Workforce Efforts in Model Based Systems Engineering
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Correlations of Additive Manufacturing Model-Based Process Metrics With Spatter-Induced Porosity in the Powder Bed Fusion-Laser Beam/Metallic Process
Components fabricated using the powder bed fusion laser beam metallic (PBF-LB/M) additive manufacturing (AM) process comprise a multitude of sequential weld passes. Qualifying materials for components in critical applications requires a thorough understanding of pertinent processing-microstructure-property relationships. Porosity defects have a strong adverse effect on the mechanical properties of a material. The morphology of porosity defects created by lack of fusion in PBF-LB/M often exhibit high aspect ratios that can act as stress concentrators and become crack initiation sites. The occurrence of spatter induced porosity is studied using synchronized AM model-based process metrics and porosity measured by high-resolution X-ray computed tomography. A novel AM process metric is introduced to quantify the relative exposure to spatter ejecta impacts and incorporation throughout the sequence of the PBF-LB/M process. Further characterization using optical metallography and scanning electron microscopy indicated that both keyhole and lack of fusion porosity correlated statistically with the spatter ejecta impact field of the PBF-LB/M process. Both keyhole and lack of fusion porosity can be predicted by the spatter exposure process metric, which can be exploited to control the fusion sequence.
Additive Manufacturing↗
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.↗
Assessments of a Turbulence Model Based on Menter's Modification to Rotta's Two-Equation Model
The main objective of this paper is to construct a turbulence model with a more reliable second equation simulating length scale. In the present paper, we assess the length scale equation based on Menter s modification to Rotta s two-equation model. Rotta shows that a reliable second equation can be formed in an exact transport equation from the turbulent length scale L and kinetic energy. Rotta s equation is well suited for a term-by-term modeling and shows some interesting features compared to other approaches. The most important difference is that the formulation leads to a natural inclusion of higher order velocity derivatives into the source terms of the scale equation, which has the potential to enhance the capability of Reynolds-averaged Navier-Stokes (RANS) to simulate unsteady flows. The model is implemented in the PAB3D solver with complete formulation, usage methodology, and validation examples to demonstrate its capabilities. The detailed studies include grid convergence. Near-wall and shear flows cases are documented and compared with experimental and Large Eddy Simulation (LES) data. The results from this formulation are as good or better than the well-known SST turbulence model and much better than k-epsilon results. Overall, the study provides useful insights into the model capability in predicting attached and separated flows.
Abdol-Hamid, Khaled S.↗
Cross-calibration of Imaging Sensors using Model-based, SI-traceable Predictions of At-sensor Radiance
Many inter-consistency efforts force empirical agreement between sensors viewing a source nearly coincident in time and geometry that ensures consistency between sensors rather than obtain an SI-traceable calibration with documented error budgets. The method described here provides interconsistency via absolute radiometric calibration with defensible error budget avoiding systematic errors through prediction of at-sensor radiance for a site viewed by multiple sensors but not necessarily viewed at coincident times. The method predicts spectral radiance over a given surface site for arbitrary view and illumination angles and for any date dominated by clear-sky conditions. The foundation is a model-based, SI-traceable prediction of at-sensor radiance over selected sites based on physical understanding of the surface and atmosphere. The calibration of the ground site will include spatial, spectral, and sunview geometric effects based on satellite and ground-based data. The result is an interconsistency of hyperspectral and multispectral sensors spanning spatial resolutions from meters to kilometers all relative to the surface site rather than a single sensor. The source-centric philosophy of calibrating the site inherently accounts for footprint size mismatch, spectral band mismatch, and temporal and spatial sampling effects. The method for characterizing the test site allows its use for SI-traceable calibration of any sensor that can view the calibrated test site. Interconsistency is obtained through the traceability and error budget rather than coincident views. Such an approach to inter-consistency provides better understanding of biases between sensors as well producing more accurate results with documented SI-traceability that reduces the need for overlapping data sets.
Thome, Kurtis↗
Applying Model-Based Reasoning to the FDIR of the Command and Data Handling Subsystem of the International Space Station
All of the International Space Station (ISS) systems which require computer control depend upon the hardware and software of the Command and Data Handling System (C&DH) system, currently a network of over 30 386-class computers called Multiplexor/Dimultiplexors (MDMs)[18]. The Caution and Warning System (C&W)[7], a set of software tasks that runs on the MDMs, is responsible for detecting, classifying, and reporting errors in all ISS subsystems including the C&DH. Fault Detection, Isolation and Recovery (FDIR) of these errors is typically handled with a combination of automatic and human effort. We are developing an Advanced Diagnostic System (ADS) to augment the C&W system with decision support tools to aid in root cause analysis as well as resolve differing human and machine C&DH state estimates. These tools which draw from sources in model-based reasoning[ 16,291, will improve the speed and accuracy of flight controllers by reducing the uncertainty in C&DH state estimation, allowing for a more complete assessment of risk. We have run tests with ISS telemetry and focus on those C&W events which relate to the C&DH system itself. This paper describes our initial results and subsequent plans.
Robinson, Peter↗
NASA’s Atmospheric Science Data Center’s Approach to a Cloud-Based Model of Ingest, Archival, and Distribution of TEMPO Data: Methods, Challenges, and Best Practices
The National Aeronautics and Space Administration's (NASA) Atmospheric Science Data Center (ASDC) at NASA Langley Research Center in Hampton, VA provides atmospheric science data products and services to the science community, including enhanced search and subsetting capabilities for numerous datasets. The ASDC is the official Distributed Active Archive Center (DAAC) of record for the upcoming Tropospheric Emissions: Monitoring of Pollution (TEMPO) instrument. TEMPO will be situated on a geostationary satellite positioned at a longitude near the center of the conterminous United States and focused on North America, making hourly swaths of its field of regard from east to west. ASDC’s data products are currently hosted locally and services (e.g., spatial and temporal subsetting) are managed on premises. The ASDC is planning to provide TEMPO data and services in the cloud through the Earthdata Search platform. This presentation will discuss the ASDC’s approach to a cloud-based model of ingest, archival, and distribution of TEMPO data. Methods, challenges, best practices, lessons learned, and future plans will be discussed.
Iman Nasif↗
Natural Language Processing to Inform Agent-Based Modeling: With Application to Modeling Adoption of Medium-Duty Electric Vehicles
Agent-based socio-technical modeling of medium- and heavy-duty (MDHD) electric vehicle (EV) adoption has the potential to provide analysis, prediction, and gui. This paper describes new applications of text analysis developed through machine learning (ML) to build and understand relevant topics and their saliency in the published discourse on adoption of MDHD EVs. This work contributes to the state of the art in topic mining models by defining a new metric of topic ranking (START) that quantifies the importance of predefined topics within the corpus using weighted results for predefined topics from two topic modeling approaches: Latent Dirichlet Allocation (LDA) and BERTopic. The START metric is then demonstrated in practice to model how academia and industry view the EV adoption process based on the respective texts published by these groups. Results show that academic literature places more emphasis on categories of interests such as norms/attitudes and adopter knowledge, while trade journals tend to emphasize long-term cost more than academia. The two bodies of literature agree on the importance of policy and incentives in MDHD EV adoption. Together these results illustrate the potential to use ML-based text analysis to populate the characteristics of agent-based socio-technical models.
Electric vehicle adoption, fleet electrification, ↗
Best practices in software development for robust and reproducible geoscientific models based on insights from the Global Carbon Budget's dynamic vegetation models
Computational models play an increasingly vital role in scientific research by enabling the numerical simulation of complex processes. Such models are also fundamental in geosciences. For instance, they offer critical insights into the impacts of global change on the Earth system today and in the future. Beyond their value as research tools, models are also software products and should therefore adhere to certain established software engineering standards. However, scientists are rarely trained as software developers, which can lead to potential deficiencies in software quality like unreadable, inefficient, or erroneous code. The complexity of models, coupled with their integration into broader workflows, also often makes it challenging to reproduce results, evaluate processes, and build upon them. In this paper, we review the state and current practices of the development processes of the state-of-the-art land surface models used by the Global Carbon Budget. We combine the experience of modelers from the respective research groups with the expertise of software engineers from tech companies to outline key principles and tools for improving software quality in research. We explore four main areas: (1) model testing and validation, (2) scientific, technical, and user documentation, (3) version control, continuous integration, and code review, and (4) the portability and reproducibility of workflows. Our review reveals that while modeling communities are incorporating many best practices, significant room for improvement remains in areas such as automated testing, automated documentation, and reproducibility. Therefore, we here identify and promote essential software engineering practices, including numerous examples of practices from within the community that can serve as guidelines for other models and could help streamline processes across the entire community. We conclude with an open-source example implementation of these principles, demonstrating portable and reproducible data flows, a continuous integration setup, and web-based visualizations. This example may serve as a practical resource for model developers, users, and all scientists engaged in scientific programming.
Gregor, Konstantin [Technical Univ. of Munich (Ger↗
Experimental Validation of Model-Based Prognostics for Pneumatic Valves
Because valves control many critical operations, they are prime candidates for deployment of prognostic algorithms. But, similar to the situation with most other components, examples of failures experienced in the field are hard to come by. This lack of data impacts the ability to test and validate prognostic algorithms. A solution sometimes employed to overcome this shortcoming is to perform run-to-failure experiments in a lab. However, the mean time to failure of valves is typically very high (possibly lasting decades), preventing evaluation within a reasonable time frame. Therefore, a mechanism to observe development of fault signatures considerably faster is sought. Described here is a testbed that addresses these issues by allowing the physical injection of leakage faults (which are the most common fault mode) into pneumatic valves. What makes this testbed stand out is the ability to modulate the magnitude of the fault almost arbitrarily fast. With that, the performance of end-of-life estimation algorithms can be tested. Further, the testbed is mobile and can be connected to valves in the field. This mobility helps to bring the overall process of prognostic algorithm development for this valve a step closer to validation. The paper illustrates the development of a model-based prognostic approach that uses data from the testbed for partial validation.
Chetan S Kulkarni↗
Validation of Model-Based Prognostics for Pneumatic Valves in a Cryogenic Fueling Demonstration Testbed
Because valves control many critical operations, they are prime candidates for deployment of prognostic algorithms. But, similar to the situation with most other components, examples of failures experienced in the field are hard to come by. This lack of data impacts the ability to test and validate prognostic algorithms. A solution sometimes employed to overcome this shortcoming is to perform run to failure experiments in a lab. However, the mean time to failure of valves is typically very high (possibly lasting decades), preventing evaluation within a reasonable time frame. Therefore, a mechanism to observe development of fault signatures considerably faster is sought. Described here is a testbed that addresses these issues by allowing the physical injection of leakage faults (which are the most common fault mode) into pneumatic valves. What makes this testbed stand out is the ability to modulate the magnitude of the fault almost arbitrarily fast. With that, the performance of end-of-life estimation algorithms can be tested. Further, the testbed is mobile and can be connected to valves in the field. This mobility helps to bring the overall process of prognostic algorithm development for this valve a step closer to validation. The paper illustrates the development of a model-based prognostic approach that uses data from the testbed for partial validation.
Kulkarni, Chetan S.↗
Using Model-Based Reasoning for Autonomous Instrument Operation
Multiprobe missions are an important part of NASA's future: Cluster, Magnetospheric Multi Scale, Global Electrodynamics and Magnetospheric Constellation are representatives from the Sun-Earth Connections Theme. To make such missions robust, reliable, and affordable, ideally the many spacecraft of a constellation must be at least as easy to operate as one spacecraft is today. To support this need for scalability, science instrumentation must become increasingly easy to operate, even as this same instrumentation becomes more capable and advanced. Communication and control resources will be at a premium for future instruments. Many missions will be out of contact with ground operators for extended periods either to reduce operations cost or because of orbits that limit communication to weekly perigee transits. Autonomous capability is necessary if such missions are to effectively achieve their operational objectives. An autonomous system is one that acts given its situation in a mission appropriate manner without external direction to achieve mission goals. To achieve this capability autonomy must be built into the system through judicious design or through a built-in intelligence that recognizes system state and manages system response. To recognize desired or undesired system states, the system must have an implicit or explicit understanding of its expected states given its history and self observations. The systems we are concerned with, science instruments, can have stringent requirements for system state knowledge in addition to requirements driven by health and safety concerns. Without accurate knowledge of the system state, the usefulness of the science instrument may be severely limited. At the same time, health and safety concerns often lead to overly conservative instrument operations further reducing the effectiveness of the instrument. These requirements, coupled with overall mission requirements including lack of communication opportunities and tolerance of environmental hazards, frame the problem of constructing autonomous science instruments. we are developing a model of the Low Energy Neutral Atom instrument (LENA) that is currently flying on board the Imager for Magnetosphere-to-Aurora Global Exploration (IMAGE) spacecraft. LENA is a particle detector that uses high voltage electrostatic optics and time-of-flight mass spectrometry to image neutral atom emissions from the denser regions of the Earth's magnetosphere. As with most spacecraft borne science instruments, phenomena in addition to neutral atoms are detected by LENA. Solar radiation and energetic particles from Earth's radiation belts are of particular concern because they may help generate currents that may compromise LENA's long term performance. An explicit model of the instrument response has been constructed and is currently in use on board IMAGE to dynamically adapt LENA to the presence or absence of energetic background radiations. The components of LENA are common in space science instrumentation, and lessons learned by modelling this system may be applied to other instruments. This work demonstrates that a model-based approach can be used to enhance science instrument effectiveness. Our future work involves the extension of these methods to cover more aspects of LENA operation and the generalization to other space science instrumentation.
Johnson, Mike↗
Microstructure-Based Modeling of Inner Oxygen Pressure in Solid Oxide Electrolysis Cells
One major degradation mechanism during long-term operation of solid oxide electrolysis cells (SOECs) is delamination of oxygen electrodes (OEs). The driving force for the electrode delamination could be the generated high inner oxygen pressure near the electrode-electrolyte interface during operation. However, the effects of transport properties and electrode thickness on the inner oxygen partial pressure are not well understood. Here, a microstructure-based electrochemical model which includes the conduction of electrons and oxygen ions coupled with Butler-Volmer-type chemical reactions at triple-phase-boundaries (TPBs), is employed to investigate the oxygen pressure in lanthanum strontium manganate (LSM)-based SOECs. The model is applied to both two-dimensional (2D) prototype microstructures and three-dimensional (3D) realistic microstructures, and the oxygen pressure is analyzed as a function of transport properties and electrode thickness under both potentiostatic and galvanostatic operations. The simulation results suggest strategies to suppress electrode delamination. The simulation results are compared to an analytical solution, and the discrepancies are attributed to the Butler-Volmer-type kinetics included in the microstructure-based model.
Xue, Fei↗
Simultaneous control of the electron temperature and safety factor profiles in DIII-D using model-based optimal control techniques
Future tokamak power plants will likely operate using a single, well-defined plasma scenario, either in steady state or for very long pulse lengths. In order to enhance the robustness of the scenario, feedback controllers for a variety of plasma properties will be necessary to counteract any disturbances and ensure safe operation. However, only a limited set of actuators will be available to control many different quantities. Because of this, it is necessary to develop controllers that are able to regulate multiple plasma properties using a limited set of actuators. To this end, a controller has been developed for the simultaneous regulation of both the electron temperature and safety factor profiles in DIII-D. This algorithm uses a linear quadratic integral control synthesis approach based on a linearized model of the dynamics of the two profiles. Two neural network surrogate models, NubeamNet and MMMnet, are included to improve the fidelity of the model. Furthermore, the controller has been tested in simulation using COTSIM, and has demonstrated the ability to simultaneously track changes in both the electron temperature and safety factor targets, including changes in both the magnitude and the shape of the profiles.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
A geometric modeler based on a dual-geometry representation polyhedra and rational b-splines
For speed and data base reasons, solid geometric modeling of large complex practical systems is usually approximated by a polyhedra representation. Precise parametric surface and implicit algebraic modelers are available but it is not yet practical to model the same level of system complexity with these precise modelers. In response to this contrast the GEOMOD geometric modeling system was built so that a polyhedra abstraction of the geometry would be available for interactive modeling without losing the precise definition of the geometry. Part of the reason that polyhedra modelers are effective is that all bounded surfaces can be represented in a single canonical format (i.e., sets of planar polygons). This permits a very simple and compact data structure. Nonuniform rational B-splines are currently the best representation to describe a very large class of geometry precisely with one canonical format. The specific capabilities of the modeler are described.
Klosterman, A. L.↗
A Model-Based Systems Engineering Journey to Developing a Concept of Operations
Starting in 2017, NASA’s Human Research Program (HRP) Exploration Medical Capability (ExMC) element began a systems engineering transition from traditional, document-centric development to model-centric development when defining its foundation medical systems. These foundation medical systems define a Concept of Operations (ConOps) and identify the generic requirements for a medical system based on assumptions about a generic crew and mission environments and guidance from NASA standards (e.g., Medical “Levels of Care”). By making the transition, ExMC intends to improve communication among stakeholders about foundation medical system requirements and content. In addition, this transition will enable ExMC to lower both development and crew treatment risks for future, mission-specific medical systems. ExMC followed a Model Based Systems Engineering (MBSE) paradigm when developing the foundation medical systems. A model-based approach provides several advantages over a traditional, document-centric approach. First, when Systems Engineers (SE) develop diagrams in a model using a standard modeling language, they produce information dense pictures that facilitate understanding much more efficiently with less room for misinterpretation than text. Second, due to the evolving nature of projects, documentation becomes out of date the minute it is published. This can result in people making decisions based on information that is no longer current, especially if they are referencing a locally-stored copy of a document. A model, on the other hand, is always up to date with the latest approved changes and information. It serves as a single point of truth. Third, a model-centric approach centralizes all important information in one place. Rather than having to flip through separate ConOps documents, design specifications, requirements specifications, and the like to coordinate information, a model captures the content in one, integrated spot. This integration makes tracing information from end-to-end easier with greater reliability. The ExMC Systems Engineering Lifecycle follows a well-defined process. ExMC Systems Engineers perform all major steps of the process, regardless of the development methodology. One of the first steps in the process is developing the ConOps that describes the operation of the system from the point of view of the users. It includes a list of the users and their needs, the goals of the medical system, key assumptions about the system, and definitions of the medical system’s operational environments. For this development effort, ExMC chose to replace the traditional text-based ConOps document with a model. While the decision to change the development workflow was not difficult, implementing the structural and organizational workflows were. It required showing ExMC’s users, most of whom are not Systems Engineers, how the information they require would be presented in the model and to gain their acceptance of this approach. This paper documents key lessons learned during the ConOps transformation by focusing on how the model represents information, the agile workflow used by SEs when developing the model and how it integrates into a project plan, how leadership influenced key users to accept the transformation, and how the users interact with the model information.
Jeffrey Robert Cohen↗
The energetics of the ionosphere of Venus - A preliminary model based on Pioneer Venus observations
A model of the energy balance of the dayside ionosphere of Venus is presented. The coupled energy equations for electrons and ions are solved numerically and the calculated temperatures are compared with temperatures measured by instruments on the Pioneer Venus Orbiter. Neutral and ion density profiles consistent with those measured by various Pioneer Venus experiments are used in the model. It was found that using standard EUV sources and thermal conductivities the calculations produce temperatures that are much lower than the measured ones. Consequently, further calculations were performed in which (1) the thermal conductivities were inhibited by means of an almost horizontal magnetic field and/or (2) heat inflow into both the electron and ion gas at the top of the ionosphere was assumed due to the solar wind interaction. It was found that the calculated and measured temperatures were in reasonably good agreement if the thermal conductivities were inhibited by a near horizontal field of about 10 gammas and if the electron and ion heat fluxes were taken to be 4 x 10 to the 9th eV/sq cm/sec and 10 to the 7th eV/sq cm/sec, respectively.
Cravens, T. E.↗
A Correction for the IRI Topside Electron Density Model Based on Alouette/ISIS Topside Sounder Data
The topside segment of the International Reference Ionosphere (IRI) electron density model (and also of the Bent model) is based on the limited amount of topside data available at the time (40,OOO Alouette 1 profiles). Being established from such a small database it is therefore not surprising that the models have well-known shortcomings, for example, at high solar activities. Meanwhile a large data base of close to 200,000 topside profiles from Alouette 1,2, and ISIS I, 2 has become available online. A program of automated scaling and inversion of a large volume of digitized ionograms adds continuously to this data pool. We have used the currently available ISIs/Alouette topside profiles to evaluate the IRI topside model and to investigate ways of improving the model. The IRI model performs generally well at middle latitudes and shows discrepancies at low and high latitudes and these discrepancies are largest during high solar activity. In the upper topside IRI consistently overestimates the measurements. Based on averages of the data-model ratios we have established correction factors for the IRI model. These factors vary with altitude, modified dip latitude, and local time.
Bilitza, D.↗