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At least 973 records · Page 54

Comparative Assessment of Experimental Testing of Instrument with an Embedded Digital Device Using Model-Based and Conventional Methods

The use of digital equipment has not been widespread in U.S. nuclear facilities. A major contributing factor to this situation arises from regulatory concerns about common cause failures (CCFs) stemming from the use of identical software in redundant systems, questions as to how to quantify the reliability of software-based products, validity of tools that are used for software verification and validation (V&V), and the effectiveness of software QA procedures. Compounding the concerns are sporadic incidents of digital equipment malfunctions in nuclear power plants, including lockups resulting from software memory leaks, feedwater control malfunctions due to excessive traffic on Ethernet networks, software logic errors, and other problems leading to plant trips. Additionally, the limited amount of demonstrated research and a lack of industry consensus on quantitative software reliability methodologies has hindered the widespread adoption of digital I&C in the nuclear industry. In a recent Regulatory Issue Summary (RIS), the U.S. Nuclear Regulatory Commission (NRC) identified concerns about the impact of greater use of instrumentation and control (I&C) equipment with an embedded digital device (EDD) [1]. Specifically, the NRC staff states that increased use of such devices “may increase a facility’s vulnerability to a CCF” (i.e., common-cause failure). The prevailing NRC guidance regarding software CCF (SCCF) identifies two design attributes that are acceptable for eliminating CCF concerns: (1) diversity or (2) testability (specifically, 100% testability). Either solution can result in high costs and remaining licensing uncertainty (i.e., how much diversity is enough? how to ensure test coverage of every possible sequence of device states?). Consequently, many utilities and reactor designers have limited or avoided more extensive use of digital technology to minimize licensing, scheduling, and financial risk. Without development of cost effective qualification methods to satisfy regulatory requirements and address the potential for CCF vulnerability associated with EDDs, the nuclear power industry may not be able to realize the benefits of digital technology achieved by other industries. In order to address these challenges, the U.S. Department of Energy (DOE) is sponsoring this research to assess the prospect of CCF in digital I&C equipment. The purpose of the current research is to develop an effective approach employing science-based methods to resolve concerns about CCF vulnerability that serve to inhibit deployment of advanced instrumentation (e.g., sensors, actuators, microcontrollers) with EDDs in nuclear power applications. The research objectives address the challenge of establishing high levels of safety and reliability assurance needed for the qualification of EDDs (e.g., microprocessors, programmable logic devices) that are subject to software design faults, complex failure modes, and CCF vulnerability. Specific objectives are: (1) assess the regulatory context for treatment of CCF vulnerability a graded approach to their qualification, (3) develop and extend model-based testing methods to enable effective demonstration of whether devices are subject to CCF, which may arise from vulnerabilities introduced at any stage of the design lifecycle, (4) establish a cost-effective testing framework that incorporates automation and test scenario prioritization, and (5) demonstrate the qualification approach through selection and testing of candidate digital device(s). This report documents an assessment of the results from experimental testing of a representative instrument with an embedded digital device. The experiment serves as a proof-of-concept demonstration of a model-based testing (MBT) framework. The objective of MBT is to ensure that an EDD undergoes suitably comprehensive testing to establish that it is not subject to SCCF. The approach by which MBT accomplishes this objective is through development and application of an effective test suite that provides the appropriate coverage to detect the full range of postulated faults that may arise at the requirements, design, and code (implementation) level of the EDD software. The findings of the experiment involve the application of the MBT framework by Ohio State University (OSU) through testing of the selected demonstration instrument (i.e., the prototype smart pressure sensor developed by Virginia Commonwealth University, VCU). In addition, the experiment findings also involve application of a more conventional black-box testing approach that serves as a baseline against which the MBT methodology can be compared. The primary outcome documented in this report is the comparative analysis of the capabilities demonstrated for each method. The results of the analysis demonstrate clear benefits that arise from the MBT methodology. The comparison indicates greater effectiveness from the more comprehensive evidence available through MBT and enhanced efficiency achieved through automation within the MBT framework. The structure of the report addresses the approach and application of each test method as well as the comparative analysis of the experimental results. Chapter 2 gives a summary overview of the demonstration approach. Chapter 3 covers the baseline testing and Chapter 4 documents the model-based testing. Chapter 5 describes the findings of the comparative analysis and presents the conclusions that can be drawn about the effectiveness and efficiency of the MBT methodology.

47 OTHER INSTRUMENTATION↗

Validation and parameterization of a novel physics-constrained neural dynamics model applied to turbulent fluid flow

We report, in fluid physics, data-driven models to enhance or accelerate time to solution are becoming increasingly popular for many application domains, such as alternatives to turbulence closures, system surrogates, or for new physics discovery. In the context of reduced order models of high-dimensional time-dependent fluid systems, machine learning methods grant the benefit of automated learning from data, but the burden of a model lies on its reduced-order representation of both the fluid state and physical dynamics. In this work, we build a physics-constrained, data-driven reduced order model for Navier–Stokes equations to approximate spatiotemporal fluid dynamics in the canonical case of isotropic turbulence in a triply periodic box. The model design choices mimic numerical and physical constraints by, for example, implicitly enforcing the incompressibility constraint and utilizing continuous neural ordinary differential equations for tracking the evolution of the governing differential equation. We demonstrate this technique on a three-dimensional, moderate Reynolds number turbulent fluid flow. In assessing the statistical quality and characteristics of the machine-learned model through rigorous diagnostic tests, we find that our model is capable of reconstructing the dynamics of the flow over large integral timescales, favoring accuracy at the larger length scales. More significantly, comprehensive diagnostics suggest that physically interpretable model parameters, corresponding to the representations of the fluid state and dynamics, have attributable and quantifiable impact on the quality of the model predictions and computational complexity.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Validation & Verification of Electrical Components B2 Test Facility

The research focus of this project is to assist in the closure of Measurement, Monitoring and Control System (MMCS) and other electrical requirements in support of the B2 Space Launch System (SLS) Core Stage Green Run Test Project. Alongside this goal I am to understand project management tools to analyze and control activities/tasks associated with those items. The project I am working on will assist electrical engineers in developing and or identifying closure rationale for the MMCS and electrical requirements. Also as serving the role of a training project manager, I am to develop and maintain a method for tracking progress with estimate completion dates specifically identifying those items during this performance window. The methods I used in order to perform the research consisted of worddocuments, excel sheets, and pdf documents needed for review. For example, documents consisted of: a SLS Core Stage Green Run Facility Requirement Document (FRD) identifying the SSC MMCS and electrical requirements, a Stage Controller to SSC Interface Control Document (ICD) identifying the SSC requirements, and the B2 SLS Core Stage Green Run Test project System Requirements Document (SRD) which identifies the MMCS and electrical requirements. The files were sent to me by both mentors, Mr. Barry Robinson and Ms. Dawn Davis. Overall, the review process for the word documents and excel spreadsheets proved to be successful. The data for the electrical components were accurate and were consistent with the original recorded data. However, the consistency with the pdf documents did not follow up all the way. Attention to this mistake was made and further revisions were done in order for the data to agree with each other. Furthermore, an itinerary was designed using Microsoft Outlook in order to track progress with estimated completion dates. This project contributes to NASA/Center Missions and Goals through the Waterfall Model. The Waterfall Model is a linear system used for engineering design. In the Waterfall Model, the fourth step is Verification and Validation. This involves installation, testing, and debugging of the B2 SLS Core Stage electrical components. For the SLS Core Stage Green Run Test Project, each requirement contained in this approved requirements set will have at least one Verification Item (VI) assigned to it. During the design phase, VIs will mostly consist of Analysis or Inspection types. Design phase VIs and closure information will be documented in Dynamics Data Management System (DDMS) in the form of analysis reports and design documentation.

Bastian, Tyler↗

Analytical Large-Signal Modeling of Inverter-Based Microgrids With Koopman Operator Theory for Autonomous Control

The microgrid (MG) plays a crucial role in the energy transition, but its nonlinearity presents a significant challenge for large-signal power systems studies in the electromagnetic transient (EMT) time scale. In this paper, we develop a large-signal linear MG model that considers the detailed dynamics of the primary and zero-control levels based on the Koopman operator (KO) theory. Firstly, a set of observable functions is carefully designed to capture the nonlinear dynamics of the MG. The corresponding linear KO is then analytically derived based on these observables, resulting in the linear representation of the original nonlinear MG with observables as the new coordinate. The influence of external input on the system dynamics is also considered during the derivation, enabling control of the MG. We solve the voltage control problem using the traditional linear quadratic integrator (LQI) method to demonstrate that textbook linear control techniques can accurately control the original nonlinear MG via the developed KO-linearized MG model. Our proposed KO linearization method is generic and can be easily extended for different control objectives and MG structures using our analytical derivation procedure. Here, we validate the effectiveness of our methodology through various case studies.

25 ENERGY STORAGE↗

Revisiting matrix-based inversion of scanning mobility particle sizer (SMPS) and humidified tandem differential mobility analyzer (HTDMA) data

Abstract. Tikhonov regularization is a tool for reducing noise amplification during data inversion. This work introduces RegularizationTools.jl, a general-purpose software package for applying Tikhonov regularization to data. The package implements well-established numerical algorithms and is suitable for systems of up to ∼ 1000 equations. Included is an abstraction to systematically categorize specific inversion configurations and their associated hyperparameters. A generic interface translates arbitrary linear forward models defined by a computer function into the corresponding design matrix. This obviates the need to explicitly write out and discretize the Fredholm integral equation, thus facilitating fast prototyping of new regularization schemes associated with measurement techniques. Example applications include the inversion involving data from scanning mobility particle sizers (SMPSs) and humidified tandem differential mobility analyzers (HTDMAs). Inversion of SMPS size distributions reported in this work builds upon the freely available software DifferentialMobilityAnalyzers.jl. The speed of inversion is improved by a factor of ∼ 200, now requiring between 2 and 5 ms per SMPS scan when using 120 size bins. Previously reported occasional failure to converge to a valid solution is reduced by switching from the L-curve method to generalized cross-validation as the metric to search for the optimal regularization parameter. Higher-order inversions resulting in smooth, denoised reconstructions of size distributions are now included in DifferentialMobilityAnalyzers.jl. This work also demonstrates that an SMPS-style matrix-based inversion can be applied to find the growth factor frequency distribution from raw HTDMA data while also accounting for multiply charged particles. The outcome of the aerosol-related inversion methods is showcased by inverting multi-week SMPS and HTDMA datasets from ground-based observations, including SMPS data obtained at Bodega Marine Laboratory during the CalWater 2/ACAPEX campaign and co-located SMPS and HTDMA data collected at the US Department of Energy observatory located at the Southern Great Plains site in Oklahoma, USA. Results show that the proposed approaches are suitable for unsupervised, nonparametric inversion of large-scale datasets as well as inversion in real time during data acquisition on low-cost reduced-instruction-set architectures used in single-board computers. The included software implementation of Tikhonov regularization is freely available, general, and domain-independent and thus can be applied to many other inverse problems arising in atmospheric measurement techniques and beyond.

54 ENVIRONMENTAL SCIENCES↗

Mechanically fastened composite laminates subjected to combined bearing-bypass and shear loading

Bolts and rivets provide a means of load transfer in the construction of aircraft. However, they give rise to stress concentrations and are often the source and location of static and fatigue failures. Furthermore, fastener holes are prone to cracks during take-off and landing. These cracks present the most common origin of structural failures in aircraft. Therefore, accurate determination of the contact stresses associated with such loaded holes in mechanically fastened joints is essential to reliable strength evaluation and failure prediction. As the laminate is subjected to loading, the contact region, whose extent is not known, develops between the fastener and the hole boundary through this contact region, which consists of slip and no-slip zones due to friction. The presence of the unknown contact stress distribution over the contact region between the pin and the composite laminate, material anisotropy, friction between the pin and the laminate, pin-hole clearance, combined bearing-bypass and shear loading, and finite geometry of the laminate result in a complex non-linear problem. In the case of bearing-bypass loading in compression, this non-linear problem is further complicated by the presence of dual contact regions. Previous research concerning the analysis of mechanical joints subjected to combined bearing-bypass and shear loading is non-existent. In the case of bearing-bypass loading only, except for the study conducted by Naik and Crews (1991), others employed the concept of superposition which is not valid for this non-linear problem. Naik and Crews applied a linear finite element analysis with conditions along the pin-hole contact region specified as displacement constraint equations. The major shortcoming of this method is that the variation of the contract region as a function of the applied load should be known a priori. Also, their analysis is limited to symmetric geometry and material systems, and frictionless boundary conditions. Since the contact stress distribution and the contact region are not known a priori, they did not directly impose the boundary conditions appropriate for modelling the contact and on-contact regions between the fastener and the hole. Furthermore, finite element analysis is not suitable for iterative design calculations for optimizing laminate construction in the presence of fasteners under complex loading conditions. In this study, the solution method developed by Madenci and Ileri (1992a,b) has been extended to determine the contact stresses in mechanical joints under combined bearing-bypass and shear loading, and bearing-bypass loading in compression resulting in dual contact regions.

Madenci, Erdogan↗

Application of the Mixed-Mode Model for Numerical Simulation of Pearlitic Transformation

The multiscale model of pearlitic transformation, including the finite element solution of the second Fick’s equation with moving boundary in the microscale and Fourier equation in the macroscale, is presented in this paper. According to the mixed-mode approach, both the volume diffusion and the interface mobility were considered. Model describes sidewise and frontal growth of cementite and ferrite plates in a single grain of the austenite. Assessment of the possibility of the developed model application to determine the key parameters in terms of strength properties of pearlitic steel, i.e., pearlite grain size and colony size as well as interlamellar spacing for various cooling conditions, was the main aim of this work. The model was validated and verified on the basis of experimental tests performed for two eutectoid steels. In practice, developed model can support design process for a technology of high-strength rods and long products manufacturing. Rails were selected as a case study in this work, and therefore, numerical simulations of accelerated cooling of the rail head were performed and the relationship between the parameters of heat treatment, parameters of the structure and properties of the finished product was determined on the basis of obtained results.

36 MATERIALS SCIENCE↗

Development and Validation of an Interactive Liner Design and Impedance Modeling Tool

The Interactive Liner Impedance Analysis and Design (ILIAD) tool is a LabVIEW-based software package used to design the composite surface impedance of a series of small-diameter quarter-wavelength resonators incorporating variable depth and sharp bends. Such structures are useful for packaging broadband acoustic liners into constrained spaces for turbofan engine noise control applications. ILIAD s graphical user interface allows the acoustic channel geometry to be drawn in the liner volume while the surface impedance and absorption coefficient calculations are updated in real-time. A one-dimensional transmission line model serves as the basis for the impedance calculation and can be applied to many liner configurations. Experimentally, tonal and broadband acoustic data were acquired in the NASA Langley Normal Incidence Tube over the frequency range of 500 to 3000 Hz at 120 and 140 dB SPL. Normalized impedance spectra were measured using the Two-Microphone Method for the various combinations of channel configurations. Comparisons between the computed and measured impedances show excellent agreement for broadband liners comprised of multiple, variable-depth channels. The software can be used to design arrays of resonators that can be packaged into complex geometries heretofore unsuitable for effective acoustic treatment.

Howerton, Brian M.↗

High-throughput protein characterization by complementation using DNA barcoded fragment libraries

Abstract Our ability to predict, control, or design biological function is fundamentally limited by poorly annotated gene function. This can be particularly challenging in non-model systems. Accordingly, there is motivation for new high-throughput methods for accurate functional annotation. Here, we used co mplementation of aux otrophs and DNA barcode seq uencing (Coaux-Seq) to enable high-throughput characterization of protein function. Fragment libraries from eleven genetically diverse bacteria were tested in twenty different auxotrophic strains of Escherichia coli to identify genes that complement missing biochemical activity. We recovered 41% of expected hits, with effectiveness ranging per source genome, and observed success even with distant E. coli relatives like Bacillus subtilis and Bacteroides thetaiotaomicron . Coaux-Seq provided the first experimental validation for 53 proteins, of which 11 are less than 40% identical to an experimentally characterized protein. Among the unexpected function identified was a sulfate uptake transporter, an O-succinylhomoserine sulfhydrylase for methionine synthesis, and an aminotransferase. We also identified instances of cross-feeding wherein protein overexpression and nearby non-auxotrophic strains enabled growth. Altogether, Coaux-Seq’s utility is demonstrated, with future applications in ecology, health, and engineering.

59 BASIC BIOLOGICAL SCIENCES↗

Ray-tracing image simulations of transparent objects with complex shape and inhomogeneous refractive index

Optical images of transparent three-dimensional objects can be different from a replica of the object’s cross section in the image plane, due to refraction at the surface or in the body of the object. Simulations of the object’s image are thus needed for the visualization and validation of physical models. We report ray tracing image simulations that achieved high physical fidelity, reproducing optical behaviors and image features not rendered in previous studies. We replicated brightfield microscopy images of drops with complex shapes, and images of pressure and shock waves traveling inside them. For high physical fidelity, the simulations must replicate the spatial and angular distribution of illumination rays, and both the experiment and the simulation must be designed for accurate optical modeling. The simulations are highly sensitive to the properties of the drops and can be used to diagnose and refine fluid dynamics models. The simulated images can also be optimized to extract multiple 3D properties from experimental images. Compared to specialized single-shot 3D imaging methods, this approach has the advantage that it preserves the experimental simplicity, the high resolution, and the visual interpretability characteristic to basic optical imaging. The techniques introduced here are directly applicable to optical microscopy, so they can be used in other fields, such as microfluidics and biology, to expand the type and the accuracy of three-dimensional information that can be extracted from basic optical images.

Cavitation↗

Online Remote Sensing Interface

BasinTools Module 1 processes remotely sensed raster data, including multi- and hyper-spectral data products, via a Web site with no downloads and no plug-ins required. The interface provides standardized algorithms designed so that a user with little or no remote-sensing experience can use the site. This Web-based approach reduces the amount of software, hardware, and computing power necessary to perform the specified analyses. Access to imagery and derived products is enterprise-level and controlled. Because the user never takes possession of the imagery, the licensing of the data is greatly simplified. BasinTools takes the "just-in-time" inventory control model from commercial manufacturing and applies it to remotely-sensed data. Products are created and delivered on-the-fly with no human intervention, even for casual users. Well-defined procedures can be combined in different ways to extend verified and validated methods in order to derive new remote-sensing products, which improves efficiency in any well-defined geospatial domain. Remote-sensing products produced in BasinTools are self-documenting, allowing procedures to be independently verified or peer-reviewed. The software can be used enterprise-wide to conduct low-level remote sensing, viewing, sharing, and manipulating of image data without the need for desktop applications.

Lawhead, Joel↗

Thermal Hydraulics Validation Activities in the ART-GCR Campaign

The Advanced Reactor Technologies - Gas Cooled Reactor Campaign (ART-GCR) is part of the United States Department of Energy - Office of Nuclear Energy's Advanced Reactor Technologies program aimed at developing a High Temperature Gas-cooled Reactor (HTGR) which will offer enhancements in safety and efficiency. The Design, Methods, and Validation arm of the ART-GCR program provides experience and advanced tools for HTGR design and analysis. The Methods and Validation arm is developing data to validate predictions of decay heat removal through an extensive experimental campaign the Natural Convection Shutdown Heat Removal Test Facility at Argonne National Laboratory. In-core thermal hydraulics validation is being facilitated through the OECD/NEA's Thermal Hydraulic Code Validation Benchmark for High Temperature Gas-Cooled Reactors using HTTF Data. That benchmark contains code-to-code and code-to-data comparisons for 3 sets of HTGR thermal hydraulics phenomena. This ongoing benchmark activity has 16 participants from 9 countries developing leading insights into HTGR thermal hydraulics code validation. The ART-GCR campaign is also working on the development of state-of-the-art MOOSE-based models of the High Temperature Engineering Test Reactor (HTTR). Through the OECD/NEA's HTTR Loss of Forced Cooling (LOFC) program, the ART-GCR campaign is developing a multiphysics transient code validation benchmark based on 3 HTTR experiments that will provide an opportunity for international collaboration on multiphysics code validation.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

HHL algorithm with mapping function and enhanced sampling for model predictive control in microgrids

Here, this paper presents a refined quantum Harrow Hassidim Lloyd (HHL) algorithm for microgrid control. The first novelty of the developed method is that a mapping shift function enables the original HHL algorithm to handle general linear equations with non-singular and indefinite matrix. Second, a method of Matrix Extension for Amplifying Sampling Probabilities of Intended Solution (ME-ASPI) is proposed to design the reformulated linear algebraic equations, allowing for improved sampling efficiency of the quantum tomography in the refined HHL algorithm. Then, we applied the method to solve the model predictive control (MPC) problem in nonlinear dynamical microgrids. Specifically, with the ME-ASPI method, the refined HHL algorithm can effectively obtain the intended partial optimal control inputs for MPC. The optimization of quadratic programming problem in each time step of MPC is transformed into a linear system problem, which is addressed by the proposed quantum solver through using only partial information, with the time complexity improved from $\mathscr{O}(\mathscr{N}^{2.37286})$ classically to $\mathscr{O}(\mathscr{N}^{2} log \mathscr{N}$ x $p$ log $p)$ in quantum. Numerical examples have validated the effectiveness of the refined HHL algorithm with the proposed mapping function and the ME-ASPI method. By leveraging quantum properties, the proposed method provides a hybrid quantum–classical framework for microgrid control. This generic method can also potentially tackle many other challenges in analyzing and controlling general complex engineered systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Final Technical Report Wireless Microsensors System for Monitoring Deep Subsurface Operations

This final technical report describes the main findings of the project Wireless Microsensors System for Monitoring Deep Subsurface Operations (FE0031850). The project was part of the U.S. Department of Energy National Energy Technology Laboratory FOA 1998 program to develop new sensor systems for direct observation of parameters associated with CO2 injection and to provide data collection without being disruptive to operations. The overall DOE program was aimed at developing and validating innovative transformational sensor systems, amenable for integration with autonomous intelligent monitoring systems, that are capable of being deployed within the casing annulus and do not have casing perforation or wires/cables in the annulus for installation, power supply, or data transmission needs. Project accomplishments included 1) design and fabrication of a wireless downhole sensor system to monitor parameters for CO2 storage, 2) field testing of the sensor system in two legacy oil & gas wells, and 3) development of an analysis approach that validates the measurements and demonstrates the application of the technology to depict CO2 movement in the subsurface. The project leveraged new sensor technologies along with specialized wellbore telemetry, deployment, and analysis methods designed to address the challenges and risks related to CO2 storage in the subsurface. Results from field testing were a mixture of successes and challenges. The temperature sensor rings, installation procedures in legacy oil & gas wells, wireless powering demonstration, automated data collection, and material compatibility were successful. The wireless data transfer through cement to the wellhead via the sensor relays was not functional beyond the first relay. Consequently, work in the last year of the project included some additional testing of data transmission through different materials along with modeling and analysis of field data for CO2 monitoring applications. This work suggested there are options like polymer cements and open hole annuli that may allow point-to-point transmission along the borehole. The techno-economic analysis suggests that the sensor system is ~40% less expensive than fiber optic distributed temperature system. Modeling of CO2 storage applications suggests temperature can provide an indicator of CO2 saturation but would be best combined with pressure sensors.

47 OTHER INSTRUMENTATION↗

Spaceflight Holography Investigation in a Virtual Apparatus

The movement of a particle in a fluid is one of the most fundamental processes in physics and plays an important role in materials science. For example, the physics of crystal growth from a nucleation site in solution can be dominated by movement of the solution over the crystal surface. Gravity usually dominates the equations of motion, but in microgravity other terms can dominate, making the equation much more complex. Until recently, the equations were solved only by numerical methods and/or by neglecting terms. During this study, we discovered an exact solution to the equations, which shows that the usually neglected terms become extremely important in microgravity. We also developed diagnostic recording methods using holography to save all of the particle field data, allowing the experiment to essentially be transferred from space back to earth in what we call the virtual apparatus . We will record holograms of particle distributions in motion in microgravity and bring them back to earth for analysis, allowing the study of the full three-dimensional motion of sets of particles, allowing us to test the new analytical solutions. The experiment will also provide accurate measurements of the quasi-steady acceleration of the space platform and other interesting microgravity and g-jitter effects. This program will produce the flight definition for an experiment in the microgravity environment of space to validate the theoretical model. We will design an experiment with the help of the theoretical model that is optimized for testing the model, measuring g, g-jitter, and other microgravity phenomena.

Source record↗

Prediction of coronary artery disease in patients undergoing operations for mitral valve degeneration

OBJECTIVES: We sought to develop and validate a model that estimates the risk of obstructive coronary artery disease in patients undergoing operations for mitral valve degeneration and to demonstrate its potential clinical utility. METHODS: A total of 722 patients (67% men; age, 61 +/- 12 years) without a history of myocardial infarction, ischemic electrocardiographic changes, or angina who underwent routine coronary angiography before mitral valve prolapse operations between 1989 and 1996 were analyzed. A bootstrap-validated logistic regression model on the basis of clinical risk factors was developed to identify low-risk (< or =5%) patients. Obstructive coronary atherosclerosis was defined as 50% or more luminal narrowing in one or more major epicardial vessels, as determined by means of coronary angiography. RESULTS: One hundred thirty-nine (19%) patients had obstructive coronary atherosclerosis. Independent predictors of coronary artery disease include age, male sex, hypertension, diabetes mellitus,and hyperlipidemia. Two hundred twenty patients were designated as low risk according to the logistic model. Of these patients, only 3 (1.3%) had single-vessel disease, and none had multivessel disease. The model showed good discrimination, with an area under the receiver-operating characteristic curve of 0.84. Cost analysis indicated that application of this model could safely eliminate 30% of coronary angiograms, corresponding to cost savings of $430,000 per 1000 patients without missing any case of high-risk coronary artery disease. CONCLUSION: A model with standard clinical predictors can reliably estimate the prevalence of obstructive coronary atherosclerosis in patients undergoing mitral valve prolapse operations. This model can identify low-risk patients in whom routine preoperative angiography may be safely avoided.

Non-NASA Center↗

Spherical Coordinate Systems for Streamlining Suited Mobility Analysis

Introduction: When describing human motion, biomechanists generally report joint angles in terms of Euler angle rotation sequences. However, there are known limitations in using this method to describe complex motions such as the shoulder joint during a baseball pitch. Euler angle notation uses a series of three rotations about an axis where each rotation is dependent upon the preceding rotation. As such, the Euler angles need to be regarded as a set to get accurate angle information. Unfortunately, it is often difficult to visualize and understand these complex motion representations. It has been shown that using a spherical coordinate system allows Anthropometry and Biomechanics Facility (ABF) personnel to increase their ability to transmit important human mobility data to engineers, in a format that is readily understandable and directly translatable to their design efforts. Objectives: The goal of this project was to use innovative analysis and visualization techniques to aid in the examination and comprehension of complex motions. Methods: This project consisted of a series of small sub‐projects, meant to validate and verify a new method before it was implemented in the ABF's data analysis practices. A mechanical test rig was built and tracked in 3D using an optical motion capture system. Its position and orientation were reported in both Euler and spherical reference systems. In the second phase of the project, the ABF estimated the error inherent in a spherical coordinate system, and evaluated how this error would vary within the reference frame. This stage also involved expanding a kinematic model of the shoulder to include the rest of the joints of the body. The third stage of the project involved creating visualization methods to assist in interpreting motion in a spherical frame. These visualization methods will be incorporated in a tool to evaluate a database of suited mobility data, which is currently in development. Results: Initial results demonstrated that a spherical coordinate system is helpful in describing and visualizing the motion of a space suit. The system is particularly useful in describing the motion of the shoulder, where multiple degrees of freedom can lead to very complex motion paths.

Benson, Elizabeth↗

State Machine Modeling of the Space Launch System Solid Rocket Boosters

The Space Launch System is a Shuttle-derived heavy-lift vehicle currently in development to serve as NASA's premiere launch vehicle for space exploration. The Space Launch System is a multistage rocket with two Solid Rocket Boosters and multiple payloads, including the Multi-Purpose Crew Vehicle. Planned Space Launch System destinations include near-Earth asteroids, the Moon, Mars, and Lagrange points. The Space Launch System is a complex system with many subsystems, requiring considerable systems engineering and integration. To this end, state machine analysis offers a method to support engineering and operational e orts, identify and avert undesirable or potentially hazardous system states, and evaluate system requirements. Finite State Machines model a system as a finite number of states, with transitions between states controlled by state-based and event-based logic. State machines are a useful tool for understanding complex system behaviors and evaluating "what-if" scenarios. This work contributes to a state machine model of the Space Launch System developed at NASA Ames Research Center. The Space Launch System Solid Rocket Booster avionics and ignition subsystems are modeled using MATLAB/Stateflow software. This model is integrated into a larger model of Space Launch System avionics used for verification and validation of Space Launch System operating procedures and design requirements. This includes testing both nominal and o -nominal system states and command sequences.

model-based systems engineering↗