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Thrust Chamber Thermal Barrier Coating Techniques

Methods for applying thermal barrier coatings to the hot-gas side wall of rocket thrust chambers in order to significantly reduce the heat transfer in high heat flux regions has been the focus of technology efforts for many years. A successful technique developed by NASA-Lewis that starts with the coating on a mandrel and then builds the thrust chamber around it by electroforming appropriate materials is described. This results in a smooth coating with exceptional adherence, as was demonstrated in hot fire rig tests. The low cycle fatigue life of chambers with coatings applied in this manner was increased dramatically compared to uncoated chambers.

Richard J Quentmeyer

Risks of Depress as a Fire Suppression Technique in Spacecraft

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

Toni Griego

Thin-Film Embedded Sensors for Battery Health Monitoring

Hybrid or all-electric aircraft are being developed as the next generation of aircraft to both allow new forms of aviation and decrease environmental impact. Since these types of aircraft are based on high-capacity battery technology, safe operation of these batteries becomes increasingly important. In particular, the potential for battery failure due to uncontrolled chemical reactions resulting in thermal runaway, catastrophic failure, and battery fires must be addressed in order for such battery technology to have the level of safety needed for standard aviation implementation. Efforts to ensure battery safety often involve engineering solutions that seek to contain rather than prevent such events by early detection. Such approaches increase the system weight and decrease the power per unit mass provided by the battery system. Existing methods for measuring battery parameters to determine the battery state-of-health are limited. These methods include electrical measurements of the cell current and/or voltage output as well as temperature measurements taken externally on the cell surface. Such external temperature measurements are limited in their ability to provide early warning of impending battery failure. In response, an effort to develop sensors operating internal to battery for health monitoring has been ongoing in the NASA Sensor-based Prognostics to Avoid Runaway Reactions & Catastrophic Ignition (SPARRCI) project. The basic approach associated with this sensor work is the deposition of thin film sensors on the battery separator located between the anode and cathode of the battery. These thin film sensors are then monitored to determine changes in battery parameters and health. Microfabrication techniques are employed to minimize the overall impact of the sensors on battery operation through the implementation of sensors with minimal size, weight, and power consumption. The thickness of the films, which are fabricated through physical vapor deposition (sputtering), are on the order of thousands of angstroms and can have minimal surface area. Thin film sensors for system health management have been implemented for a many decades on complex components for aerospace applications. However, the application of thin films of this type on a battery separator for internal battery monitoring applications has not previously been demonstrated to our knowledge. This paper describes the development of sensors for the internal battery monitoring through the use of thin film sensor technology. Thin metal films were successfully deposited on a battery separator polymer material with good adherence and electrical continuity. Multiple types of sensors have been deposited, as well as lead connections from the sensor to the edge of the separator material. The ability of these thin film sensors immersed in electrolyte to perform multiple types of battery parameter measurements has been demonstrated. For example, a multiparameter sensor system measured multiple properties simultaneously inside of a pouch cell over a wide temperature range. Further, real time measurement of interior temperature changes in a battery pouch cell with an integrated interior temperature sensor was demonstrated. These changes include detecting a fault in the battery (shorting) in situ with rapid response time (less than a minute) corresponding to a more limited response by a temperature sensor mounted externally. Other aspects of monitoring battery health were also explored, such as real-time measurement of simulated dendrite growth/metal deposition by sensor on separator material demonstrated. Future efforts will include improvements in the durability of the sensor structure to allow introduction of the approach into standard battery fabrication techniques. Overall, this work is a step forward in providing a method to prevent catastrophic battery failures and provide a foundation for safer, lighter, and higher energy batteries for the electric aircraft industry.

thin film battery health

A method for battery activation

A technique to activate nickel cadmium batteries is described. The method shortened the time required for activation, eliminated the temperature rise in the batteries, and produced a voltage on the discharge that was better than when the C/20 was run for 48 hours during tests. Various methods of activation are described and evaluated. Results of alternate conditioning charge schemes are presented along with voltage/temperature characteristics for multiple level nickel cadmium battery chargers.

Halpert, G.

Autonomous Power Expert Fault Diagnostic System for Space Station Freedom Electrical Power System Testbed

The goal of the Autonomous Power System (APS) program is to develop and apply intelligent problem solving and control to the Space Station Freedom Electrical Power System (SSF/EPS) testbed being developed and demonstrated at NASA Lewis Research Center. The objectives of the program are to establish artificial intelligence technology paths, to craft knowledge-based tools with advanced human-operator interfaces for power systems, and to interface and integrate knowledge-based systems with conventional controllers. The Autonomous Power EXpert (APEX) portion of the APS program will integrate a knowledge-based fault diagnostic system and a power resource planner-scheduler. Then APEX will interface on-line with the SSF/EPS testbed and its Power Management Controller (PMC). The key tasks include establishing knowledge bases for system diagnostics, fault detection and isolation analysis, on-line information accessing through PMC, enhanced data management, and multiple-level, object-oriented operator displays. The first prototype of the diagnostic expert system for fault detection and isolation has been developed. The knowledge bases and the rule-based model that were developed for the Power Distribution Control Unit subsystem of the SSF/EPS testbed are described. A corresponding troubleshooting technique is also described.

Long V Truong

Comparison between the PISO algorithm and preconditioning methods for compressible flow

Two widely used family of algorithms, pressure-based and density-based methods, have been developed for computational fluid dynamics (CFD) problems over the years. Pressure-based methods (such as SIMPLE and PISO) use a Poisson-like equation for updating pressure instead of the continuity equation, while density-based methods use the continuity equation to update density (an equation of state is used to provide density in pressure based schemes and pressure in density based schemes). Pressure-based methods were developed originally for incompressible flows at low Reynolds numbers and were then extended to high Reynolds numbers and compressible applications. On the other hand, density based methods were originally developed for transonic flows and have been extended down to low Mach numbers through the use of preconditioning techniques. We compare these two very different approaches to solving the Navier-Stokes equations in order to gain an understanding of their similarities and differences. Specifically, we consider the PISO scheme as a representative pressure-based method and contrast it with a recently developed preconditioning scheme. We also compare the relative performance of the PISO algorithm with a Euler implicit algorithm that is employed to solve the preconditioned equations by means of a vector stability analysis.

Charles L Merkle

Comparison and Application of Battery Modeling Methods for Conceptual Electric Aircraft

Growing interest in design and optimization of electrified aircraft propulsion concepts prompts the need for accurate, flexible, and efficient methods to model battery systems. Presented in this paper are three battery modeling methods that have been used at NASA’s Glenn Research Center, each representing different mathematical or electrical approaches. Thévenin equivalent circuit, normalization, and curve-fitting methods are compared against battery cell test data for the X-57 Maxwell electric aircraft technology demonstrator. The methods are then applied in a simple multidisciplinary optimization context using NASA’s Six-Passenger Electric Quadrotor concept to determine their applicability and performance. The normalization method achieves the highest accuracy for steady and unsteady discharge rates with a voltage mean error percentage of 0.423% and 1.186%, respectively. Optimal quadrotor mission range between the models varies up to 0.5 nmi, identifying current battery modeling methods as a potentially significant contributor to mission analysis error. A set of relevant tools and techniques for conceptual battery modeling are identified in this paper, with conclusions made on the utility of each modeling approach for various design challenges.

power

Opportunities to Intercalibrate Radiometric Sensors from International Space Station

Highly accurate measurements of Earth's thermal infrared and reflected solar radiation are required for detecting and predicting long-term climate change. Consideration is given to the concept of using the International Space Station to test instruments and techniques that would eventually be used on a dedicated mission, such as the Climate Absolute Radiance and Refractivity Observatory (CLARREO). In particular, a quantitative investigation is performed to determine whether it is possible to use measurements obtained with a highly accurate (0.3%,with 95%confidence) reflected solar radiation spectrometer to calibrate similar, less accurate instruments in other low Earth orbits. Estimates of numbers of samples useful for intercalibration are made with the aid of yearlong simulations of orbital motion. Results of this study support the conclusion that the International Space Station orbit is ideally suited for the purpose of intercalibration between spaceborne sensors.

Intercalibrate

Data Mining for ISHM of Liquid Rocket Propulsion Status Update

This document consists of presentation slides that review the current status of data mining to support the work with the Integrated Systems Health Management (ISHM) for the systems associated with Liquid Rocket Propulsion. The aim of this project is to have test stand data from Rocketdyne to design algorithms that will aid in the early detection of impending failures during operation. These methods will be extended and improved for future platforms (i.e., CEV/CLV).

Ashok Srivastava

Autonomous Detection and Classification of Lunar Minerals Using a Convolutional Neural Network Based Framework for the SUCR DALI Project

NASA’s long-term goal is to deploy humans to the Moon and, from there, advance human exploration to Mars, with Artemis missions as pivotal milestones. Raman spectroscopy can uniquely identify minerals, compounds, water states, and other materials, providing distinctive fingerprints for classification. A Raman instrument has been successfully deployed and utilized on the Mars surface via the Perseverance rover, but has not yet been utilized at the lunar surface The SUCR DALI project is working towards developing a Raman spectroscopy instrument to be applied in various lunar mission concepts, including within the Artemis program. The objective of my research is to assist in the maturation of the proposed SUCR DALI lunar Raman instrument through the development of an autonomous detection and classification model capable of identifying minerals and water states on the Moon’s surface.

Convolutional Neural Networks

Satellite Optical Remote Sensing of Clouds and Aerosols: From Particle Single-Scattering and Gaseous Absorption Through Radiative Transfer to Retrieval Products

Clouds and aerosols are fundamental regulators of Earth’s radiation budget and climate system, influencing both solar and terrestrial radiation through scattering, absorption, and emission processes. Accurate characterization of their physical and radiative properties from space requires a rigorous understanding of particle single-scattering, gaseous absorption, and radiative transfer in the atmosphere, as well as reliable inversion methods. This review synthesizes the physical foundations and algorithmic implementations of satellite-based passive optical remote sensing of clouds and aerosols, spanning the ultraviolet to thermal infrared spectral range. Beginning with electromagnetic scattering theory and state-of-the-art methods for computing single-scattering by nonspherical particles and computationally efficient methods for accounting for atmospheric absorption, we discuss the radiative transfer framework underpinning cloud and aerosol retrievals. The connection between single-scattering and multiple-scattering is rigorously formulated. We then summarize operational and research-grade retrieval techniques, including cloud masking and thermodynamic phase determination, CO₂ slicing for cloud-top pressure, the Nakajima-King shortwave bi-spectral, and infrared split-window approaches for cloud optical thickness and effective particle size, inversion algorithms for determining aerosol properties from multi-spectral and/or multi-angle radiometric and polarimetric measurements, and active-passive sensing synergy. Examples of the global cloud and aerosol climatologies are illustrated using observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Multi-angle Imaging SpectroRadiometer (MISR). Furthermore, the unique strengths of active remote sensing techniques based on spaceborne lidar observations are briefly elaborated in the context of studying ice clouds composed of randomly and horizontally oriented ice crystals, which is a significant challenge for conventional passive remote sensing techniques. By connecting physical theory to practical retrievals, this review highlights both the maturity of current methodologies and the remaining challenges in reducing uncertainties in particle morphology, vertical structure, absorption, and aerosol-cloud interactions. Furthermore, the impact of artificial intelligence (AI) on atmospheric remote sensing is briefly addressed.

Aerosols

Battery Fault Detection with Saturating Transformers

A battery monitoring system utilizes a plurality of transformers interconnected with a battery having a plurality of battery cells. Windings of the transformers are driven with an excitation waveform whereupon signals are responsively detected, which indicate a health of the battery. In one embodiment, excitation windings and sense windings are separately provided for the plurality of transformers such that the excitation waveform is applied to the excitation windings and the signals are detected on the sense windings. In one embodiment, the number of sense windings and/or excitation windings is varied to permit location of underperforming battery cells utilizing a peak voltage detector.

Davies, Francis J.

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

Early Fire Detection System for Partial and Low Gravity Environments

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

Early fire detectioin

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

Ares I-X Ground Diagnostic Prototype

The automation of pre-launch diagnostics for launch vehicles offers three potential benefits: improving safety, reducing cost, and reducing launch delays. The Ares I-X Ground Diagnostic Prototype demonstrated anomaly detection, fault detection, fault isolation, and diagnostics for the Ares I-X first-stage Thrust Vector Control and for the associated ground hydraulics while the vehicle was in the Vehicle Assembly Building at Kennedy Space Center (KSC) and while it was on the launch pad. The prototype combines three existing tools. The first tool, TEAMS (Testability Engineering and Maintenance System), is a model-based tool from Qualtech Systems Inc. for fault isolation and diagnostics. The second tool, SHINE (Spacecraft Health Inference Engine), is a rule-based expert system that was developed at the NASA Jet Propulsion Laboratory. We developed SHINE rules for fault detection and mode identification, and used the outputs of SHINE as inputs to TEAMS. The third tool, IMS (Inductive Monitoring System), is an anomaly detection tool that was developed at NASA Ames Research Center. The three tools were integrated and deployed to KSC, where they were interfaced with live data. This paper describes how the prototype performed during the period of time before the launch, including accuracy and computer resource usage. The paper concludes with some of the lessons that we learned from the experience of developing and deploying the prototype.

Machine Learning

Recommended Practices in Laser-Induced Fluorescence (LIF) Diagnostics for Electric Propulsion

Laser-induced fluorescence (LIF) spectroscopy uses Doppler-shifted laser photons to excite a bound electron transition in an atom or ion, with subsequent fluorescence emission detected in order to measure the local velocity distribution function (VDF) and/or particle density. Due to its non-invasive nature, high spatial resolution, and acceptable difficulty of implementation, LIF has become a favored diagnostic for electric propulsion (EP) plasmas, particularly in the study of Hall thrusters. This paper presents recommended best practices for LIF measurements in electric thrusters, drawn from over three decades of implementation heritage in the EP community. Focusing on both single-photon LIF (typically used to measure VDFs) and two-photon LIF (TALIF, typically used to determine densities), the paper covers selection of atomic transitions to target, experimental setups, and interpretation of data. A number of special topics and advanced applications are discussed, including uncertainty analysis, techniques for high-speed measurements, and applications to a variety of propellants.

plasma plume