Results for “Model-based Testing” — Page 12

NASA NTRS2012

Orion Flight Test 1 Architecture: Observed Benefits of a Model Based Engineering Approach

This paper details how a NASA-led team is using a model-based systems engineering approach to capture, analyze and communicate the end-to-end information system architecture supporting the first unmanned orbital flight of the Orion Multi-Purpose Crew Exploration Vehicle. Along with a brief overview of the approach and its products, the paper focuses on the observed program-level benefits, challenges, and lessons learned; all of which may be applied to improve system engineering tasks for characteristically similarly challenges

Multi-Purpose Crew Exploration Vehicle.↗

NASA NTRS2012

NASA Tech Briefs, December 2012

The topics include: Pattern Generator for Bench Test of Digital Boards; 670-GHz Down- and Up-Converting HEMT-Based Mixers; Lidar Electro-Optic Beam Switch with a Liquid Crystal Variable Retarder; Feedback Augmented Sub-Ranging (FASR) Quantizer; Real-Time Distributed Embedded Oscillator Operating Frequency Monitoring; Software Modules for the Proximity-1 Space Link Interleaved Time Synchronization (PITS) Protocol; Description and User Instructions for the Quaternion to Orbit v3 Software; AdapChem; Mars Relay Lander and Orbiter Overflight Profile Estimation; Extended Testability Analysis Tool; Interactive 3D Mars Visualization; Rapid Diagnostics of Onboard Sequences; MER Telemetry Processor; pyam: Python Implementation of YaM; Process for Patterning Indium for Bump Bonding; Archway for Radiation and Micrometeorite Occurrence Resistance; 4D Light Field Imaging System Using Programmable Aperture; Device and Container for Reheating and Sterilization; Radio Frequency Plasma Discharge Lamps for Use as Stable Calibration Light Sources; Membrane Shell Reflector Segment Antenna; High-Speed Transport of Fluid Drops and Solid Particles via Surface Acoustic Waves; Compact Autonomous Hemispheric Vision System; A Distributive, Non-Destructive, Real-Time Approach to Snowpack Monitoring; Wideband Single-Crystal Transducer for Bone Characterization; Numerical Simulation of Rocket Exhaust Interaction With Lunar Soil; Motion Imagery and Robotics Application (MIRA): Standards-Based Robotics; Particle Filtering for Model-Based Anomaly Detection in Sensor Networks; Ka-band Digitally Beamformed Airborne Radar Using SweepSAR Technique; Composite With In Situ Plenums; Multi-Beam Approach for Accelerating Alignment and Calibration of HyspIRI-Like Imaging Spectrometers; JWST Lifting System; Next-Generation Tumbleweed Rover; Pneumatic System for Concentration of Micrometer-Size Lunar Soil.

Source record↗

NASA NTRS2013

Validation and Verification of LADEE Models and Software

The Lunar Atmosphere Dust Environment Explorer (LADEE) mission will orbit the moon in order to measure the density, composition and time variability of the lunar dust environment. The ground-side and onboard flight software for the mission is being developed using a Model-Based Software methodology. In this technique, models of the spacecraft and flight software are developed in a graphical dynamics modeling package. Flight Software requirements are prototyped and refined using the simulated models. After the model is shown to work as desired in this simulation framework, C-code software is automatically generated from the models. The generated software is then tested in real time Processor-in-the-Loop and Hardware-in-the-Loop test beds. Travelling Road Show test beds were used for early integration tests with payloads and other subsystems. Traditional techniques for verifying computational sciences models are used to characterize the spacecraft simulation. A lightweight set of formal methods analysis, static analysis, formal inspection and code coverage analyses are utilized to further reduce defects in the onboard flight software artifacts. These techniques are applied early and often in the development process, iteratively increasing the capabilities of the software and the fidelity of the vehicle models and test beds.

Gundy-Burlet, Karen↗

NASA NTRS2014

Application of Model-based Prognostics to a Pneumatic Valves Testbed

Pneumatic-actuated valves play an important role in many applications, including cryogenic propellant loading for space operations. Model-based prognostics emphasizes the importance of a model that describes the nominal and faulty behavior of a system, and how faulty behavior progresses in time, causing the end of useful life of the system. We describe the construction of a testbed consisting of a pneumatic valve that allows the injection of faulty behavior and controllable fault progression. The valve opens discretely, and is controlled through a solenoid valve. Controllable leaks of pneumatic gas in the testbed are introduced through proportional valves, allowing the testing and validation of prognostics algorithms for pneumatic valves. A new valve prognostics approach is developed that estimates fault progression and predicts remaining life based only on valve timing measurements. Simulation experiments demonstrate and validate the approach.

prediction↗

NASA NTRS2013

A Cryogenic Fluid System Simulation in Support of Integrated Systems Health Management

Simulations serve as important tools throughout the design and operation of engineering systems. In the context of sys-tems health management, simulations serve many uses. For one, the underlying physical models can be used by model-based health management tools to develop diagnostic and prognostic models. These simulations should incorporate both nominal and faulty behavior with the ability to inject various faults into the system. Such simulations can there-fore be used for operator training, for both nominal and faulty situations, as well as for developing and prototyping health management algorithms. In this paper, we describe a methodology for building such simulations. We discuss the design decisions and tools used to build a simulation of a cryogenic fluid test bed, and how it serves as a core technology for systems health management development and maturation.

cryogenics↗

NASA NTRS2011

A Model-based Prognostics Methodology for Electrolytic Capacitors Based on Electrical Overstress Accelerated Aging

A remaining useful life prediction methodology for electrolytic capacitors is presented. This methodology is based on the Kalman filter framework and an empirical degradation model. Electrolytic capacitors are used in several applications ranging from power supplies on critical avionics equipment to power drivers for electro-mechanical actuators. These devices are known for their comparatively low reliability and given their criticality in electronics subsystems they are a good candidate for component level prognostics and health management. Prognostics provides a way to assess remaining useful life of a capacitor based on its current state of health and its anticipated future usage and operational conditions. We present here also, experimental results of an accelerated aging test under electrical stresses. The data obtained in this test form the basis for a remaining life prediction algorithm where a model of the degradation process is suggested. This preliminary remaining life prediction algorithm serves as a demonstration of how prognostics methodologies could be used for electrolytic capacitors. In addition, the use degradation progression data from accelerated aging, provides an avenue for validation of applications of the Kalman filter based prognostics methods typically used for remaining useful life predictions in other applications.

Electrolytic capacitors↗

NASA NTRS2012

Prognostics Approach for Power MOSFET Under Thermal-Stress

The prognostic technique for a power MOSFET presented in this paper is based on accelerated aging of MOSFET IRF520Npbf in a TO-220 package. The methodology utilizes thermal and power cycling to accelerate the life of the devices. The major failure mechanism for the stress conditions is dieattachment degradation, typical for discrete devices with leadfree solder die attachment. It has been determined that dieattach degradation results in an increase in ON-state resistance due to its dependence on junction temperature. Increasing resistance, thus, can be used as a precursor of failure for the die-attach failure mechanism under thermal stress. A feature based on normalized ON-resistance is computed from in-situ measurements of the electro-thermal response. An Extended Kalman filter is used as a model-based prognostics techniques based on the Bayesian tracking framework. The proposed prognostics technique reports on preliminary work that serves as a case study on the prediction of remaining life of power MOSFETs and builds upon the work presented in [1]. The algorithm considered in this study had been used as prognostics algorithm in different applications and is regarded as suitable candidate for component level prognostics. This work attempts to further the validation of such algorithm by presenting it with real degradation data including measurements from real sensors, which include all the complications (noise, bias, etc.) that are regularly not captured on simulated degradation data. The algorithm is developed and tested on the accelerated aging test timescale. In real world operation, the timescale of the degradation process and therefore the RUL predictions will be considerable larger. It is hypothesized that even though the timescale will be larger, it remains constant through the degradation process and the algorithm and model would still apply under the slower degradation process. By using accelerated aging data with actual device measurements and real sensors (no simulated behavior), we are attempting to assess how such algorithm behaves under realistic conditions.

Power MOSFET PHM↗

NASA NTRS2013

Intensification of North American Megadroughts through Surface and Dust Aerosol Forcing

Tree-ring-based reconstructions of the Palmer drought severity index (PDSI) indicate that, during the Medieval Climate Anomaly (MCA), the central plains of North America experienced recurrent periods of drought spanning decades or longer. These megadroughts had exceptional persistence compared to more recent events, but the causes remain uncertain. The authors conducted a suite of general circulation model experiments to test the impact of sea surface temperature (SST) and land surface forcing on the MCA megadroughts over the central plains. The land surface forcing is represented as a set of dune mobilization boundary conditions, derived from available geomorphological evidence and modeled as increased bare soil area and a dust aerosol source (32deg-44degN, 105deg-95degW). In the experiments, cold tropical Pacific SST forcing suppresses precipitation over the central plains but cannot reproduce the overall drying or persistence seen in the PDSI reconstruction. Droughts in the scenario with dust aerosols, however, are amplified and have significantly longer persistence than in other model experiments, more closely matching the reconstructed PDSI. This additional drying occurs because the dust increases the shortwave planetary albedo, reducing energy inputs to the surface and boundary layer. The energy deficit increases atmospheric stability, inhibiting convection and reducing cloud cover and precipitation over the central plains. Results from this study provide the first model-based evidence that dust aerosol forcing and land surface changes could have contributed to the intensity and persistence of the central plains megadroughts, although uncertainties remain in the formulation of the boundary conditions and the future importance of these feedbacks.

Earth surface↗

NASA NTRS2014

Additive Manufacturing Design Considerations for Liquid Engine Components

The Marshall Space Flight Center's Propulsion Systems Department has gained significant experience in the last year designing, building, and testing liquid engine components using additive manufacturing. The department has developed valve, duct, turbo-machinery, and combustion device components using this technology. Many valuable lessons were learned during this process. These lessons will be the focus of this presentation. We will present criteria for selecting part candidates for additive manufacturing. Some part characteristics are 'tailor made' for this process. Selecting the right parts for the process is the first step to maximizing productivity gains. We will also present specific lessons we learned about feature geometry that can and cannot be produced using additive manufacturing machines. Most liquid engine components were made using a two-step process. The base part was made using additive manufacturing and then traditional machining processes were used to produce the final part. The presentation will describe design accommodations needed to make the base part and lessons we learned about which features could be built directly and which require the final machine process. Tolerance capabilities, surface finish, and material thickness allowances will also be covered. Additive Manufacturing can produce internal passages that cannot be made using traditional approaches. It can also eliminate a significant amount of manpower by reducing part count and leveraging model-based design and analysis techniques. Information will be shared about performance enhancements and design efficiencies we experienced for certain categories of engine parts.

Whitten, Dave↗

NASA NTRS2015

Real-Time Model-Based Leak-Through Detection within Cryogenic Flow Systems

The timely detection of leaks within cryogenic fuel replenishment systems is of significant importance to operators on account of the safety and economic impacts associated with material loss and operational inefficiencies. Associated loss in control of pressure also effects the stability and ability to control the phase of cryogenic fluids during replenishment operations. Current research dedicated to providing Prognostics and Health Management (PHM) coverage of such cryogenic replenishment systems has focused on the detection of leaks to atmosphere involving relatively simple model-based diagnostic approaches that, while effective, are unable to isolate the fault to specific piping system components. The authors have extended this research to focus on the detection of leaks through closed valves that are intended to isolate sections of the piping system from the flow and pressurization of cryogenic fluids. The described approach employs model-based detection of leak-through conditions based on correlations of pressure changes across isolation valves and attempts to isolate the faults to specific valves. Implementation of this capability is enabled by knowledge and information embedded in the domain model of the system. The approach has been used effectively to detect such leak-through faults during cryogenic operational testing at the Cryogenic Testbed at NASA's Kennedy Space Center.

Walker, M.↗

NASA NTRS2015

Hazard Assessment from Storm Tides and Rainfall on a Tidal River Estuary

Here, we report on methods and results for a model-based flood hazard assessment we have conducted for the Hudson River from New York City to Troy/Albany at the head of tide. Our recent work showed that neglecting freshwater flows leads to underestimation of peak water levels at up-river sites and neglecting stratification (typical with two-dimensional modeling) leads to underestimation all along the Hudson. As a result, we use a three-dimensional hydrodynamic model and merge streamflows and storm tides from tropical and extratropical cyclones (TCs, ETCs), as well as wet extratropical cyclone (WETC) floods (e.g. freshets, rain-on-snow events). We validate the modeled flood levels and quantify error with comparisons to 76 historical events. A Bayesian statistical method is developed for tropical cyclone streamflows using historical data and consisting in the evaluation of (1) the peak discharge and its pdf as a function of TC characteristics, and (2) the temporal trend of the hydrograph as a function of temporal evolution of the cyclone track, its intensity and the response characteristics of the specific basin. A k-nearest-neighbors method is employed to determine the hydrograph shape. Out of sample validation tests demonstrate the effectiveness of the method. Thus, the combined effects of storm surge and runoff produced by tropical cyclones hitting the New York area can be included in flood hazard assessment. Results for the upper Hudson (Albany) suggest a dominance of WETCs, for the lower Hudson (at New York Harbor) a case where ETCs are dominant for shorter return periods and TCs are more important for longer return periods (over 150 years), and for the middle-Hudson (Poughkeepsie) a mix of all three flood events types is important. However, a possible low-bias for TC flood levels is inferred from a lower importance in the assessment results, versus historical event top-20 lists, and this will be further evaluated as these preliminary methods and results are finalized. Future funded work will quantify the influences of sea level rise and flood adaptation plans (e.g. surge barriers). It would also be valuable to examine how streamflows from tropical cyclones and wet cool-season storms will change, as this factor will dominate at upriver locations.

Hazard assessment↗

NASA NTRS2016

Modeling in the State Flow Environment to Support Launch Vehicle Verification Testing for Mission and Fault Management Algorithms in the NASA Space Launch System

Analysis methods and testing processes are essential activities in the engineering development and verification of the National Aeronautics and Space Administration's (NASA) new Space Launch System (SLS). Central to mission success is reliable verification of the Mission and Fault Management (M&FM) algorithms for the SLS launch vehicle (LV) flight software. This is particularly difficult because M&FM algorithms integrate and operate LV subsystems, which consist of diverse forms of hardware and software themselves, with equally diverse integration from the engineering disciplines of LV subsystems. M&FM operation of SLS requires a changing mix of LV automation. During pre-launch the LV is primarily operated by the Kennedy Space Center (KSC) Ground Systems Development and Operations (GSDO) organization with some LV automation of time-critical functions, and much more autonomous LV operations during ascent that have crucial interactions with the Orion crew capsule, its astronauts, and with mission controllers at the Johnson Space Center. M&FM algorithms must perform all nominal mission commanding via the flight computer to control LV states from pre-launch through disposal and also address failure conditions by initiating autonomous or commanded aborts (crew capsule escape from the failing LV), redundancy management of failing subsystems and components, and safing actions to reduce or prevent threats to ground systems and crew. To address the criticality of the verification testing of these algorithms, the NASA M&FM team has utilized the State Flow environment6 (SFE) with its existing Vehicle Management End-to-End Testbed (VMET) platform which also hosts vendor-supplied physics-based LV subsystem models. The human-derived M&FM algorithms are designed and vetted in Integrated Development Teams composed of design and development disciplines such as Systems Engineering, Flight Software (FSW), Safety and Mission Assurance (S&MA) and major subsystems and vehicle elements such as Main Propulsion Systems (MPS), boosters, avionics, Guidance, Navigation, and Control (GN&C), Thrust Vector Control (TVC), liquid engines, and the astronaut crew office. Since the algorithms are realized using model-based engineering (MBE) methods from a hybrid of the Unified Modeling Language (UML) and Systems Modeling Language (SysML), SFE methods are a natural fit to provide an in depth analysis of the interactive behavior of these algorithms with the SLS LV subsystem models. For this, the M&FM algorithms and the SLS LV subsystem models are modeled using constructs provided by Matlab which also enables modeling of the accompanying interfaces providing greater flexibility for integrated testing and analysis, which helps forecast expected behavior in forward VMET integrated testing activities. In VMET, the M&FM algorithms are prototyped and implemented using the same C++ programming language and similar state machine architectural concepts used by the FSW group. Due to the interactive complexity of the algorithms, VMET testing thus far has verified all the individual M&FM subsystem algorithms with select subsystem vendor models but is steadily progressing to assessing the interactive behavior of these algorithms with LV subsystems, as represented by subsystem models. The novel SFE applications has proven to be useful for quick look analysis into early integrated system behavior and assessment of the M&FM algorithms with the modeled LV subsystems. This early MBE analysis generates vital insight into the integrated system behaviors, algorithm sensitivities, design issues, and has aided in the debugging of the M&FM algorithms well before full testing can begin in more expensive, higher fidelity but more arduous environments such as VMET, FSW testing, and the Systems Integration Lab7 (SIL). SFE has exhibited both expected and unexpected behaviors in nominal and off nominal test cases prior to full VMET testing. In many findings, these behavioral characteristics were used to correct the M&FM algorithms, enable better test coverage, and develop more effective test cases for each of the LV subsystems. This has improved the fidelity of testing and planning for the next generation of M&FM algorithms as the SLS program evolves from non-crewed to crewed flight, impacting subsystem configurations and the M&FM algorithms that control them. SFE analysis has improved robustness and reliability of the M&FM algorithms by revealing implementation errors and documentation inconsistencies. It is also improving planning efficiency for future VMET testing of the M&FM algorithms hosted in the LV flight computers, further reducing risk for the SLS launch infrastructure, the SLS LV, and most importantly the crew.

Trevino, Luis↗

NASA NTRS2017

Mars 2020 Model Based Systems Engineering Pilot

The pilot study is led by the Integration Engineering group in NASA's Launch Services Program (LSP). The Integration Engineering (IE) group is responsible for managing the interfaces between the spacecraft and launch vehicle. This pilot investigates the utility of Model-Based Systems Engineering (MBSE) with respect to managing and verifying interface requirements. The main objectives of the pilot are to model several key aspects of the Mars 2020 integrated operations and interface requirements based on the design and verification artifacts from Mars Science Laboratory (MSL) and to demonstrate how MBSE could be used by LSP to gain further insight on the interface between the spacecraft and launch vehicle as well as to enhance how LSP manages the launch service. The method used to accomplish this pilot started through familiarization of SysML, MagicDraw, and the Mars 2020 and MSL systems through books, tutorials, and NASA documentation. MSL was chosen as the focus of the model since its processes and verifications translate easily to the Mars 2020 mission. The study was further focused by modeling specialized systems and processes within MSL in order to demonstrate the utility of MBSE for the rest of the mission. The systems chosen were the In-Flight Disconnect (IFD) system and the Mass Properties process. The IFD was chosen as a system of focus since it is an interface between the spacecraft and launch vehicle which can demonstrate the usefulness of MBSE from a system perspective. The Mass Properties process was chosen as a process of focus since the verifications for mass properties occur throughout the lifecycle and can demonstrate the usefulness of MBSE from a multi-discipline perspective. Several iterations of both perspectives have been modeled and evaluated. While the pilot study will continue for another 2 weeks, pros and cons of using MBSE for LSP IE have been identified. A pro of using MBSE includes an integrated view of the disciplines, requirements, and verifications leading up to launch. The model allows IE to understand the relationships between disciplines throughout test activities and verifications. Additionally, the relationships between disciplines and integration tasks are generally consistent. The model allows for the generic relationships and tasks to be captured and used throughout multiple mission models should LSP further pursue MBSE. A con of MBSE is the amount of time it takes upfront to understand MBSE and create a useful model. The upfront time it takes to create a useful model is heavily discussed in MBSE literature and is a consistent con throughout the known applications of MBSE. The need to understand SysML and the software chosen also poses the possibility of a "bottleneck" or one person being the sole MBSE user for the working group. The utility of MBSE will continue to be evaluated through the remainder of the study. In conclusion, the original objectives of the pilot study were to use artifacts from MSL to model key aspects of Mars 2020 and demonstrate how MBSE could be used by LSP to gain insight into the spacecraft and launch vehicle interfaces. Progress has been made in modeling and identifying the utility of MBSE to LSP IE and will continue to be made until the pilot study's conclusion in mid-August. The results of this study will produce initial models, modeling instructions and examples, and a summary of MBSE's utility for future use by LSP.

Dukes, Alexandra Marie↗

NASA NTRS2014

LADEE Multi-Domain Simulation

The Lunar Atmosphere Dust Environment Explorer (LADEE) was a small explorer class spacecraft that was launched on Sept 7, 2013 and that was de-orbited and successfully impacted the Moons surface on April 17, 2014 after completing all of the mission objectives. The low-cost rapidly prototyped hardware design used for the spacecraft was extend to the development of the software base. To achieve this goal, a Model Based Design approach was utilized to develop the onboard flight software, and out of this development a model based multipurpose simulator was created of the LADEE spacecraft and its mission environment. This simulator extended the traditional function of propagating the vehicle's kinematic and rotational states and included the electrical and thermal states propagation. Traditionally, these domains are handled by domain specific high fidelity simulations that use the states histories from other domains as input. By reducing the fidelity and abstracting the relevant features being monitored and controlled by the flight software, it was possible to model the coupling across these domains resulting in more accurate overall system behavior. A faster than real-time workstation (WSIM) version of the LADEE simulator was used to develop and test the software control algorithms in the Simulink environment. To maximize the performance of the simulation, modeling knobs were introduced to reduce the resolution of the some of the domains models when the effects of that domain were not significant for the scope of that simulation. The automatic code generation feature in Simulink was used to port the simulation to several real-time environments to support Processor-in-the-Loop (PIL) and Hardware-in-the-Loop (HIL) testing, verification and validation. The real-time environment required that the design of each of the domain models be deterministic as possible in the time required to perform all of the calculations to update its states. The simulation interface was designed to be compatible with the command interface employed by the LADEE mission operation team. The WSIM, PIL, and HIL simulators thus used a common interface and thus were used for flight software testing, for mission operations personnel training (nominal and off-nominal operations) prior to the mission and to perform command sequence verification during the mission. This presentation will look at the modeling strategies used to create a common interface to the simulator and to model and couple multiple domains within the simulation, the results of those strategies, and the lessons learned.

Multi-Domain↗

NASA NTRS2016

A Structured, Model-Based Systems Engineering Methodology for Operations System Design

Two widely accepted techniques for lowering the cost and risk of developing systems are (1) the use of a defined systems engineering (SE) process or methodology and (2) the reuse of existing (previously built) system components. The first technique is represented, for example, in materials published by NASA (e.g., NASA Systems Engineering Handbook) or by professional societies such as INCOSE (International Council on Systems Engineering). Well-formed SE techniques provide value by establishing the proper scope of the system (e.g., requirements), and by identifying and resolving problems relatively early in project lifecycles, when fixes are less expensive. The second technique (reuse) is applied most commonly to hardware and software; it seeks to avoid replicating design and implementation costs while also reducing risk by placing proven capabilities into operational use. In this paper, we outline a methodology combining these two techniques and extending reuse beyond hardware and software to foundational aspects of a Mission Operation System’s (MOS) design. We describe the system design artifacts that result (e.g., requirements, design documentation), as well as the reusable patterns and elements of the design, and their interrelationships. This approach is enabled by model-based systems engineering (MBSE) techniques and tools and is currently available in SysML form as a plug-in to MagicDraw. Additionally, usage of a rigorous MBSE approach allows for training materials and tutorials to be packaged within the overall model itself. The results of such an approach include decreased cost and risk during the design phase, improved ability of the MOS development team to investigate trade spaces and identify impacts to important flight-ground trade studies. Such results extend into decreased costs and risk in later phases due to improved design, decreased need for late fixes or development of "glue-ware" or scripts to fill unanticipated gaps in functionality, and improved ability to identify and plan testing and other validation activities. Finally, lower operational costs can be expected, both due to improved quality of the MOS, increased ease of maintaining updated knowledge of system configuration, and the fact that training and procedural materials are also updated at the same time as accepted system changes.

Bindschadler, Duane L.↗

NASA NTRS2016

A Model Based Systems Engineering Approach Towards Developing a Rapid Analysis and Trades Environment

In this work, an integrated and end-to-end modeling environment was developed to assess the system-level impacts of evolving requirements and design parameters. Researchers at the Georgia Institute of Technology's Aerospace Systems Design Laboratory (ASDL) collaborated with JPL engineers to develop, implement, and test a modeling environment to assess design changes to a notional Europa Mission called the Jupiter Europa Buzzer (JEB). This environment was developed using a Model-Based Systems Engineering (MBSE) approach and consists of three major components: the Systems Model, the Mission Simulator, and the Web Based Interactive Dashboard. In summary, utilizing this environment in a representative notional end-to-end scenario, performance margins were calculated in hours while maintaining consistent analytical, hardware, and operational assumptions.

Model Based System Engineering↗

NASA NTRSDate not supplied

ARCTRON: A Rapid Experimental Proving Ground for TPS Experiments and Arcjet Technology Development

Innovation in high-enthalpy facilities is fundamentally limited by the cost and risk of experimentation. New concepts for plasma control, diagnostics, facility components, and plasma-material interaction often require repeated iterations that are impractical to perform in production arcjets. As a result, promising ideas may remain unexplored or reach operational facilities only after significant development effort. ARCTRON is being developed as a rapid experimental proving ground where new ideas in plasma science, arcjet engineering, diagnostics, and material response can be conceived, tested, and quantitatively evaluated before transition to large-scale facilities. The platform combines radio-frequency (RF) and DC arc plasma generation, externally applied magnetic fields, configurable gas composition, reduced-pressure operation, laser heating, electrical biasing, and modular diagnostic access. These capabilities permit the plasma source, applied forcing, test article, and measurement configuration to be modified independently, allowing individual physical mechanisms to be isolated more readily than in a traditional test environment. One class of investigations addresses fundamental plasma-surface interaction physics. Conventional material tests often expose a specimen simultaneously to convective heating, reactive species, pressure, shear, radiation, and surface-current effects. The resulting material response may be measured accurately, while the contribution of each mechanism remains difficult to identify. ARCTRON is designed to vary these effects selectively. Plasma chemistry can be changed independently through configurable gas mixtures; magnetic fields and electrical biasing can modify charged-particle transport; laser heating can provide a non-plasma thermal input; and pressure, flow, and discharge mode can be varied over a broad operating space. This enables controlled tests of hypotheses involving surface catalycity, reactive-species transport, plasma-assisted oxidation, electromagnetic effects, shear, and the relative contributions of thermal and chemical loading. A second class of investigations enabled by this approach concerns the engineering of high-enthalpy facilities themselves. Arc-heated facilities are limited by electrode erosion, unstable arc attachment, localized heating, and damage to nozzles and other plasma-facing components. ARCTRON provides a lower-cost environment for testing concepts intended to mitigate these limitations. Candidate investigations include the use of applied magnetic fields to alter current paths and reduce plasma interaction with nozzle walls, ExB forcing to introduce controlled plasma rotation, magnetic or geometric approaches for distributing arc attachment, and alternative electrode or discharge configurations intended to reduce erosion and improve stability. Because the platform is reconfigurable, these concepts can be evaluated through repeated design--build--test cycles before they are considered for implementation in operational facilities. The platform also supports the development and validation of diagnostics that may be difficult to introduce initially into a large arcjet. Current and planned measurements include spatially resolved optical emission spectroscopy, electrostatic probes, fast imaging, pyrometry, calorimetry, laser-induced fluorescence, and absorption spectroscopy. These diagnostics are intended not merely to document a nominal operating condition, but to constrain the local plasma state and its relationship to component or material response. The modular facility geometry allows diagnostic concepts to be tested, calibrated, and compared under repeatable conditions before deployment in more demanding environments. ARCTRON is also supported by an integrated software suite. Automated control and data acquisition allow discharge parameters, gas composition, magnetic fields, diagnostic timing, and test configuration to be recorded as part of each experiment (STARDAC - Software for Testing, Analysis, Research Data, and Control). The Backend for Experiment Analysis, Storage, and Traceability (BEAST) is a database that provides the infrastructure needed to associate heterogeneous measurements with facility configuration, specimen identity, calibration state, geometry, and analysis provenance. This backend is particularly important for exploratory campaigns, in which many related configurations may be tested, and the value of an individual experiment depends on its connection to earlier and subsequent iterations. Complementary analysis capabilities, including computer-vision-based transient response measurements (arcjetCV), three-dimensional surface reconstruction (STARSCAN), and model-based Bayesian inference (SHIELD), and tomography data analysis (TOMATO, PuMA) can be incorporated when required by a specific hypothesis without becoming the focus of every campaign. The central objective of ARCTRON is therefore not to maximize heat flux or reproduce a complete flight environment. Its purpose is to reduce the cost and time required to ask consequential questions about plasma behavior, plasma-facing materials, diagnostics, and arcjet technology. By providing a controlled environment for rapid reconfiguration, mechanism isolation, quantitative measurement, and iterative engineering, ARCTRON can help mature concepts that would otherwise remain too speculative or too risky for evaluation in production facilities. The resulting knowledge can then guide the design of material models, focus test objectives in larger arcjets, reduce facility-development risk, and improve the physical basis of high-enthalpy ground testing. This work will present the ARCTRON architecture, operating modes, diagnostic suite, and digital experimental workflow. Initial experimental results from the first integrated operation of the facility will be presented, including flow characterization, power limitations, and deployment of the initial diagnostic suite. Ongoing development efforts aimed at catalycity characterization, magnetic plasma control, and advanced optical diagnostics will also be discussed, illustrating how the platform supports rapid iteration from concept to experiment.

experimental diagnostics↗

NASA NTRSDate not supplied

ARCTRON: A Rapid Experimental Proving Ground for TPS Experiments and Arcjet Technology Development

Innovation in high-enthalpy facilities is fundamentally limited by the cost and risk of experimentation. New concepts for plasma control, diagnostics, facility components, and plasma-material interaction often require repeated iterations that are impractical to perform in production arcjets. As a result, promising ideas may remain unexplored or reach operational facilities only after significant development effort. ARCTRON is being developed as a rapid experimental proving ground where new ideas in plasma science, arcjet engineering, diagnostics, and material response can be conceived, tested, and quantitatively evaluated before transition to large-scale facilities. The platform combines radio-frequency (RF) and DC arc plasma generation, externally applied magnetic fields, configurable gas composition, reduced-pressure operation, laser heating, electrical biasing, and modular diagnostic access. These capabilities permit the plasma source, applied forcing, test article, and measurement configuration to be modified independently, allowing individual physical mechanisms to be isolated more readily than in a traditional test environment. One class of investigations addresses fundamental plasma-surface interaction physics. Conventional material tests often expose a specimen simultaneously to convective heating, reactive species, pressure, shear, radiation, and surface-current effects. The resulting material response may be measured accurately, while the contribution of each mechanism remains difficult to identify. ARCTRON is designed to vary these effects selectively. Plasma chemistry can be changed independently through configurable gas mixtures; magnetic fields and electrical biasing can modify charged-particle transport; laser heating can provide a non-plasma thermal input; and pressure, flow, and discharge mode can be varied over a broad operating space. This enables controlled tests of hypotheses involving surface catalycity, reactive-species transport, plasma-assisted oxidation, electromagnetic effects, shear, and the relative contributions of thermal and chemical loading. A second class of investigations enabled by this approach concerns the engineering of high-enthalpy facilities themselves. Arc-heated facilities are limited by electrode erosion, unstable arc attachment, localized heating, and damage to nozzles and other plasma-facing components. ARCTRON provides a lower-cost environment for testing concepts intended to mitigate these limitations. Candidate investigations include the use of applied magnetic fields to alter current paths and reduce plasma interaction with nozzle walls, ExB forcing to introduce controlled plasma rotation, magnetic or geometric approaches for distributing arc attachment, and alternative electrode or discharge configurations intended to reduce erosion and improve stability. Because the platform is reconfigurable, these concepts can be evaluated through repeated design--build--test cycles before they are considered for implementation in operational facilities. The platform also supports the development and validation of diagnostics that may be difficult to introduce initially into a large arcjet. Current and planned measurements include spatially resolved optical emission spectroscopy, electrostatic probes, fast imaging, pyrometry, calorimetry, laser-induced fluorescence, and absorption spectroscopy. These diagnostics are intended not merely to document a nominal operating condition, but to constrain the local plasma state and its relationship to component or material response. The modular facility geometry allows diagnostic concepts to be tested, calibrated, and compared under repeatable conditions before deployment in more demanding environments. ARCTRON is also supported by an integrated software suite. Automated control and data acquisition allow discharge parameters, gas composition, magnetic fields, diagnostic timing, and test configuration to be recorded as part of each experiment (STARDAC - Software for Testing, Analysis, Research Data, and Control). The Backend for Experiment Analysis, Storage, and Traceability (BEAST) is a database that provides the infrastructure needed to associate heterogeneous measurements with facility configuration, specimen identity, calibration state, geometry, and analysis provenance. This backend is particularly important for exploratory campaigns, in which many related configurations may be tested, and the value of an individual experiment depends on its connection to earlier and subsequent iterations. Complementary analysis capabilities, including computer-vision-based transient response measurements (arcjetCV), three-dimensional surface reconstruction (STARSCAN), and model-based Bayesian inference (SHIELD), and tomography data analysis (TOMATO, PuMA) can be incorporated when required by a specific hypothesis without becoming the focus of every campaign. The central objective of ARCTRON is therefore not to maximize heat flux or reproduce a complete flight environment. Its purpose is to reduce the cost and time required to ask consequential questions about plasma behavior, plasma-facing materials, diagnostics, and arcjet technology. By providing a controlled environment for rapid reconfiguration, mechanism isolation, quantitative measurement, and iterative engineering, ARCTRON can help mature concepts that would otherwise remain too speculative or too risky for evaluation in production facilities. The resulting knowledge can then guide the design of material models, focus test objectives in larger arcjets, reduce facility-development risk, and improve the physical basis of high-enthalpy ground testing. This work will present the ARCTRON architecture, operating modes, diagnostic suite, and digital experimental workflow. Initial experimental results from the first integrated operation of the facility will be presented, including flow characterization, power limitations, and deployment of the initial diagnostic suite. Ongoing development efforts aimed at catalycity characterization, magnetic plasma control, and advanced optical diagnostics will also be discussed, illustrating how the platform supports rapid iteration from concept to experiment.

experimental diagnostics↗