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DOE OSTI2025

Multiscale Modeling of the Mechanical Response of Silicon Carbide Composite Within the Accelerated Fuel Qualification Framework

The accelerated fuel qualification (AFQ) framework has been used for the initial development of multiscale modeling of silicon carbide (SiC) fiber reinforced composite (SiC-SiC). The AFQ framework provides a methodology to leverage physics-informed multiscale modeling along with a reduced set of empirical test data to reduce the time and cost of licensing and qualification of new nuclear fuel systems while maintaining the overall nuclear power plant safety case. SiC-SiC is being proposed for in-core applications, most notably fuel cladding, for current and next-generation nuclear reactors because of its high temperature stability, irradiation tolerance, and ability to withstand many accident conditions. As these composites exhibit multiscale architectures and complex microstructure-based fracture mechanics, it is an appealing use case for the AFQ methodology. While the end goal of this work is a single multiscale model that can be used for predictive in-core performance, current focus is on the individual various length scale models. Four individual models have been initially developed from microscale to engineering system level to capture key physics-based effects across different length scales. These models include a microscale homogenized tow model, a mesoscale fast Fourier transform–based weave model that integrates the homogenized tow model, a mesoscale finite element–based weave model, and a system-level BISON fuel performance model. Results of these models have undergone an initial comparison with separate-effects test data showing a good match to experimental results. By using the AFQ framework during model development, several near-term benefits have been secured including a reduction in development time for the SiC-SiC cladding, more targeted irradiation testing, and a better understanding of uncertainty.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

NASA NTRS1990

Real-time diagnostics of the reusable rocket engine using on-line system identification

A model-based failure diagnosis system has been proposed for real-time diagnosis of SSME failures. Actuation, sensor, and system degradation failure modes are all considered by the proposed system. In the case of SSME actuation failures, it was shown that real-time identification can effectively be used for failure diagnosis purposes. It is a direct approach since it reduces the detection, isolation, and the estimation of the extent of the failures to the comparison of parameter values before and after the failure. As with any model-based failure detection system, the proposed approach requires a fault model that embodies the essential characteristics of the failure process. The proposed diagnosis approach has the added advantage that it can be used as part of an intelligent control system for failure accommodation purposes.

Guo, T.-H.↗

NASA NTRS1992

Formalization and visualization of domain-specific software architectures

This paper describes a domain-specific software design system based on the concepts of software architectures engineering and domain-specific models and languages. In this system, software architectures are used as high level abstractions to formulate a domain-specific software design. The software architecture serves as a framework for composing architectural fragments (e.g., domain objects, system components, and hardware interfaces) that make up the knowledge (or model) base for solving a problem in a particular application area. A corresponding software design is generated by analyzing and describing a system in the context of the software architecture. While the software architecture serves as the framework for the design, this concept is insufficient by itself for supplying the additional details required for a specific design. Additional domain knowledge is still needed to instantiate components of the architecture and develop optimized algorithms for the problem domain. One possible way to obtain the additional details is through the use of domain-specific languages. Thus, the general concept of a software architecture and the specific design details provided by domain-specific languages are combined to create what can be termed a domain-specific software architecture (DSSA).

Bailor, Paul D.↗

NASA NTRS2016

Engineering Design Tools for Shape Memory Alloy Actuators: CASMART Collaborative Best Practices and Case Studies

The primary goal of the Consortium for the Advancement of Shape Memory Alloy Research and Technology (CASMART) is to enable the design of revolutionary applications based on shape memory alloy (SMA) technology. In order to help realize this goal and reduce the development time and required experience for the fabrication of SMA actuation systems, several modeling tools have been developed for common actuator types and are discussed herein along with case studies, which highlight the capabilities and limitations of these tools. Due to their ability to sustain high stresses and recover large deformations, SMAs have many potential applications as reliable, lightweight, solid-state actuators. Their advantage over classical actuators can also be further improved when the actuator geometry is modified to fit the specific application. In this paper, three common actuator designs are studied: wires, which are lightweight, low-profile, and easily implemented; springs, which offer actuation strokes upwards of 200 at reduced mechanical loads; and torque tubes, which can provide large actuation forces in small volumes and develop a repeatable zero-load actuation response (known as the two-way shape memory effect). The modeling frameworks, which have been implemented in the design tools, are developed for each of these frequently used SMA actuator types. In order to demonstrate the versatility and flexibility of the presented design tools, as well as validate their modeling framework, several design challenges were completed. These case studies include the design and development of an active hinge for the deployment of a solar array or foldable space structure, an adaptive solar array deployment and positioning system, a passive air temperature controller for regulation flow temperatures inside of a jet engine, and a redesign of the Corvette active hatch, which allows for pressure equalization of the car interior. For each of the presented case studies, a prototype or proof-of-concept was fabricated and the experimental results and lessons learned are discussed. This analysis presents a collection of CASMART collaborative best practices in order to allow readers to utilize the available design tools and understand their modeling principles. These design tools, which are based on engineering models, can provide first-order optimal designs and are a basic and efficient method for either demonstrating design feasibility or refining design parameters. Although the design and integration of an SMA-based actuation system always requires application- and environment-specific engineering considerations, common modeling tools can significantly reduce the investment required for actuation system development and provide valuable engineering insight.

Design tools↗

NASA NTRS2003

Lessons Learned from using a Livingstone Model to Diagnose a Main Propulsion System

NASA researchers have demonstrated that qualitative, model-based reasoning can be used for fault detection in a Main Propulsion System (MPS), a complex, continuous system. At the heart of this diagnostic system is Livingstone, a discrete, propositional logic-based inference engine. Livingstone comprises a language for specifying a discrete model of the system and a set of algorithms that use the model to track the system's state. Livingstone uses the model to test assumptions about the state of a component - observations from the system are compared with values predicted by the model. The intent of this paper is to summarize some advantages of Livingstone seen through our modeling experience: for instance, flexibility in modeling, speed and maturity. We also describe some shortcomings we perceived in the implementation of Livingstone, such as modeling continuous dynamics and handling of transients. We list some upcoming enhancements to the next version of Livingstone that may resolve some of the current limitations.

Sweet, Adam↗

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 NTRSDate not supplied

Exploitation of a Validation Hierarchy for Modeling and Simulation

Across engineering there is an evolving need to increase reliance on physics-based simulation to develop, design and optimize engineering systems. This increased reliance on modeling and simulation has highlighted a growing need to transform the confidence that modeling and simulation analysts have in their results into credibility for systems engineers to design and field systems more quickly and with less physical testing. For isolated components of a complex system, where a single discipline may drive product design, this is less of a concern as the relationship is often straightforward and easy to explain. However, when these isolated components are integrated, and are expected to operate in a multi-disciplinary context in which safety critical systems are involved, new concepts and model assurance standards are required. In this paper we address this challenge by showing how a model validation hierarchy can be exploited to identify those model validation experiments that will contribute most to increasing confidence and credibility of modeling and simulation predictions. The approach that is adopted contains four main steps. The first step is the construction of a model validation hierarchy that links subsystems, assemblies, and components to a hierarchy of physical experiments that can be used support model validation. This hierarchy connects the concerns of systems engineers to those of the modeling and simulation analyst in a clear and logical way. The structure and content of this hierarchy is then used in a second step to establish which physical phenomena have the greatest impact on overall system performance metrics. A gap analysis technique, based upon modeling and simulation concerns, is then used to prioritize the important physical phenomenon. Unfortunately, a common outcome of such gap analyses is the identification of many important gaps and so, in the final step of our process, we advocate the use of a global sensitivity analysis as a means to complete the prioritization.

Verification and Validation↗

NASA NTRSDate not supplied

Exploitation of a Validation Hierarchy for Modeling and Simulation

Verification and Validation↗

NASA NTRS1984

SPIRE Data-Base Management System

Spacelab Payload Integration and Rocket Experiment (SPIRE) data-base management system (DBMS) based on relational model of data bases. Data bases typically used for engineering and mission analysis tasks and, unlike most commercially available systems, allow data items and data structures stored in forms suitable for direct analytical computation. SPIRE DBMS designed to support data requests from interactive users as well as applications programs.

Fuechsel, C. F.↗

NASA NTRS1993

Qualitative model-based diagnostics for rocket systems

A diagnostic software package is currently being developed at NASA LeRC that utilizes qualitative model-based reasoning techniques. These techniques can provide diagnostic information about the operational condition of the modeled rocket engine system or subsystem. The diagnostic package combines a qualitative model solver with a constraint suspension algorithm. The constraint suspension algorithm directs the solver's operation to provide valuable fault isolation information about the modeled system. A qualitative model of the Space Shuttle Main Engine's oxidizer supply components was generated. A diagnostic application based on this qualitative model was constructed to process four test cases: three numerical simulations and one actual test firing. The diagnostic tool's fault isolation output compared favorably with the input fault condition.

Maul, William↗

NASA NTRS1993

Qualitative model-based diagnostics for rocket systems

Maul, William↗

NASA NTRS2006

Practical Application of Model-based Programming and State-based Architecture to Space Missions

A viewgraph presentation to develop models from systems engineers that accomplish mission objectives and manage the health of the system is shown. The topics include: 1) Overview; 2) Motivation; 3) Objective/Vision; 4) Approach; 5) Background: The Mission Data System; 6) Background: State-based Control Architecture System; 7) Background: State Analysis; 8) Overview of State Analysis; 9) Background: MDS Software Frameworks; 10) Background: Model-based Programming; 10) Background: Titan Model-based Executive; 11) Model-based Execution Architecture; 12) Compatibility Analysis of MDS and Titan Architectures; 13) Integrating Model-based Programming and Execution into the Architecture; 14) State Analysis and Modeling; 15) IMU Subsystem State Effects Diagram; 16) Titan Subsystem Model: IMU Health; 17) Integrating Model-based Programming and Execution into the Software IMU; 18) Testing Program; 19) Computationally Tractable State Estimation & Fault Diagnosis; 20) Diagnostic Algorithm Performance; 21) Integration and Test Issues; 22) Demonstrated Benefits; and 23) Next Steps

Mission Data System (MDS)↗

NASA NTRS2005

Managed Development Environment Successes for MSFC's VIPA Team

This paper outlines the best practices of the Vehicle Design Team for VIPA. VIPA is the Vehicle Integrated Performance Analysis Team at MSFC. This team was created to reconnect the individual engineering disciplines to be able to perform system level technical assessments in support of program decisions. The functions of the VIPA Vehicle Design (VVD) discipline team are to maintain the controlled reference geometry and provide linked, simplified geometry for each of the other discipline analyses. The core of the VVD work, and the approach for VVD s first task of controlling the reference geometry, involves systems engineering, top-down, layout-based CAD modeling within a Product Data Manager (PDM) development environment. The topdown approach allcws for simple contrnl of very large, integrated assemblies and greatly enhances the ability to generate trade configurations and reuse data. The second W D task, model simplification for analysis, is handled within the managed environment through application of the master model concept. In this approach, there is a single controlling, or master, product definition dataset. Connected to this master model are reference datasets with live geometric and expression links. The referenced models can be for drawings, manufacturing, visualization, embedded analysis, or analysis simplification. A discussion of web based interaction, including visualization, between the design and other disciplines is included. Demonstrated examples are cited, including the Space Launch Initiative development cycle, the Saturn V systems integration and verification cycle, an Orbital Space Plane study, and NASA Exploration Office studies of Shuttle derived and clean sheet launch vehicles. The VIPA Team has brought an immense amount of detailed data to bear on program issues. A central piece of that success has been the Managed Development Environment and the VVD Team approach to modeling.

Finckenor, Jeff↗

NASA NTRS2005

Managed Development Environment Successes for MSFC's VIPA Team

This paper outlines the best practices of the Vehicle Design Team for VIPA. The functions of the VIPA Vehicle Design (VVD) discipline team are to maintain the controlled reference geometry and provide linked, simplified geometry for each of the other discipline analyses. The core of the VVD work, and the approach for VVD s first task of controlling the reference geometry, involves systems engineering, top-down, layout-based CAD modeling within a Product Data Manager (PDM) development environment. The top- down approach allows for simple control of very large, integrated assemblies and greatly enhances the ability to generate trade configurations and reuse data. The second VVD task, model simplification for analysis, is handled within the managed environment through application of the master model concept. In this approach, there is a single controlling, or master, product definition dataset. Connected to this master model are reference datasets with live geometric and expression links. The referenced models can be for drawings, manufacturing, visualization, embedded analysis, or analysis simplification. A discussion of web based interaction, including visualization, between the design and other disciplines is included. Demonstrated examples are cited, including the Space Launch Initiative development cycle, the Saturn V systems integration and verification cycle, an Orbital Space Plane study, and NASA Exploration Office studies of Shuttle derived and clean sheet launch vehicles. The VIPA Team has brought an immense amount of detailed data to bear on program issues. A central piece of that success has been the Managed Development Environment and the VVD Team approach to modeling.

Finckenor, Jeff↗

NASA NTRS1995

A method for diagnosing time dependent faults using model-based reasoning systems

This paper explores techniques to apply model-based reasoning to equipment and systems which exhibit dynamic behavior (that which changes as a function of time). The model-based system of interest is KATE-C (Knowledge based Autonomous Test Engineer) which is a C++ based system designed to perform monitoring and diagnosis of Space Shuttle electro-mechanical systems. Methods of model-based monitoring and diagnosis are well known and have been thoroughly explored by others. A short example is given which illustrates the principle of model-based reasoning and reveals some limitations of static, non-time-dependent simulation. This example is then extended to demonstrate representation of time-dependent behavior and testing of fault hypotheses in that environment.

Goodrich, Charles H.↗

NASA NTRS1997

Remote Sensing of Surficial Process Responses to Extreme Meteorological Events

Changes in the frequency and magnitude of extreme meteorological events are associated with changing environmental means. Such events are important in human affairs, and can also be investigated by orbital remote sensing. During the course of this project, we applied ERS-1, ERS-2, Radarsat, and an airborne sensor (AIRSAR-TOPSAR) to measure flood extents, flood water surface profiles, and flood depths. We established a World Wide Web site (the Dartmouth Flood Observatory) for publishing remote sensing-based maps of contemporary floods worldwide; this is also an online "active archive" that presently constitutes the only global compilation of extreme flood events. We prepared an article for EOS concerning SAR imaging of the Mississippi Valley flood; an article for the International Journal of Remote Sensing on measurement of a river flood wave using ERS-2, began work on an article (since completed and published) on the Flood Observatory for a Geoscience Information Society Proceedings volume, and presented lectures at several Geol. Soc. of America Natl. Meetings, an Assoc. of Amer. Geographers Natl. Meeting, and a Binghamton Geomorphology Symposium (all on SAR remote sensing of the Mississippi Valley flood). We expanded in-house modeling capabilities by installing the latest version of the Army Corps of Engineers RMA two-dimensional hydraulics software and BYU Engineering Graphics Lab's Surface Water Modeling System (finite elements based pre- and post-processors for RMA work) and also added watershed modeling software. We are presently comparing the results of the 2-d flow models with SAR image data. The grant also supported several important upgrades of pc-based remote sensing infrastructure at Dartmouth. During work on this grant, we collaborated with several workers at the U.S. Army Corps of Engineers, Remote Sensing/GIS laboratory (for flood inundation mapping and modeling; particularly of the Illinois River using the AIRSAR/TOPSAR/ERS-2 combined data), with Dr. Karen Prestegaard at the University of Maryland (geomorphological responses to the extreme 1993 flood along the Raccoon drainage in central Iowa), and with Mr Tim Scrom of the Albany National Weather Service River Forecast Center (initial planning for the use of Radarsat and ERS-2 for flood warning). The work thus initiated with this proposal is continuing.

Brakenridge, G. Robert↗

NASA NTRS2000

The Life Cycle Application of Intelligent Software Modeling for the First Materials Science Research Rack

Marshall Space Flight Center (MSFC) has been funding development of intelligent software models to benefit payload ground operations for nearly a decade. Experience gained from simulator development and real-time monitoring and control is being applied to engineering design, testing, and operation of the First Material Science Research Rack (MSRR-1). MSRR-1 is the first rack in a suite of three racks comprising the Materials Science Research Facility (MSRF) which will operate on the International Space Station (ISS). The MSRF will accommodate advanced microgravity investigations in areas such as the fields of solidification of metals and alloys, thermo-physical properties of polymers, crystal growth studies of semiconductor materials, and research in ceramics and glasses. The MSRR-1 is a joint venture between NASA and the European Space Agency (ESA) to study the behavior of different materials during high temperature processing in a low gravity environment. The planned MSRR-1 mission duration is five (5) years on-orbit and the total design life is ten (IO) years. The MSRR-1 launch is scheduled on the third Utilization Flight (UF-3) to ISS, currently in February of 2003). The objective of MSRR-1 is to provide an early capability on the ISS to conduct material science, materials technology, and space product research investigations in microgravity. It will provide a modular, multi-user facility for microgravity research in materials crystal growth and solidification. An intelligent software model of MSRR-1 is under development and will serve multiple purposes to support the engineering analysis, testing, training, and operational phases of the MSRR-1 life cycle development. The G2 real-time expert system software environment developed by Gensym Corporation was selected as the intelligent system shell for this development work based on past experience gained and the effectiveness of the programming environment. Our approach of multi- uses of the simulation model and its intuitive graphics capabilities is providing a concurrent engineering environment for rapid prototyping and development. Operational schematics of the MSRR-1 electrical, thermal control, vacuum access, and gas supply systems, and furnace inserts are represented graphically in the environment. Logic to represent first order engineering calculations is coded into the knowledge base to simulate the operational behavior of the MSRR-1 systems. An example of engineering data provided includes electrical currents, voltages, operational power, temperatures, thermal fluid flow rates. pressures, and component status indications. These type of data are calculated and displayed at appropriate instrumentation points, and the schematics are animated to reflect the simulated operational status of the MSRR-1. The software control functions are also simulated to represent appropriate operational behavior based on automated control and response to commands received by the crew or ground controllers. The first benefit of this simulation environment is being realized in the high fidelity engineering analysis results from the electrical power system G2 model. Secondly, the MSRR-1 simulation model will be embedded with a hardware mock-up of the MSRR-1 to provide crew training on MSRR-1 integrated payload operations. G2 gateway code will output the simulated instrumentation values, termed as telemetry, in a flight-like data stream so that the crew has realistic and accurate simulated MSRR-1 data on the flight displays which will be designed for crew use. The simulation will also respond appropriately to crew or ground initiated commands, which will be part of normal facility operations. A third use of the G2 model is being planned; the MSRR-1 simulation will be integrated with additional software code as part of the test configuration of the primary onboard computer, or Master Controller, for MSRR-1. We will take advantage of the G2 capability to simulate the flight like data stream to test flight software responses and behavior. A fourth use of the G2 model will be to train the Ground Support Personnel that will monitor the MSRR-1 systems and payloads while they are operating aboard the ISS. The intuitive, schematic based environment will provide an excellent foundation for personnel to understand the integrated configuration and operation of the MSRR-1, and the anticipated telemetry feedback based on operational modes of the equipment. Expert monitoring features will be enhanced to provide a smart monitoring environment for the operators. These features include: (1) Animated, intuitive schematic-based displays which reflect telemetry values, (1) Real-time plotting of simulated or incoming sensor values, (3) High/Low exception monitoring for analog data, (4) Expected state monitoring for discrete data, (5) Data trending, (6) Automated malfunction procedure execution to diagnose problems, (7) Look ahead capability to planned MSRR-1 activities in the onboard timeline. And finally, the logic to calculate telemetry values will be deactivated, and the same environment will interface to the incoming data for the real-time telemetry stream to schematically represent the onboard hardware configuration. G2 will be the foundation for the real-time monitoring and control environment. In summary, our MSRR-1 simulation model spans many elements of the life cycle development of this project: Engineering Analysis, Test and Checkout, Training of Crew and Ground Personnel, and Real-time monitoring and control. By utilizing the unique features afforded by an expert system development environment, we have been able to synergize a powerful tool capable of addressing our project needs at every phase of project development.

Rice, Amanda↗

DOE OSTI2024

Optimizing Batch Crystallization with Model-based Design of Experiments

Adaptive and self-optimizing intelligent systems such as digital twins are increasingly important in science and engineering. Digital twins utilize mathematical models to provide added precision to decision-making. However, physics-informed models are challenging to build, calibrate, and validate with existing data science methods. Model-based design of experiments (MBDoE) is a popular framework for optimizing data collection to maximize parameter precision in mathematical models and digital twins. In this work, we apply MBDoE, facilitated by the open-source package Pyomo.DoE, to train and validate mathematical models for batch crystallization. We quantitatively examined the estimability of the model parameters for experiments with different cooling rates. This analysis provides a quantitative explanation for the heuristic of using multiple experiments at different cooling rates.

Lynch, Hailey↗