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Modeling and Simulation Credibility Assessment of Finite Element Models for Fall From Heights Injury Scenarios
Finite element (FE) computational models of the whole human body are being used to investigate the injury modalities and mechanisms arising from suited astronauts’ ExtraVehicular Activities (EVAs). These FE whole body models – simplified Elemance and THUMS pedestrian versions – have undergone a series of verification and validation (V&V) assessments for applications in automotive, domestic, and contact sports arenas. However, the FE models’ Modeling and Simulation (M&S) credibility assessments for simulating suited astronaut injuries due to fall from heights in altered gravity environments are limited. The current study evaluates the M&S credibility of simplified Elemance and THUMS pedestrian FE models based on eight credibility factors – data pedigree, input pedigree, code verification, solution verification, conceptual validation, referent validation, results uncertainty, and results robustness – as per NASA-STD-7009A [1]. These credibility factors were assigned ordinal scores ranging between 0 to 4, with a score of 0 in the case of insufficient evidence and 4 when all data for the model is known, used appropriately, and traceable to the Real-World System (RWS) with acceptable accuracy, precision, and uncertainty. The credibility factor sufficiency thresholds were assigned upon guidance from NASA EVA subject matter experts. The factor scores were ascertained through the evaluation of M&S credibility assessment procedures described in the published literature and FE model reports. The M&S credibility scores for the Elemance and THUMS FE models vary between 1 and 3 for data pedigree, input pedigree, and referent validation credibility factors, and between 0 and 1 for code verification, solution verification, conceptual validation, results uncertainty and results robustness. The results show that these FE models are credible for simulating fall from heights injury scenarios in specific kinematic and kinetic ranges that correlate with highway and contact sports-related external conditions. Multiple credibility elevation strategies are prescribed to improve the Elemance and THUMS models’ credibility for use in the EVA fall from height injury scenarios.
2018-2019 Mid-Term Credibility Plan Review
This presentation summarizes the Interagency Modeling and Analysis Group (IMAG) / Multiscale Modeling (MSM)'s Committee on Credible Practice in Modeling and Simulation in Healthcare's (CPMS) mid-term review of each MSM U01 project's progress toward fulfilling their Model Credibility plan. Generally, the model credibility reporting and update process utilized several pieces of information formatted to communicate to the uninformed reviewer/user an assessment of steps taken toward model credibility with respect to the intended use of each U01 model, as well as communicate where the more interested reviewer/user can go to find more information. The reviewers, consisting of the members of the CPMS Executive Committee, focused on the documentation and communication of each PI's credibility efforts and did not perform an assessment of the implemented credible practice given the evolving nature of the projects. In this inaugural activity, the CPMS members sought insight on how PIs may view the importance of communicating credibility, as well as how PIs interpret establishing evidence for credibility within the scope of CPMS Tens simple rules. To that end, reviewers provided feedback on documentation and communication adequacy, and, only in few rare cases, on the credible practice itself.
Simulation Credibility: Advances in Verification, Validation, and Uncertainty Quantification
Decision makers and other users of simulations need to know quantified simulation credibility to make simulation-based critical decisions and effectively use simulations, respectively. The credibility of a simulation is quantified by its accuracy in terms of uncertainty, and the responsibility of establishing credibility lies with the creator of the simulation. In this volume, we present some state-of-the-art philosophies, principles, and frameworks. The contributing authors involved in this publication have been dedicated to advancing simulation credibility. They detail and provide examples of key advances over the last 10 years in the processes used to quantify simulation credibility: verification, validation, and uncertainty quantification. The philosophies and assessment methods presented here are anticipated to be useful to other technical communities conducting continuum physics-based simulations; for example, issues related to the establishment of simulation credibility in the discipline of propulsion are discussed. We envision that simulation creators will find this volume very useful to guide and assist them in quantitatively conveying the credibility of their simulations.
Modeling and Simulation Credibility Assessments of Whole-Body Finite Element Computational Models for Use in NASA Extravehicular Activity Applications
Computational finite element (FE) models are used in suited astronaut injury risk assessments; however, these models’ verification, validation, and credibility (VV&C) procedures for simulating injuries in altered gravity environments are limited. Our study conducts VV&C assessments of THUMS and Elemance whole-body FE models for predicting suited astronaut injury biomechanics using eight credibility factors, as per NASA-STD-7009A. Credibility factor ordinal scores are assigned by reviewing existing documentation describing VV&C practices, and credibility sufficiency thresholds are assigned based on input from subject matter experts. Our results show the FE models are credible for suited astronaut injury investigation in specific ranges of kinematic and kinetic conditions correlating to highway and contact sports events. Nevertheless, these models are deficient when applied outside these ranges. Several credibility elevation strategies are prescribed to improve models’ credibility for the NASA-centric application domain.
Modeling and simulation credibility assessments of whole-body finite element computational models for use in NASA extravehicular activity applications
Computational finite element (FE) models are used in suited astronaut injury risk assessments; however, these models’ verification, validation, and credibility (VV&C) procedures for simulating injuries in altered gravity environments are limited. Our study conducts VV&C assessments of THUMS and Elemance whole-body FE models for predicting suited astronaut injury biomechanics using eight credibility factors, as per NASA-STD-7009A. Credibility factor ordinal scores are assigned by reviewing existing documentation describing VV&C practices, and credibility sufficiency thresholds are assigned based on input from subject matter experts. Our results show the FE models are credible for suited astronaut injury investigation in specific ranges of kinematic and kinetic conditions correlating to highway and contact sports events. Nevertheless, these models are deficient when applied outside these ranges. Several credibility elevation strategies are prescribed to improve models’ credibility for the NASA-centric application domain.
Can Simulation Credibility Be Improved Using Sensitivity Analysis to Understand Input Data Effects on Model Outcome?
Model and simulation (MS) credibility is defined as, the quality to elicit belief or trust in MS results. NASA-STD-7009 [1] delineates eight components (Verification, Validation, Input Pedigree, Results Uncertainty, Results Robustness, Use History, MS Management, People Qualifications) that address quantifying model credibility, and provides guidance to the model developers, analysts, and end users for assessing the MS credibility. Of the eight characteristics, input pedigree, or the quality of the data used to develop model input parameters, governing functions, or initial conditions, can vary significantly. These data quality differences have varying consequences across the range of MS application. NASA-STD-7009 requires that the lowest input data quality be used to represent the entire set of input data when scoring the input pedigree credibility of the model. This requirement provides a conservative assessment of model inputs, and maximizes the communication of the potential level of risk of using model outputs. Unfortunately, in practice, this may result in overly pessimistic communication of the MS output, undermining the credibility of simulation predictions to decision makers. This presentation proposes an alternative assessment mechanism, utilizing results parameter robustness, also known as model input sensitivity, to improve the credibility scoring process for specific simulations.
Credible practice of modeling and simulation in healthcare: ten rules from a multidisciplinary perspective
The complexities of modern biomedicine are rapidly increasing. Thus, modeling and simulation have become increasingly important as a strategy to understand and predict the trajectory of pathophysiology, disease genesis, and disease spread in support of clinical and policy decisions. In such cases, inappropriate or ill-placed trust in the model and simulation outcomes may result in negative outcomes, and hence illustrate the need to formalize the execution and communication of modeling and simulation practices. Although verification and validation have been generally accepted as significant components of a model’s credibility, they cannot be assumed to equate to a holistic credible practice, which includes activities that can impact comprehension and in-depth examination inherent in the devel-opment and reuse of the models. For the past several years, the Committee on Credible Practice of Modeling and Simulation in Healthcare, an interdisciplinary group seeded from a U.S. interagency initiative, has worked to codify best practices. Here, we provide Ten Rules for credible practice of modeling and simulation in healthcare developed from a comparative analysis by the Committee’s multidisciplinary membership, followed by a large stakeholder com-munity survey. These rules establish a unified conceptual framework for modeling and simulation design, implementation, evaluation, dissemination and usage across the modeling and simulation life-cycle. While biomedical science and clinical care domains have somewhat different requirements and expectations for credible practice, our study converged on rules that would be useful across a broad swath of model types. In brief, the rules are: (1) Define context clearly. (2) Use contextually appropriate data. (3) Evaluate within context. (4) List limitations explicitly. (5) Use version control. (6) Document appropriately. (7) Disseminate broadly. (8) Get independent reviews. (9) Test competing imple-mentations. (10) Conform to standards. Although some of these are common sense guidelines, we have found that many are often missed or misconstrued, even by seasoned practitioners. Computational models are already widely used in basic science to generate new biomedical knowledge. As they penetrate clinical care and healthcare policy, contributing to personalized and precision medicine, clinical safety will require established guidelines for the credible practice of modeling and simulation in healthcare.
The aerospace plane design challenge: Credible computational fluid dynamics results
Computational fluid dynamics (CFD) is necessary in the design processes of all current aerospace plane programs. Single-stage-to-orbit (STTO) aerospace planes with air-breathing supersonic combustion are going to be largely designed by means of CFD. The challenge of the aerospace plane design is to provide credible CFD results to work from, to assess the risk associated with the use of those results, and to certify CFD codes that produce credible results. To establish the credibility of CFD results used in design, the following topics are discussed: CFD validation vis-a-vis measurable fluid dynamics (MFD) validation; responsibility for credibility; credibility requirement; and a guide for establishing credibility. Quantification of CFD uncertainties helps to assess success risk and safety risks, and the development of CFD as a design tool requires code certification. This challenge is managed by designing the designers to use CFD effectively, by ensuring quality control, and by balancing the design process. For designing the designers, the following topics are discussed: how CFD design technology is developed; the reasons Japanese companies, by and large, produce goods of higher quality than the U.S. counterparts; teamwork as a new way of doing business; and how ideas, quality, and teaming can be brought together. Quality control for reducing the loss imparted to the society begins with the quality of the CFD results used in the design process, and balancing the design process means using a judicious balance of CFD and MFD.
Credible Software and Simulation Uncertainty
The utility of software primarily depends on its reliability and performance; whereas, its significance depends solely on its credibility for intended use. The credibility of simulations confirms the credibility of software. The level of veracity and the level of validity of simulations determine the degree of credibility of simulations. The process of assessing this credibility in fields such as computational mechanics (CM) differs from that followed by the Defense Modeling and Simulation Office in operations research. Verification and validation (V&V) of CM simulations is not the same as V&V of CM software. Uncertainty is the measure of simulation credibility. Designers who use software are concerned with management of simulation uncertainty. Terminology and concepts are presented with a few examples from computational fluid dynamics.
Dimensions of Credibility in Models and Simulations
Based on the National Aeronautics and Space Administration's (NASA's) work in developing a standard for models and simulations (M&S), the subject of credibility in M&S became a distinct focus. This is an indirect result from the Space Shuttle Columbia Accident Investigation Board (CAIB), which eventually resulted in an action, among others, to improve the rigor in NASA's M&S practices. The focus of this action came to mean a standardized method for assessing and reporting results from any type of M&S. As is typical in the standards development process, this necessarily developed into defming a common terminology base, common documentation requirements (especially for M&S used in critical decision making), and a method for assessing the credibility of M&S results. What surfaced in the development of the NASA Standard was the various dimensions credibility to consider when accepting the results from any model or simulation analysis. The eight generally relevant factors of credibility chosen in the NASA Standard proved only one aspect in the dimensionality of M&S credibility. At the next level of detail, the full comprehension of some of the factors requires an understanding along a couple of dimensions as well. Included in this discussion are the prerequisites for the appropriate use of a given M&S, the choice of factors in credibility assessment with their inherent dimensionality, and minimum requirements for fully reporting M&S results.
Modeling and Simulation Credibility Assessments of Musculoskeletal Computational Models for Simulating Astronaut Injuries Due to a Poor Spacesuit Fit
The musculoskeletal (MS) system of astronauts is subject to physiological changes, potentially leading to injuries due to the exposure to different gravitational environments experienced during spaceflight. These injuries can occur while an astronaut is performing an Extravehicular Activity (EVA) in space, on lunar or planetary surfaces or while wearing a spacesuit during terrestrial training for an EVA. The OpenSim MS modeling software can assess EVA induced MS injury mechanisms such as muscle strains, ligament injuries and joint injuries. One area of concern, since there are only a few different spacesuit sizes with limited adjustability, is the possibility of a poorly fitting spacesuit. This can cause unnatural joint motions and torques resulting in various MS injuries. A credibility assessment of the OpenSim modeling and simulation procedures is performed per NASA-STD-7009A to provide information on the credibility of the model’s use in simulating EVA related injury mechanisms. The credibility assessment evaluated various OpenSim models against the following eight credibility factors: data pedigree, input pedigree, code verification, solution verification, conceptual validation, referent validation, results uncertainty and results robustness (sensitivity). The models evaluated for EVA injuries will require additional credibility factor analysis and upgrades to the model features, such as adding ligaments to a whole-body model, to reliably predict and analyze the EVA injuries expected to occur due to a poor spacesuit fit. The degree of elevation strategy required to increase the credibility assessment scores will depend on the model complexity and the injury mechanism.
Modeling and Simulation Credibility Assessments of Musculoskeletal Computational Models for Simulating Astronaut Injuries Due to a Poor Spacesuit Fit
The musculoskeletal (MS) system of astronauts is subject to physiological changes, potentially leading to injuries due to the exposure to different gravitational environments experienced during spaceflight. These injuries can occur while an astronaut is performing an Extravehicular Activity (EVA) in space, on lunar or planetary surfaces or while wearing a spacesuit during terrestrial training for an EVA. The OpenSim MS modeling software can assess EVA induced MS injury mechanisms such as muscle strains, ligament injuries and joint injuries. One area of concern, since there are only a few different spacesuit sizes with limited adjustability, is the possibility of a poorly fitting spacesuit. This can cause unnatural joint motions and torques resulting in various MS injuries. A credibility assessment of the OpenSim modeling and simulation procedures is performed per NASA-STD-7009A to provide information on the credibility of the model’s use in simulating EVA related injury mechanisms. The credibility assessment evaluated various OpenSim models against the following eight credibility factors: data pedigree, input pedigree, code verification, solution verification, conceptual validation, referent validation, results uncertainty and results robustness (sensitivity). The models evaluated for EVA injuries will require additional credibility factor analysis and upgrades to the model features, such as adding ligaments to a whole-body model, to reliably predict and analyze the EVA injuries expected to occur due to a poor spacesuit fit. The degree of elevation strategy required to increase the credibility assessment scores will depend on the model complexity and the injury mechanism.
Credible Practice of Models and Simulations for Healthcare
As computational models penetrate clinical care and drive healthcare policy decisions, there is increasing need to communicate that model creation and testing follows reasonable credible practice. Although verification and validation have been generally accepted as significant components of a model’s credibility, they cannot be assumed to equate to a holistic credible practice, which includes activities that can impact comprehension and in-depth examination inherent in the development and reuse of the models. This presentation introduces the Ten Rules for credible practice of modeling and simulation in healthcare developed from a comparative multidisciplinary analysis and practitioner survey. These rules establish a unified conceptual framework for modeling and simulation design, implementation, evaluation, dissemination and usage across the modeling and simulation life-cycle. Although some of these are common sense guidelines, many are often missed or misconstrued, even by seasoned practitioners.
The aerospace plane design challenge - Credible computational fluid dynamics results
In order to establish the credibility of CFD results utilized in aerospace plane design, the following topics are discussed: CFD validation in relation to 'measureable' fluid dynamics (MFD) validation, credibility requirements, responsibility for credibility, and a guide for establishing credibility. What is of paramount concern for fluid dynamic design is not CFD code validation but qualification of CFD unknowns so that their magnitude is greatly reduced and that these uncertainties are employed for designing with margin. The designers must be trained to properly use CFD if they are to produce good designs. In approximately 70 percent of the flight envelopes of SSTO aerospace planes with supersonic combustion, CFD will be necessary to determine dynamics performance and specifications.
How to Develop and Interpret a Credibility Assessment of Numerical Models for Human Research: NASA-STD-7009 Demystified
In the wake of the Columbia accident, the NASA-STD-7009 [1] credibility assessment was developed as a unifying platform to describe model credibility and the uncertainties in its modeling predictions. This standard is now being adapted by NASAs Human Research Program to cover a wide range of numerical models for human research. When used properly, the standard can improve the process of code development by encouraging the use of best practices. It can also give management more insight in making informed decisions through a better understanding of the models capabilities and limitations.To a newcomer, the abstractions presented in NASA-STD-7009 and the sheer volume of information that must be absorbed can be overwhelming. This talk is aimed at describing the credibility assessment, which is the heart of the standard, in plain terms. It will outline how to develop a credibility assessment under the standard. It will also show how to quickly interpret the graphs and tables that result from the assessment and how to drill down from the top-level view to the foundation of the assessment. Finally, it will highlight some of the resources that are available for further study.
Toward shell model interactions with credible uncertainties
Background: The nuclear shell model is a powerful framework for predicting nuclear structure observables, but relies on interaction matrix elements fit to experimental data as its inputs. Extending the shell model's applicability, particularly toward dripline nuclei, requires efficient fitting methods and credible uncertainty quantification. Traditional approaches face computational challenges and may underestimate uncertainties. Purpose: We develop and test a framework combining eigenvector continuation and Markov chain Monte Carlo to efficiently fit shell model interaction matrix elements and quantify their uncertainties. Methods: Eigenvector continuation is used to emulate shell model calculations, reducing computational costs. The emulator enables Markov chain Monte Carlo sampling to optimize interaction matrix elements and rigorously assess parametric uncertainties. Here, the framework is benchmarked using the USDB interaction in the 𝑠𝑑 shell. Results: The emulator reproduces the USDB interaction with negligible error, validating its use in shell model fitting applications. However, we find that to obtain credible predictive intervals, the model defect of the shell model itself, rather than experimental or emulator error, must be taken into account in order to obtain credible uncertainties. Conclusions: The proposed framework provides an efficient and rigorous approach for fitting shell model interactions and quantifying uncertainties. Further, the normality assumption used in the past appears sufficient to describe the distribution of interaction matrix elements. However, it is crucial to account for model correlations to avoid underestimating uncertainties.
HOLISTIC CREDIBILITY ASSESSMENT OF A MACHINE LEARNING-BASED SURROGATE MODEL IN AN AERODYNAMICS APPLICATION
Elements of ASME V&V 20 credibility assessment methodology are used in tandem with credibility assessment tools from the machine learning community to assess the credibility of a deep neural network based surrogate model. This surrogate model is trained, tested, validated, and employed in the context of aerodynamic coefficient prediction for a NACA 0012 airfoil in subsonic and transonic flow. The parameter space is defined by angle of attack, Reynolds number, and Mach number.