Search NASASearch

SEARCH · Search NASA

Results for “System-Theoretic Process Analysis”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

997 records · Page 5

Analysis of Screen Channel LAD Bubble Point Tests in Liquid Methane at Elevated Temperature

This paper examines the effect of varying the liquid temperature and pressure on the bubble point pressure for screen channel Liquid Acquisition Devices in cryogenic liquid methane using gaseous helium across a wide range of elevated pressures and temperatures. Testing of a 325 x 2300 Dutch Twill screen sample was conducted in the Cryogenic Components Lab 7 facility at the NASA Glenn Research Center in Cleveland, Ohio. Test conditions ranged from 105 to 160K and 0.0965 – 1.78 MPa. Bubble point is shown to be a strong function of the liquid temperature and a weak function of the amount of subcooling at the LAD screen. The model predicts well for saturated liquid but under predicts the subcooled data.

Reaction Control System

Spacecraft Water Impurity Monitor, a System for Water Quality Analysis on Exploration Missions Beyond Low Earth Orbit

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.

Water Monitoring

Aerothermodynamic Analysis of a Flexible Thermal Protection System under Reentry Loads

The Carryall Block 1 reentry vehicle being developed by Outpost Space utilizes a strut supported semirigid deployable heatshield. This consists of a flexible thermal protection system, a heat-resistant fabric stack, stretched over actuated spars. The advantages of a deployable heatshield include reduced heat loading and earlier deceleration in the trajectory. However, the nature of the flexible thermal protection system necessitates considering the loaded shape of the heat shield. The flexible thermal protection system will deflect under reentry loads leading to areas of higher heating rates as well as a reduced axial coefficient as compared to the nominal shape. The Carryall Block 1 is analyzed using NASA’s FUN3D and DPLR CFD solvers with a deflected shape based on the catenary equations. The aerodynamic results are found to be within a percent for both solvers and both structured and unstructured mesh types. Fluid Structure Interaction (FSI) analysis is currently a work in progress, using file I/O to communicate between FUN3D and LS-DYNA, a commercial nonlinear structural solver. Challenges in deforming the geometry, mesh, and initial results are presented here.

thermal protection system

Test Data Analysis of the Thermodynamic Vent System-Augmented Top Spray Injector Liquid Nitrogen Transfer Experiments

Traditionally, a cryogenic tank must be pre-chilled to some “target” temperature before the main vent valve can be closed to attempt a non-vented fill (NVF) of cryogenic liquid propellant. This methodology is particularly attractive for performing in-space transfer of cryogens due to the unknown location of the liquid/vapor interface in microgravity and the high likelihood of venting liquid if the vent valve is opened during transfer. This paper presents in-depth test data analysis of a Thermodynamic Vent System (TVS) augmented injector used for cryogenic tank chilldown and fill experiments of a thin-walled Titanium tank. Eight tests were conducted using liquid nitrogen across a range of inlet conditions and boundary conditions, and three different chilldown/fill methods. For four of the tests, the injector sprays liquid into the tank as normal, but also uses a TVS heat exchanger to cool the metallic injector itself as well as the main incoming liquid stream. Results show that using the TVS augmented injector simplifies transfer operation via enhanced condensation at the injector surface at the cost of sacrificing only a small amount of propellant.

Thermodynamic Vent System

NASA JSC’s Simulant Development Lab Capabilities and Artemis Testing

The Simulant Development Lab (SDL) is a multifunctional collaborative workspace that supports the development, curation, analysis, testing, and distribution of planetary regolith simulants – including lunar, Martian, asteroidal, and other granular materials. The lab provides a multidisciplinary setting for scientific characterization of simulant physical properties and for engineering evaluations conducted with simulant test beds. To enable this work, the SDL curates and maintains a stock of more than 35 metric tons of simulant material. To evaluate these materials and support testing goals, the lab is equipped with a comprehensive suite of processing tools and analytical instruments. These capabilities enable the SDL’s mission at NASA’s Johnson Space Center to distribute, develop, process, characterize, and test regolith simulants for mission relevant applications. Through controlled and repeatable testing environments that replicate the physical and compositional properties of lunar regolith, the SDL supports Artemis hardware maturation, providing safe, Earth‑based analogs for evaluating systems that must withstand regolith dust interactions, physical wear and abrasion, and operational loads. The facility’s extensive simulant inventory and integrated geological and engineering test infrastructure accelerate technology readiness for Artemis and future exploration campaigns (e.g., future crewed or robotic missions to Mars).

Simulant Development Lab

Spacecraft Water Impurity Monitor, a System for Water Quality Analysis on Exploration Missions Beyond Low Earth Orbit

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.

Water Monitoring

Power and Propulsion Element Steerable High Gain Antenna Lunar Transit Thermal Analysis Tracking Methodology

The Power and Propulsion Element (PPE) is an ion thruster propulsion spacecraft developed as an element of Space Reactor (SR-1) Freedom to provide propulsion, communications and power for the spacecraft. PPE was originally being developed for the use with the lunar orbiting space station Gateway as one of the first two planned elements. PPE was to be launched with the Habitation and Logistics Outpost (HALO) element in a configuration called the Co-Manifested Vehicle (CMV) that would arrive at a Near-Rectilinear Halo Orbit (NRHO) around the Moon via a lunar transit spiral trajectory phase. The PPE communication system is equipped with two Steerable High Gain Antennas (SHGA) each steered by a two-axis gimbal (TAG) mechanism. A thermal analysis was conducted during the near-Earth spiral phase of the mission using Thermal Desktop (TD). This analysis utilized multiple axis Earth tracking articulators in combination with SINDA system internal environmental heating symbols to produce accurate Earth ground station tracking communication system temperatures. This presentation provides an overview of the communication system thermal model and the analysis methodology.

Thermal Analysis

Nickel hydrogen battery expert system

The Hubble Telescope Battery Testbed at MSFC uses the Nickel Cadmium (NiCd) Battery Expert System (NICBES-2) which supports the evaluation of performance of Hubble Telescope spacecraft batteries and provides alarm diagnosis and action advice. NICBES-2 provides a reasoning system along with a battery domain knowledge base to achieve this battery health management function. An effort is summarized which was used to modify NICBES-2 to accommodate Nickel Hydrogen (NiH2) battery environment now in MSFC testbed. The NICBES-2 is implemented on a Sun Microsystem and is written in SunOS C and Quintus Prolog. The system now operates in a multitasking environment. NICBES-2 spawns three processes: serial port process (SPP); data handler process (DHP); and the expert system process (ESP) in order to process the telemetry data and provide the status and action advice. NICBES-2 performs orbit data gathering, data evaluation, alarm diagnosis and action advice and status and history display functions. The adaptation of NICBES-2 to work with NiH2 battery environment required modification to all of the three component processes.

Shiva, Sajjan G.

Design and Analysis of Battery Thermal Management Systems

Thermal management of battery cell packs is a critically needed technology. The purpose of this work is to design new and improved Battery Thermal Management Systems (BTMS) for use in electric airplanes. The BTMS should be 3D printable and hold twelve to sixteen 18650 batteries. To minimize aircraft’s weight, an actively air-cooled battery pack was chosen to avoid the excess weight of water-cooled and phase change material (PCM) cooled packs. As a result, significant changes were made to remove all metal in the pack and replace it with lower density polymer matrix composites (PMCs) which can be additively manufactured. Two air cooled battery pack configurations (traditional propeller fans & bladeless fans) were designed, modeled, and compared. These packs were first modeled in SolidWorks 2021 3D CAD, then imported into COMSOL MultiPhysics to be studied using the “Heat Transfer in Solids and Fluids” module. The design with the bladeless fans eliminated the need to use high conductivity heavy metal to remove unwanted thermal energy. These bladeless fans were designed entirely out of PMCs. This thermal pack design weighs 0.04 kg less than that of the traditional propeller fans design and has increased the battery pack energy density by 8.25 Wh/kg.

Thermal Management System for Battery Packs

Contamination Control and Assessment Strategy for Martian Moons Exploration (MMX)

Martian Moons eXploration (MMX) is a sample return mission from the Martian moon Phobos. The MMX spacecraft is scheduled for launch in 2026 and return to Earth in 2031. The primary science objective of MMX is to reveal the origin of the Martian moons, thereby advancing the understanding of planetary system formation and material transport in the solar system, as well as to observe processes affecting the circumplanetary and surface environments of Mars. The returned sample will be transported to the curation facility at ISAS/JAXA, and the subsequent curation and sample analysis activity will be conducted. As a sample return mission, MMX requires strict contamination control to prevent the intrusion of terrestrial materials.

H Sugahara

Hydrology Copilot: A Cloud-Native Ai System for Hydrological Data Analysis

The emergence of AI-driven Earth observation systems promises to broaden access to petabyte-scale geospatial data beyond domain specialists. However, translating this vision into operational scientific infrastructure requires addressing fundamental challenges in data virtualization, code transparency, and domain-specific reasoning. We present Hydrology Copilot, a cloud-native AI framework for natural-language-driven analysis of Earth observation data. To demonstrate operational capabilities at scale, we implement the system using NASA's North American Land Data Assimilation System version 3 (NLDAS-3), which provides surface meteorological forcing and land-surface model output across North and Central America at 1-km resolution, from which drought diagnostics are derived. The system integrates five core contributions: (1) scalable data virtualization using Kerchunk-based cloud optimized access, achieving a 1.5 to 4.6 times improvement in I/O latency across benchmark queries spanning regional single-day extractions (4.6 times speedup) to continental monthly aggregations (1.5 times speedup); (2) transparent code generation through Microsoft Azure AI Foundry agents that expose executable Python workflows for scientific verification; (3) persistent conversational memory enabling multi-turn analytical discourse across sessions; (4) intelligent query validation that enforces dataset boundaries and resolves ambiguous requests before execution; and (5) a multi-agent architecture coordinating query parsing, code generation, and visualization. We evaluate the system through drought-monitoring workflows, demonstrating reliable code generation, accurate results validated against reference computations and the operational U.S. Drought Monitor, and efficient operation across increasingly complex tasks. By bridging natural-language interfaces with rigorous hydrological analysis, Hydrology Copilot advances beyond proof-of-concept demonstrations to provide a deployable framework for operational Earth science applications.

Data virtualization

The Hyperspectral Microwave Photonic Instrument (HyMPI) and its NEDT Performance

This work presents an overview of a hyperspectral microwave-photonic spectrometer and demonstrates the system end-to-end noise equivalent delta temperature (NEDT) performance. The system aims at augmenting the remote sensing capability from space, with a focus on the Earth’s planetary boundary layer (PBL) thermal microwave (MW) spectral region (0-200 GHz). Combining a Photonic Integrated Circuit (PIC) channelizer and an application-specific integrated circuit (ASIC) spectrometer, the PIC & ASIC (PICASIC) module is capable of processing 40 GHz spectra at hyperspectral (4 MHz) resolution. The photonic technology is agnostic to the spectral region and multiple photonic modules can cover the entire 200 GHz spectrum. Measured results of the end-to-end system NEDT agree with predicted values confirming that the NEDT is primarily dominated by the noise figure of the MW front-end, with the optical link adding no significant noise. The data also demonstrate that a single module enables simultaneous super- and hyper-spectral resolution channel analysis across a 40 GHz range.

spectrometer

Pulsed Electroacoustic Analysis Capabilities at NASA Glenn Research Center

The High Voltage Testing Laboratory at NASA Glenn Research Center is equipped with a pulsed electroacoustic (PEA) analyzer to study space charge phenomena in dielectric materials. Dielectric materials such as those used in high voltage insulation systems are of great interest due to their crucial role in withstanding high voltages and avoiding electrical breakdown in electrified aircraft power systems. Current research is underway for the development of novel lightweight electrical insulation and the thorough evaluation of these materials is required. The PEA instrumentation at NASA GRC is a nondestructive method to evaluate the space charge phenomena which can give a unique insight on the feasibility and lifetime of material systems. The instrumentation capability and initial results are reported here.

pulsed electroacoustic

Thermal Design and Analysis of Green Propulsion Dual Method CubeSat

Green Propulsion Dual Method (GPDM) is a collaboration between NASA Marshall Space Flight Center (MSFC) and Georgia Tech to create a 6U CubeSat demonstrating the use of the green propellant Advanced Spacecraft Energetic Non-Toxic (ASCENT) in two propulsion systems: using a traditional chemical thruster and an electrospray thruster system. The driving thermal considerations includes a planned orbit always in Sun view without any time in Earth’s eclipse, and a chemical thruster reaching 1300°C during firing. Thermal design and analysis on CubeSats are not always emphasized, particularly in experimental or academic environments. This paper will describe the thermal design and analysis performed on GPDM and the mitigations implemented for this mission, which will highlight some of the thermal challenges unique to experimental small satellites.

Thermal Analysis

Thermal Design and Analysis of Green Propulsion Dual Mode CubeSat

Green Propulsion Dual Mode (GPDM) is a collaboration between NASA Marshall Space Flight Center (MSFC) and Georgia Tech to create a 6U CubeSat demonstrating the use of the green propellant Advanced Spacecraft Energetic Non-Toxic (ASCENT) in two propulsion systems: using a traditional chemical thruster and an electrospray thruster system. The driving thermal considerations includes a planned orbit always in Sun view without any time in Earth’s eclipse, and a chemical thruster reaching 1300°C during firing. Thermal design and analysis on CubeSats are not always emphasized, particularly in experimental or academic environments. This paper will describe the thermal design and analysis performed on GPDM and the mitigations implemented for this mission, which will highlight some of the thermal challenges unique to experimental small satellites.

Thermal Analysis

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