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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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Health Monitoring and Prognostics in Li-ion Batteries

Space applications need to overcome a very critical challenge of predicting remaining useful life of its critical systems/subsystems, with batteries being one of them. Batteries, power electronics conditioning system and motors and one of the most critical systems. Similarly in case of electric aircrafts, computing remaining flying time is safety-critical, since an aircraft that runs out of power (battery charge) while in the air will eventually lose control leading to catastrophe. To tackle and solve the prediction problem, it is essential to have awareness of the current state and health of the system, especially since it is necessary to perform condition-based predictions. To be able to accurately predict the future state of any system, it is required to possess knowledge of its current and future operations. Given models of the current and future system behavior, the general approach of model-based prognostics can be employed as a solution to the prior stated prediction problem. Two approaches are presented with battery prognostics application. The first approach presentation covers a physics based-modeling approach implemented for battery prognostics. Given models of the current and future system behavior, a general approach of model-based prognostics can be employed as a solution to the prediction problem and further for decision making. A second hybrid framework for fusing information from physics-based performance models along with deep learning algorithms for prognostics of complex safety critical systems i.e. batteries is presented. In this framework, physics-based performance models infer unobservable model parameters related to the system's components health solving a calibration problem in the deep learning approach.

Batteries↗
DOE OSTI2023

Colocalized Raman spectroscopy – scanning electrochemical microscopy investigation of redox flow battery dialkoxybenzene redoxmer degradation pathways

Non-aqueous redox flow batteries offer high voltages for grid-level energy storage technologies. However, decomposition of the redoxmers - redox-active molecules that make up the anolyte and catholyte in the negative and positive cell compartments - is an important challenge to overcome for long-term storage. Here, we present a spectroelectrochemical study of the catholyte candidate 2,3-dimethyl-1,4-dialkoxybenzene (C7) and its decomposition mechanisms in the presence of a model nucleophilic base, pyridine. We utilize colocalized Raman microscopy and scanning electrochemical microscopy (Raman-SECM) to quantify the chemical rates of decom-position and qualitatively identify the reaction intermediates and products. A detailed study on how the Raman-SECM parameters (electrode distance, substrate electrode, and laser focal height) influence the Raman signal of the charged catholyte C7 ∙+ is presented. Using optimized conditions, we monitored the deprotonation of C7 ∙+ via Raman spectroscopy and the subsequent hydrogen abstraction from solvent molecules to regenerate C7 via electrochemistry. Finite element modeling was used to fit electrochemical and spectroscopic data, quantifying the deprotonation rates as k dep = 2000 and 700 L mol -1 s -1 and abstraction rates as k abs = 0.5 and 0.2 s - 1 in propylene carbonate and acetonitrile solvents, respectively. Our results show the value of spatiotemporal reso-lution in evaluating the chemical and electrochemical behavior of materials for redox flow batteries.

25 ENERGY STORAGE↗
NASA NTRS1998

Structural Loading on the QCM/SAW Instrument Aboard the ER-2 Used for Atmospheric Testing

Several experiments have been proposed to capture and evaluate samples of the atmosphere where SST's travel. One means to achieve this is to utilize the quartz crystal microbalance (QCM) / surface acoustical wave (SAW) instrument installed aboard the ER-2, formerly the U-2 reconnaissance aircraft. The QCM is a cascade impactor designed to perform in-situ, real-time measurements of aerosols and chemical vapors at an altitude of 60,000-70,000 feet. The primary use of the ER-2 is by NASA for Earth resources to test new sensor systems before being placed aboard satellites. One of the main reasons the ER-2 is used for this flight experiment is its capability to fly approximately twelve miles above the sea level (can reach an altitude of 78,000 feet). Because the ER-2 operates at such a high altitude, it is of special interest to scientists interested in space exploration or supersonic aircraft. The purpose of some of the experiments is to extinct data from the atmosphere around the ER-2. For the current CSTEA flight experiment, the housing of the QCM is in a frame that connects to an outer pod that attaches to the fuselage of the ER-2. Due to the location of the QCM within the housing frame and the location of the pod on the ER-2, the pod and its contents are subject to structural loads. In addition to structural loads, structural vibrations are also of importance because the QCM output data is based on the determination of beat frequencies between a pair of oscillators (one coated, the second uncoated, according to the chemical reaction being monitored). A structural analysis of this system can indicate whether potential resonances may exist between the (higher) structural modal frequencies and the beat frequencies. In addition undesirable deformations may result due to maximum expected static or dynamic loads during typical flight conditions. If the deformations are excessive they may adversely affect the accuracy the instrumentation output.

Bainum, Peter M.↗
NASA NTRS2001

Diurnal and Seasonal Cold Lands Signatures in SSM/I-scale Microwave Radiometry of the North Slope of Alaska

In this paper, we explore scaling and data assimilation-related issues associated with utilizing passive microwave satellite observations of Cold Lands-in this case, the climatologically and ecologically sensitive arctic tundra. Our approach expands on our earlier work using a one-year dataset from the Radiobrightness Energy Balance Experiment-3 (REBEX-3). REBEX-3 featured a tower-based SSM/I (Special Sensor Microwave/Imager) simulator deployed on the North Slope of Alaska in 1994-95. Two findings are significant here. First, a comparison of tower and satellite signatures at 19 and 37 GHz strongly suggested that the North Slope is radiometrically homogeneous for spatial scales up to SSM/I footprints (approximately 25 km), an unusual and valuable characteristic for monitoring and retrieving land surface conditions. And second, at the plot scale, signatures of snow/no-snow and freeze/thaw transitions were identifiable for tussock tundra land cover, so that even snow-free frozen tundra could be unambiguously distinguished from tundra covered with dry snow, another unusual and valuable characteristic. We present results from analyzing satellite brightness signatures of selected North Slope pixels corresponding to instrumented sites along a transect from the Brooks Range to the Arctic Ocean. A custom EASE (Equal Area Scalable Earth)-Grid processor was used to extract SSMJI data for every orbit with observations of this region during the 1994-95 year. The resulting high temporal-resolution (4-8 points/day), gridded data were then analyzed for evidence of the same diurnal and seasonal signatures seen at the plot scale (through micrometeorological and/or brightness data). Differences between satellite and tower brightness observations are quantified for various conditions at the REBEX-3 site. Such differences from the less-frequent and/or larger-scale satellite observations represent a form of input 'noise' in data assimilation applications. For the other sites, the performance of snow/no-snow and freeze/thaw discriminators vs. ground truth represents an opportunity to gauge the homogeneity of other pixels.

Kim, Edward J.↗
NASA NTRS2009

Electrical Resistance of SiC/SiC Ceramic Matrix Composites for Damage Detection and Life-Prediction

Ceramic matrix composites (CMC) are suitable for high temperature structural applications such as turbine airfoils and hypersonic thermal protection systems due to their low density high thermal conductivity. The employment of these materials in such applications is limited by the ability to accurately monitor and predict damage evolution. Current nondestructive methods such as ultrasound, x-ray, and thermal imaging are limited in their ability to quantify small scale, transverse, in-plane, matrix cracks developed over long-time creep and fatigue conditions. CMC is a multifunctional material in which the damage is coupled with the material s electrical resistance, providing the possibility of real-time information about the damage state through monitoring of resistance. Here, resistance measurement of SiC/SiC composites under mechanical load at both room temperature monotonic and high temperature creep conditions, coupled with a modal acoustic emission technique, can relate the effects of temperature, strain, matrix cracks, fiber breaks, and oxidation to the change in electrical resistance. A multiscale model can in turn be developed for life prediction of in-service composites, based on electrical resistance methods. Results of tensile mechanical testing of SiC/SiC composites at room and high temperatures will be discussed. Data relating electrical resistivity to composite constituent content, fiber architecture, temperature, matrix crack formation, and oxidation will be explained, along with progress in modeling such properties.

Smith, Craig↗
NASA NTRS2015

A Vehicle Management End-to-End Testing and Analysis Platform for Validation of Mission and Fault Management Algorithms to Reduce Risk for NASA's Space Launch System

The engineering development of the new Space Launch System (SLS) launch vehicle requires cross discipline teams with extensive knowledge of launch vehicle subsystems, information theory, and autonomous algorithms dealing with all operations from pre-launch through on orbit operations. The characteristics of these spacecraft systems must be matched with the autonomous algorithm monitoring and mitigation capabilities for accurate control and response to abnormal conditions throughout all vehicle mission flight phases, including precipitating safing actions and crew aborts. This presents a large and complex system engineering challenge, which is being addressed in part by focusing on the specific subsystems involved in the handling of off-nominal mission and fault tolerance with response management. Using traditional model based system and software engineering design principles from the Unified Modeling Language (UML) and Systems Modeling Language (SysML), the Mission and Fault Management (M&FM) algorithms for the vehicle are crafted and vetted in specialized Integrated Development Teams (IDTs) composed of multiple development disciplines such as Systems Engineering (SE), Flight Software (FSW), Safety and Mission Assurance (S&MA) and the major subsystems and vehicle elements such as Main Propulsion Systems (MPS), boosters, avionics, Guidance, Navigation, and Control (GNC), Thrust Vector Control (TVC), and liquid engines. These model based algorithms and their development lifecycle from inception through Flight Software certification are an important focus of this development effort to further insure reliable detection and response to off-nominal vehicle states during all phases of vehicle operation from pre-launch through end of flight. NASA formed a dedicated M&FM team for addressing fault management early in the development lifecycle for the SLS initiative. As part of the development of the M&FM capabilities, this team has developed a dedicated testbed that integrates specific M&FM algorithms, specialized nominal and off-nominal test cases, and vendor-supplied physics-based launch vehicle subsystem models. Additionally, the team has developed processes for implementing and validating these algorithms for concept validation and risk reduction for the SLS program. The flexibility of the Vehicle Management End-to-end Testbed (VMET) enables thorough testing of the M&FM algorithms by providing configurable suites of both nominal and off-nominal test cases to validate the developed algorithms utilizing actual subsystem models such as MPS. The intent of VMET is to validate the M&FM algorithms and substantiate them with performance baselines for each of the target vehicle subsystems in an independent platform exterior to the flight software development infrastructure and its related testing entities. In any software development process there is inherent risk in the interpretation and implementation of concepts into software through requirements and test cases into flight software compounded with potential human errors throughout the development lifecycle. Risk reduction is addressed by the M&FM analysis group working with other organizations such as S&MA, Structures and Environments, GNC, Orion, the Crew Office, Flight Operations, and Ground Operations by assessing performance of the M&FM algorithms in terms of their ability to reduce Loss of Mission and Loss of Crew probabilities. In addition, through state machine and diagnostic modeling, analysis efforts investigate a broader suite of failure effects and associated detection and responses that can be tested in VMET to ensure that failures can be detected, and confirm that responses do not create additional risks or cause undesired states through interactive dynamic effects with other algorithms and systems. VMET further contributes to risk reduction by prototyping and exercising the M&FM algorithms early in their implementation and without any inherent hindrances such as meeting FSW processor scheduling constraints due to their target platform - ARINC 653 partitioned OS, resource limitations, and other factors related to integration with other subsystems not directly involved with M&FM such as telemetry packing and processing. The baseline plan for use of VMET encompasses testing the original M&FM algorithms coded in the same C++ language and state machine architectural concepts as that used by Flight Software. This enables the development of performance standards and test cases to characterize the M&FM algorithms and sets a benchmark from which to measure the effectiveness of M&FM algorithms performance in the FSW development and test processes.

Trevino, Luis↗
NASA NTRS2016

Safety and Certification Considerations for Expanding the Use of UAS in Precision Agriculture

The agricultural community is actively engaged in adopting new technologies such as unmanned aircraft systems (UAS) to help assess the condition of crops and develop appropriate treatment plans. In the United States, agricultural use of UAS has largely been limited to small UAS, generally weighing less than 55 lb and operating within the line of sight of a remote pilot. A variety of small UAS are being used to monitor and map crops, while only a few are being used to apply agricultural inputs based on the results of remote sensing. Larger UAS with substantial payload capacity could provide an option for site-specific application of agricultural inputs in a timely fashion, without substantive damage to the crops or soil. A recent study by the National Aeronautics and Space Administration (NASA) investigated certification requirements needed to enable the use of larger UAS to support the precision agriculture industry. This paper provides a brief introduction to aircraft certification relevant to agricultural UAS, an overview of and results from the NASA study, and a discussion of how those results might affect the precision agriculture community. Specific topics of interest include business model considerations for unmanned aerial applicators and a comparison with current means of variable rate application. The intent of the paper is to inform the precision agriculture community of evolving technologies that will enable broader use of unmanned vehicles to reduce costs, reduce environmental impacts, and enhance yield, especially for specialty crops that are grown on small to medium size farms.

Hayhurst, Kelly J.↗
DOE OSTI2022

Optical device for in-line and real-time monitoring of microorganisms

A multi-wavelength laser diode based optical sensor system capable of monitoring the dynamics and physiological changes of a microorganism culture in real-time. The microorganism culture from a microorganism production chamber is pumped to a flow chamber. Laser diodes emit light at certain wavelengths through the flow chamber, which is sensed by photodiodes. A laser control circuitry is operatively connected to the laser diodes and a signal conditioning circuitry is operatively connected to the photodiodes. A microprocessor reads and records voltage signals corresponding to the wavelengths. A data acquisition system converts said voltage signals into measurements of biological parameters, which are displayed on a graphical user interface and allow a user to monitor the measurements in real time.

47 OTHER INSTRUMENTATION↗
NASA NTRS2002

Cyclic Failure Mechanisms of Thermal and Environmental Barrier Coating Systems Under Thermal Gradient Test Conditions

Plasma-sprayed ZrO2-8wt%Y2O3 and mullite+BSAS/Si multilayer thermal and environmental barrier coating (TBC-EBC) systems on SiC/SiC ceramic matrix composite (CMC) substrates were thermally cyclic tested under high thermal gradients using a laser high-heat-flux rig in conjunction with furnace exposure in water-vapor environments. Coating sintering and interface damage were assessed by monitoring the real-time thermal conductivity changes during the laser heat-flux tests and by examining the microstructural changes after exposure. Sintering kinetics of the coating systems were also independently characterized using a dilatometer. It was found that the coating failure involved both the time-temperature dependent sintering and the cycle frequency dependent cyclic fatigue processes. The water vapor environments not only facilitated the initial coating conductivity increases due to enhanced sintering and interface reaction, but also promoted later conductivity reductions due to the accelerated coating cracking and delamination. The failure mechanisms of the coating systems are also discussed based on the cyclic test results and are correlated to the sintering and thermal stress behavior under the thermal gradient test conditions.

Zhu, Dongming↗
DOE OSTI2025

Iodine Capture Studies of Copper- and Bismuth-Based Sorbents

The release of radioiodine, one of several radionuclides of concern when recycling used nuclear fuel (UNF), is an important consideration in the fuel cycle. In this study, two sorbent materials, Cu 0 -polyacrylonitrile (PAN) and Bi 0 -PAN, were tested as solid sorbent candidates for iodine capture. Experiments using a thin bed of sorbent material were exposed to vaporized iodine for over 300 hours (~2 weeks) under varied conditions in a dynamic flow environment. The overall performance was monitored in real-time using thermogravimetric analysis, and the materials were subsequently characterized for surface and bulk analysis using scanning electron microscopy – energy-dispersive spectroscopy (SEM-EDS) and powder x-ray diffraction (pXRD), respectively. Iodine (in the form of I 2 ) is expected to be released primarily in the dissolver off-gas (DOG) stream; therefore, this study demonstrates the effects of elemental iodine (I 2 ), water vapor (H 2 O), and nitrogen dioxide (NO 2 ). When exposed to ‘ideal’ conditions (in which I 2 is carried by dry air), Cu 0 -PAN and Bi 0 -PAN behave differently, with TGA analysis indicating that Cu 0 sorption performance is higher than that of Bi 0 , as evidenced by a larger mass change. Under ‘harsh’ conditions—such as a gaseous feed containing I 2 , H 2 O, and NO 2 vapors carried by air,—iodine capture performance for both Cu 0 - and Bi 0 -PAN are affected. SEM-EDS and pXRD analysis of these materials is discussed herein.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS2014

Detecting Change in Urban Areas at Continental Scales with MODIS Data

Urbanization is one of the most important components of global environmental change, yet most of what we know about urban areas is at the local scale. Remote sensing of urban expansion across large areas provides information on the spatial and temporal patterns of growth that are essential for understanding differences in socioeconomic and political factors that spur different forms of development, as well the social, environmental, and climatic impacts that result. However, mapping urban expansion globally is challenging: urban areas have a small footprint compared to other land cover types, their features are small, they are heterogeneous in both material composition and configuration, and the form and rates of new development are often highly variable across locations. Here we demonstrate a methodology for monitoring urban land expansion at continental to global scales using Moderate Resolution Imaging Spectroradiometer (MODIS) data. The new method focuses on resolving the spectral and temporal ambiguities between urban/non-urban land and stable/changed areas by: (1) spatially constraining the study extent to known locations of urban land; (2) integrating multitemporal data from multiple satellite data sources to classify c. 2010 urban extent; and (3) mapping newly built areas (2000-2010) within the 2010 urban land extent using a multi-temporal composite change detection approach based on MODIS 250 m annual maximum enhanced vegetation index (EVI). We test the method in 15 countries in East-Southeast Asia experiencing different rates and manifestations of urban expansion. A two-tiered accuracy assessment shows that the approach characterizes urban change across a variety of socioeconomic/political and ecological/climatic conditions with good accuracy (70-91% overall accuracy by country, 69-89% by biome). The 250 m EVI data not only improve the classification results, but are capable of distinguishing between change and no-change areas in urban areas. Over 80% of the error in the change detection can be related to definitional issues or error propagation, rather than algorithm error. As such, these methods hold great potential for routine monitoring of urban change, as well as for providing a consistent and up-to-date dataset on urban extent and expansion for a rapidly evolving region.

Urban areas↗
DOE OSTI2025

Estimation of cutting tool wear using an elastomeric tactile sensor

Machining performance of cutting tools and part quality are affected by the geometric condition of the cutting edge, which is influenced by thermomechanical loads experienced during the process. Tool condition monitoring (TCM) systems provide insight for timely replacement of cutting tools. However, existing TCM systems are expensive and require specialized equipment or sensors, hindering widespread adoption. A novel TCM system is developed herein using an elastomeric tactile sensor. Sensor images of the cutting edge are used to quantify wear using two distinct algorithms. In the first algorithm, the unworn and worn edges are identified based on Canny edge detect. In the second, the unworn edge is identified using edge detection while the region of wear is identified using a relative intensity method. In both cases, the maximum wear width is calculated based on an experimentally determined pixel to-physical distance scale. The TCM system is first used to estimate flank wear on a solid carbide helical end mill before evaluating its robustness by employing it to estimate insert wear of an indexable helical end mill. Measurements are also performed manually using an optical microscope and a high-resolution focus variation microscope for verification. The novel technique estimates flank wear in the solid carbide tool with a high accuracy of 98%. Larger discrepancies are observed for the inserts, however, with overlapping uncertainties. In conclusion, the technique shows promise in adaptability, automation, and closed loop control of machine tools.

Machining↗
DOE OSTI2022

Using Ensemble Data Assimilation to Estimate Transient Hydrologic Exchange Flow Under Highly Dynamic Flow Conditions

Abstract Quantifying dynamic hydrologic exchange flows (HEFs) within river corridors that experience high‐frequency flow variations caused by dam regulations is important for understanding the biogeochemical processes at the river water and groundwater interfaces. Heat has been widely used as a tracer to infer steady‐state flow velocities through analytical solutions of heat transport defined by the diurnal temperature signals. Under sub‐daily dynamic flow conditions, however, such analytical solutions are not applicable due to the violation of their fundamental assumptions. In this study, we developed a data assimilation‐based approach to estimate the sub‐daily flux under highly dynamic flow conditions using multi‐depth temperature observations at a 5‐min resolution. If the hydraulic gradient is measured, Darcy's law was used to calculate the flux with permeability estimated from temperature responses below the riverbed. Otherwise, flux was estimated directly by assimilating multi‐depth temperature data at 1‐ or 2‐hr time intervals assuming one‐dimensional flow and heat transport governing equation. By comparing estimated fluxes with model‐generated synthetic truth, we demonstrated that both schemes have robust performance in estimating fluxes under highly dynamic flow conditions. This data assimilation‐based flux estimation method was able to capture the vertical sub‐daily fluxes using multi‐depth high‐resolution temperature data alone, even in the presence of multi‐dimensional flow. This approach has been successfully applied to real field temperature data collected at the Hanford site, which experiences highly dynamic HEFs. Our study shows the promise of adopting distributed 1‐D temperature monitoring to capture spatial and temporal exchange dynamics in river corridors at a watershed scale or beyond.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Radiance-based NIR v as a proxy for GPP of corn and soybean

Substantial uncertainty exists in daily and sub-daily gross primary production (GPP) estimation, which dampens accurate monitoring of the global carbon cycle. Here we find that near-infrared radiance of vegetation (NIR v,Rad ), defined as the product of observed NIR radiance and normalized difference vegetation index (NDVI), can accurately estimate corn and soybean GPP at daily and half-hourly time scales, benchmarked with multi-year tower-based GPP at three sites with different environmental and irrigation conditions. Overall, NIR v,Rad explains 84% and 78% variations of half-hourly GPP for corn and soybean, respectively, outperforming NIR reflectance of vegetation (NIR v,Ref ), enhanced vegetation index (EVI), and far-red solar-induced fluorescence (SIF760). The strong linear relationship between NIR v,Rad and absorbed photosynthetically active radiation by green leaves (APAR green ), and that between APAR green and GPP, explain the good NIR v,Rad -GPP relationship. The NIR v,Rad -GPP relationship is robust and consistent across sites. The scalability and simplicity of NIR v,Rad indicate a great potential to estimate daily or sub-daily GPP from high-resolution and/or long-term satellite remote sensing data.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

The physiological acclimation and growth response of Populus trichocarpa to warming

Plant metabolic acclimation to thermal stress remains underrepresented in current global climate models. Gaps exist in our understanding of how metabolic processes (i.e., photosynthesis, respiration) acclimate over time and how aboveground versus belowground acclimation differs. We measured the thermal acclimation of Populus trichocarpa, comparing aboveground versus belowground physiology over time. Ninety genetically identical ramets were propagated in mesocosms that separated root and microbial components. After establishment at 25°C for 6 weeks, 60 clones were warmed +4 or +8°C and monitored for 10 weeks, measuring photosynthesis (A), leaf respiration (R), soil respiration (R s ), root plus soil respiration (R s+r ), and root respiration (R r ). We observed thermal acclimation in both A and R, with rates initially increasing, then declining as the thermal photosynthetic optimum (T opt ) and the temperature-sensitivity (Q 10 ) of respiration adjusted to warmer conditions. Photosynthetic acclimation was constructive, based on an increase in both T opt and peak A. Belowground, R s+r decreased linearly with warming, while R s rates declined abruptly, then remained constant with additional warming. Plant biomass was greatest at +4°C, with 30% allocated belowground. Rates of mass-based R r were similar among treatments; however, root nitrogen declined at +8°C leading to less mass nitrogen-based R r in that treatment. The Q 10 -temperature relationship of R r was affected by warming, leading to differing values among treatments. Aboveground acclimation exceeded belowground acclimation, and plant nitrogen-use mediated the acclimatory response. Results suggest that moderate climate warming (+4°C) may lead to acclimation and increased plant biomass production but increases in production could be limited with severe warming (+8°C).

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1993

Using manufacturing message specification for monitor and control at Venus

The flexibility and robustness of a monitor and control (M&C) system are a direct result of the underlying interprocessor communications architecture. A new architecture for M&C at the Deep Space Communications Complexes (DSCC's) has been developed based on the Manufacturing Message Specification (MMS) process control standard of the Open System Interconnection (OSI) suite of protocols. This architecture has been tested both in a laboratory environment and under operational conditions at the Deep Space Network (DSN) experimental Venus station (DSS-13). The Venus experience in the application of OSI standards to support M&C has been extremely successful. MMS meets the functional needs of the station and provides a level of flexibility and responsiveness previously unknown in that environment. The architecture is robust enough to meet current operational needs and flexible enough to provide a migration path for new subsystems. This paper will describe the architecture of the Venus M&C system, discuss how MMS was used and the requirements this imposed on other parts of the system, and provide results from systems and operational testing at the Venus site.

Heuser, W. Randy↗
NASA NTRS1993

DSS-13 - Using an OSI process control standard for monitor and control

The flexibility and robustness of a monitor and control (M&C) system are a direct result of the underlying inter-processor communications architecture. A new architecture for M&C at the Deep Space Communications Complexes has been developed based on the manufacturing message specification (MMS) process control standard of the open system interconnection (OSI) suite of protocols. This architecture has been tested both in a laboratory environment and under operational conditions at the Deep Space Network experimental station (DSS-13). The DSS-13 experience in the application of OSI standards to support M&C has been extremely successful. MMS meets the functional needs of the station and provides a level of flexibility and responsiveness previously unknown in that environment. The architecture is robust enough to meet current operational needs and flexible enough to provide a migration path for new subsystems. This paper describes the architecture of the DSS-13 M&C system, discuss how MMS was used and the requirements this imposed on other parts of the system, and provides results from systems and operational testing at DSS-13.

Heuser, W. R.↗
NASA NTRS2015

A Vehicle Management End-to-End Testing and Analysis Platform for Validation of Mission and Fault Management Algorithms to Reduce Risk for NASAs Space Launch System

The engineering development of the National Aeronautics and Space Administration's (NASA) new Space Launch System (SLS) requires cross discipline teams with extensive knowledge of launch vehicle subsystems, information theory, and autonomous algorithms dealing with all operations from pre-launch through on orbit operations. The nominal and off-nominal characteristics of SLS's elements and subsystems must be understood and matched with the autonomous algorithm monitoring and mitigation capabilities for accurate control and response to abnormal conditions throughout all vehicle mission flight phases, including precipitating safing actions and crew aborts. This presents a large and complex systems engineering challenge, which is being addressed in part by focusing on the specific subsystems involved in the handling of off-nominal mission and fault tolerance with response management. Using traditional model-based system and software engineering design principles from the Unified Modeling Language (UML) and Systems Modeling Language (SysML), the Mission and Fault Management (M&FM) algorithms for the vehicle are crafted and vetted in Integrated Development Teams (IDTs) composed of multiple development disciplines such as Systems Engineering (SE), Flight Software (FSW), Safety and Mission Assurance (S&MA) and the major subsystems and vehicle elements such as Main Propulsion Systems (MPS), boosters, avionics, Guidance, Navigation, and Control (GNC), Thrust Vector Control (TVC), and liquid engines. These model-based algorithms and their development lifecycle from inception through FSW certification are an important focus of SLS's development effort to further ensure reliable detection and response to off-nominal vehicle states during all phases of vehicle operation from pre-launch through end of flight. To test and validate these M&FM algorithms a dedicated test-bed was developed for full Vehicle Management End-to-End Testing (VMET). For addressing fault management (FM) early in the development lifecycle for the SLS program, NASA formed the M&FM team as part of the Integrated Systems Health Management and Automation Branch under the Spacecraft Vehicle Systems Department at the Marshall Space Flight Center (MSFC). To support the development of the FM algorithms, the VMET developed by the M&FM team provides the ability to integrate the algorithms, perform test cases, and integrate vendor-supplied physics-based launch vehicle (LV) subsystem models. Additionally, the team has developed processes for implementing and validating the M&FM algorithms for concept validation and risk reduction. The flexibility of the VMET capabilities enables thorough testing of the M&FM algorithms by providing configurable suites of both nominal and off-nominal test cases to validate the developed algorithms utilizing actual subsystem models such as MPS, GNC, and others. One of the principal functions of VMET is to validate the M&FM algorithms and substantiate them with performance baselines for each of the target vehicle subsystems in an independent platform exterior to the flight software test and validation processes. In any software development process there is inherent risk in the interpretation and implementation of concepts from requirements and test cases into flight software compounded with potential human errors throughout the development and regression testing lifecycle. Risk reduction is addressed by the M&FM group but in particular by the Analysis Team working with other organizations such as S&MA, Structures and Environments, GNC, Orion, Crew Office, Flight Operations, and Ground Operations by assessing performance of the M&FM algorithms in terms of their ability to reduce Loss of Mission (LOM) and Loss of Crew (LOC) probabilities. In addition, through state machine and diagnostic modeling, analysis efforts investigate a broader suite of failure effects and associated detection and responses to be tested in VMET to ensure reliable failure detection, and confirm responses do not create additional risks or cause undesired states through interactive dynamic effects with other algorithms and systems. VMET further contributes to risk reduction by prototyping and exercising the M&FM algorithms early in their implementation and without any inherent hindrances such as meeting FSW processor scheduling constraints due to their target platform - the ARINC 6535-partitioned Operating System, resource limitations, and other factors related to integration with other subsystems not directly involved with M&FM such as telemetry packing and processing. The baseline plan for use of VMET encompasses testing the original M&FM algorithms coded in the same C++ language and state machine architectural concepts as that used by FSW. This enables the development of performance standards and test cases to characterize the M&FM algorithms and sets a benchmark from which to measure their effectiveness and performance in the exterior FSW development and test processes. This paper is outlined in a systematic fashion analogous to a lifecycle process flow for engineering development of algorithms into software and testing. Section I describes the NASA SLS M&FM context, presenting the current infrastructure, leading principles, methods, and participants. Section II defines the testing philosophy of the M&FM algorithms as related to VMET followed by section III, which presents the modeling methods of the algorithms to be tested and validated in VMET. Its details are then further presented in section IV followed by Section V presenting integration, test status, and state analysis. Finally, section VI addresses the summary and forward directions followed by the appendices presenting relevant information on terminology and documentation.

Trevino, Luis↗