loading Performance

Corrective actuator forces are applied to the DSS 13 antenna structure to improve its accuracy. These forces are calibrated according to the antenna elevation requirements. The calibration is derived from accurate field measurements and is not subject to the errors that result from computer modeling. A successful demonstration provided significant antenna surface improvement. An improvement of 0.6 to 1 dB is predicted.

R Levy

Multikilowatt Bipolar Nickel/Hydrogen Battery

High energy densities appear feasible. Nickel/hydrogen battery utilizing bipolar construction in common pressure vessel, addressing needs for multikilowatt storage for low-Earth-orbit applications, designed and 10-cell prototype model tested. Modular-concept-design 35-kW battery projected energy densities of 20 to 24 Wh/b (160 to 190 kj/kg) and 700 to 900 Wh/ft3 (90 to 110 MJ/m3) and incorporated significant improvements over state-of-the-art storage systems.

Source record

X-Ray Polarization From the Atoll 4U 1735−44 Suggests a Low Inclination

X-ray polarimetry is a new tool capable of probing the geometry of accretion onto weakly magnetized neutron stars. Here we present the first X-ray spectro-polarimetric results from coordinated observations of the atoll source 4U 1735−44, conducted with the Imaging X-ray Polarimetry Explorer (IXPE), NICER, and NuSTAR . Over the 2–8 keV energy range, we obtained a marginal detection of polarization with the polarization degree of 1.4% ± 0.7% and polarization angle of −29◦ ± 14◦, corresponding to a 3σ upper limit on the polarization degree of 3.5%. The best-fit model to describe the spectrum comprises a thermal component associated with the accretion disk, a Comptonized black body component, and a relativistic reflection component. From the reflection model, we infer a disk inclination of ∼40◦. The spectroscopic and polarimetric properties of 4U 1735−44 are consistent with those observed in other atoll sources studied by IXPE, with its low polarization likely due to its low inclination

X-rays: binaries

The Role of Disruptive Impacts on Ocean Generation and Longevity in Icy Moons

Among icy moons of the outer Solar System, subsurface water oceans and large collisions both seem to be common, but the impact of the latter on the presence and persistence of the former is unclear and has rarely been investigated. Here we interface a smoothed-particle hydrodynamics model to simulate collisions with a thermal-structural evolution model to simulate the evolution of moons pre-collision, post-collision and without a collision. Overall, even such large-scale collisions affect only the ocean thickness or longevity, and the presence or absence of an ocean is affected for only a part of a moon’s history. In reaccreted moons, the ocean survives the impact and becomes much thicker inside larger moons with radius near 1,000 km, whereas an ocean that would otherwise arise inside moons with radius near 500 km is absent because the collision promotes ice–rock differentiation. Our simulations have not yielded an ocean developed post-impact—whether directly via collisional or reaccretional heating or indirectly through tidal heating due to collision-induced orbital changes—in a moon that would otherwise have remained frozen. The ocean-enhancing effect is pronounced only for late disruptive impacts onto large, 1,000-km-class targets, which are unlikely in recent solar system history.

Marc Neveu

Thermal Inspection for the Assessment of Adhesively Bonded Metal Adherents

Certification of adhesively bonded structures is currently a challenge for aircraft manufacturers. The ability to certify bonds in primary structure can reduce dependence on fasteners and this will enable more efficient manufacturing. For example, drilling holes and installing fasteners in bonded joints can be a potentially significant bottleneck in airframe manufacturing. In addition, fasteners increase the airframe weight and can add stress concentration areas. Reducing fastener count can accelerate manufacturing and improve aircraft performance. NASA is currently investigating nondestructive evaluation (NDE) techniques to assess bond integrity. For example, bond thickness influences bond strength and therefore NDE techniques are being investigated to determine bond thickness. For bonded metal structures, there is a large difference in the thermal diffusivity between the 7075 aluminum alloy metal adherends and aircraft grade adhesive. Multi-layered thermal models show a large variation in the thermal response for bondline adhesive thicknesses that vary from 100 to 300 microns for adherend thicknesses of 0.163 cm. Experimental through-transmission thermal measurements reveal promise to quantitatively characterize the bondline thickness. Results were validated with X-ray computed tomography and optical microscopy measurements, and influence of porosity on the thermal model and measurements are investigated.

bondline thickness

Thermal Inspection for the Assessment of Adhesively Bonded Metal Adherends

Certification of adhesively bonded structures is currently a challenge for aircraft manufacturers. The ability to certify bonds in primary structure can reduce dependence on fasteners and this will enable more efficient manufacturing. For example, drilling holes and installing fasteners in bonded joints can be a potentially significant bottleneck in airframe manufacturing. In addition, fasteners increase the airframe weight and can add stress concentration areas. Reducing fastener count can accelerate manufacturing and improve aircraft performance. NASA is currently investigating nondestructive evaluation (NDE) techniques to assess bond integrity. For example, bond thickness influences bond strength and therefore NDE techniques are being investigated to determine bond thickness. For bonded metal structures, there is a large difference in the thermal diffusivity between the 7075 aluminum alloy metal adherends and aircraft grade adhesive. Multi-layered thermal models show a large variation in the thermal response for bondline adhesive thicknesses that vary from 100 to 300 microns for adherend thicknesses of 0.163 cm. Experimental through-transmission thermal measurements reveal promise to quantitatively characterize the bondline thickness. Results were validated with X-ray computed tomography and optical microscopy measurements, and influence of porosity on the thermal model and measurements are investigated.

X-ray computed tomography

Practical Tips for Setting Up an LS-DYNA MAT_213 Analysis

Since 2012, NASA has actively contributed to the development and application of the LS-DYNA MAT_213 material model to predict responses under dynamic loading events. This presentation provides a high-level overview of MAT_213 and captures practical tips and suggestions for using it.

MAT_213

Use of Assistive Technology to Augment API Capabilities

Application Programming Interfaces (APIs) allow for access to data and capabilities of computer applications by developers or users with experience in computer programming. Recent development with both Thermal Desktop and ESATAN-TMS have provided APIs to allow users to develop their own capabilities that interface with the Graphical User Interfaces (GUI) or manipulate the thermal model data. However, these APIs are only as good as the breadth of features in the native code accessible through the API; if a particular code’s feature is not accessible through the API, then users have very limited options besides waiting for updates to the API that expose the necessary functionality, particularly if model data access or user action, such as a button click, is required. However, Assistive Technology features that allow for differently-abled users to more fully experience a software’s capabilities may be creatively utilized to gain further access to data and capabilities not yet exposed by the API. This paper describes the process to augment the features of the OpenTD API via assistive technology and describes how to identify the application instance, navigate GUI elements, updates values on forms, and execute actions such as selecting a listbox item or clicking a button. It concludes with identifying some of the pitfalls to avoid and describes methods to best implement this approach.

Application Programming Interface

Use of Assistive Technology to Augment API Capabilities

Application Programming Interfaces (APIs) allow for access to data and capabilities of computer applications by developers or users with experience in computer programming. Recent development with both Thermal Desktop and ESATAN-TMS have provided APIs to allow users to develop their own capabilities that interface with the Graphical User Interfaces (GUI) or manipulate the thermal model data. However, these APIs are only as good as the breadth of features in the native code accessible through the API. If a particular code’s feature is not accessible through the API, then users have very limited options besides waiting for updates to the API that expose the necessary functionality, particularly if model data access or user action, such as a button click, is required. However, Assistive Technology features that allow for users with a disability to more fully experience a software’s capabilities may be creatively utilized to gain further access to data and capabilities not yet exposed by the API. This paper describes the process to augment the features of the OpenTD API via assistive technology and describes how to identify the application instance, navigate GUI elements, updates values on forms, and execute actions such as selecting a listbox item or clicking a button. It concludes with identifying some of the pitfalls to avoid and describes methods to best implement this approach.

Application Programming Interface