Initial Analysis of Varied Advanced Air Mobility Noise and Geographic Area Response Difference (VANGARD) Test
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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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The laser transmission and monitoring system for the Galileo Optical Experiment (GOPEX) at the Table Mountain Facility (TMF) in Wrightwood, California is described. The transmission system configuration and the data measurement techniques are described. The calibration procedure and the data analysis algorithm are also discussed. The mean and standard deviation of the laser energy transmitted each day of GOPEX show that the laser transmission system performed well and within the limit established in conjunction with the Galileo Project for experiment concurrence.
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Modern space propulsion and exploration system designs are becoming increasingly sophisticated and complex. Determining the health state of these systems using traditional methods is becoming more difficult as the number of sensors and component interactions grows. Data-driven monitoring techniques have been developed to address these issues by analyzing system operations data to automatically characterize normal system behavior. 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 for analysis of archived events. Ongoing and developing IMS space operations applications include International Space Station flight control, satellite vehicle system health management, launch vehicle ground operations, and fleet supportability. As a common thread of discussion this paper will employ the evolution of the IMS data-driven technique as related to several Integrated Systems Health Management (ISHM) elements. Thematically, the projects listed will be used as case studies. The maturation of IMS via projects where it has been deployed, or is currently being integrated to aid in fault detection will be described. The paper will also explain how IMS can be used to complement a suite of other ISHM tools, providing initial fault detection support for diagnosis and recovery.
A planetary rover will be traversing largely unknown and often unknowable terrain. In addition to geometric obstacles such as cliffs, rocks, and holes, it may also have to deal with non-geometric hazards such as soft soil and surface breakthroughs which often cannot be detected until rover is in imminent danger. Therefore, the rover must monitor its progress throughout a traverse, making sure to stay on course and to detect and act on any previously unseen hazards. Its onboard planning system must decide what sensors to monitor, what landmarks to take position readings from, and what actions to take if something should go wrong. The planning systems being developed for the Pathfinder Planetary Rover to perform these execution monitoring tasks are discussed. This system includes a network of planners to perform path planning, expectation generation, path analysis, sensor and reaction selection, and resource allocation.
The topics discussed are presented in viewgraph form and include Air Force nickel hydrogen standardization goals, philosophy, project outline, cell level standardization, battery level standardization, and schedule.
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Embodiments include an iron-air rechargeable battery having a composite electrode including an iron electrode and a hydrogen electrode integrated therewith. An air electrode is spaced from the iron electrode and an electrolyte is provided in contact with the air electrode and the iron electrodes. Various additives and catalysts are disclosed with respect to the iron electrode, air electrode, and electrolyte for increasing battery efficiency and cycle life.
This project, conducted by TDA Research, Inc. in collaboration with GE Research under DOE Award DE-FE0032261, developed and demonstrated advanced structured sorbent-coated contactors for the high-performance Direct Air Capture (DAC) of CO 2 .
Modern space propulsion and exploration system designs are becoming increasingly sophisticated and complex. Determining the health state of these systems using traditional methods is becoming more difficult as the number of sensors and component interactions grows. Data-driven monitoring techniques have been developed to address these issues by analyzing system operations data to automatically characterize normal system behavior. 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 for analysis of archived events. Ongoing and developing IMS space operations applications include International Space Station flight control, spacecraft vehicle system health management, launch vehicle ground operations, and fleet supportability. As a common thread of discussion this paper will employ the evolution of the IMS data-driven technique as related to several Integrated Systems Health Management (ISHM) elements. Thematically, the projects listed will be used as case studies. The maturation of IMS via projects where it has been deployed or is currently being integrated to aid in fault detection will be described. The paper will also explain how IMS can be used to complement a suite of other ISHM tools, providing initial fault detection support for diagnosis and recovery
Inductive power transfer (IPT) systems provide a flexible, hands-free charging opportunity to electric vehicles (EV). The resonant network components and the transmitter and receiver coils are often subjected to high voltages or currents. Component aging in the compensation network and coils of resonant IPT systems is detrimental to the reliability and power transfer efficiency of the IPT system. Monitoring the component health of such multi-element complex systems requires robust optimization algorithms. This paper discusses condition monitoring of a resonant IPT system for an EV charger using a digital twin model. A hybrid estimation algorithm based on genetic algorithms and adaptive particle swarm optimization is developed to estimate the parameters of the digital twin model. Simulation results are used to verify the monitoring capabilities of the developed algorithm under various operating conditions of the IPT system.
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Electric aviation faces a major challenge of avoiding potentially catastrophic consequences of the battery’s thermal runaway while keeping the weight of the battery low. Detection of early warning signals of battery failures requires accurate monitoring of the battery’s health throughout its lifespan. However, identifying the parameters of the battery from field data is notoriously difficult. We investigate this problem within the framework of modeling the temperature dynamics of a Li-ion cell during tests simulating loading in electric aircraft flights. It is found that the parameters of a higher-fidelity physics-based thermal model cannot be identified from the simulated flight data. To resolve this issue, we reduce the higher-fidelity thermal model to a model with fewer parameters. The resulting reduced-order model can predict temperature dynamics accurately and is identifiable throughout the cell’s lifespan which allows using the model’s parameters to monitor the state-of-health of the aging cell and detect anomalies in thermal behavior.
Microbial monitoring onboard the International Space Station (ISS) is essential for assessing the efficiency of the Environmental Control and Life Support Systems (ECLSS) and providing insight into potential risk to both crew and spacecraft. Historically, this monitoring required the need to culture organisms onboard, return these cultures to Earth, and then complete the identifications, a process that would take months. Over the past decade, and through numerous payloads, advances in molecular biology have enabled in-flight microbial identifications using nanopore sequencing. The swab-to-sequencer method resulting from these efforts was transitioned from research to operations for microbial monitoring under the Crew Health Care Systems (CHeCS) BioMole. Collectively, these accomplishments have propelled the swab-to-sequencer method to be selected as the Microbial Surface Monitor (MSM) for Gateway, as well as a payload on Artemis IV. However, the lack of cold stowage availability for Artemis requires modifications to the entire method due to the thermal instability of the reagents required for sample preparation. To achieve this, new development, optimization, and validations were undertaken. Key considerations included enzyme concentration, buffer compatibility, and equal or enhanced sensitivity and specificity. At each step, thorough side-by-side comparisons with the current ISS method were performed. The development of a robust shelf-stable method will ensure continued sequencing-based microbial monitoring for Artemis and beyond, providing data in near real-time, enhancing risk response time, and yielding clear insight into the microbiome of spacecraft.
This paper briefly describes the spacecraft and ground systems monitoring process at the Jet Propulsion Laboratory and highlights some difficulties associated with the existing technology used in mission operations. A new automated system based on artificial intelligence technology is described which seeks to overcome many of these limitations. The system, called the Spacecraft Health Automated Reasoning Prototype (SHARP), is designed to automate health and status analysis for multi-mission spacecraft and ground data systems operations. The SHARP system has proved to be effective for detecting and analyzing potential spacecraft and ground systems problems by performing real-time analysis of spacecraft and ground data systems engineering telemetry. Telecommunications link analysis of the Voyager 2 spacecraft was the initial focus for evaluation of the system in a real-time operations setting during the Voyager spacecraft encounter with Neptune in August, 1989. The SHARP system will be delivered to the JPL Space Flight Operations Center for regular use by planetary flight projects, including the Galileo and Magellan spacecraft, and will also be applied to monitoring and control applications in the Deep Space Network's Network Operations Control Center.
The 1998 NASA Seal/Secondary Air System Workshop was divided into three major areas with limited materials presented in Volume II: (1) overviews of the (NASAs high speed research (HSR) and DOE's advanced turbine engine systems (ATS)) gas turbine programs and the general aviation program (GAP) with emphasis on sealing methods and results; (2) sealing concepts and methods and results including experimental facilities and numerical predictions; and (3) reviews of the numerical engine simulation and aerospace vehicles and concepts (Trailblazer, Bantam, and X-38).
Exploration missions beyond low-earth-orbit (LEO) will require advanced instrumentation to monitor water quality. Traveling beyond LEO means the transfer of water samples to an Earth-based laboratory for detailed analysis is not feasible. Detailed analysis of water composition during exploration is still necessary, because having the capability to determine the specific organic chemical causing a change in total organic carbon (TOC) or the specific metal or ionic species causing a change in conductivity has the potential to inform the crew health and system management decisions. On a new vehicle such as a lunar or Mars surface habitat or a Mars transit vehicle, finding “new” impurities not seen on ISS should be expected. The key is to identify the impurity so the correct action can be taken. On ISS we can measure TOC, conductivity, and other physical properties but do not have the capability for detailed analysis using vehicle instrumentation. This is acceptable because ISS can send samples down to Earth for further analysis and obtain the detailed composition. The Spacecraft Water Impurity Monitor (SWIM) will provide detailed water quality analysis for missions in which sample down mass is not available. SWIM is a system comprising organic and inorganic analysis modules. For organic chemicals, a gas chromatograph mass spectrometer (GCMS) detects and identifies organic impurities. For inorganic species, a capillary electrophoresis capacitively coupled contactless conductivity detection (CE-C4D) system as well as ion specific electrodes detect and identify metal ions and other inorganic salts / acids. The SWIM technology demonstration project has completed a System Requirements Review (SRR) to finalize detection requirements and is currently working to refine vehicle interface requirements for a future technology demonstration. The project also has begun preliminary flight design activities for the core analyzers in the instrument suite.
The Microbial Air Sampler was used on mission days 1, 7, and 13 in the Spacelab during STS-50/USML-1. Microbial air samples were collected using two types of media strips containing agar (Rose Bengal for yeast and molds, TSA for bacteria). The bacterial level found on day 1 was lower than experienced on previous Spacelab missions. A high level of fungi was present on day 1, however subsequent samples on days 7 and 13 did not indicate fungal growth. Bacterial growth was also minimized in this microgravity environment as the mission progressed. No pathogenic microorganisms were isolated, and the health risk from airborne microbes was minimal throughout the mission.