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At least 865 records · Page 48
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Computational Fluid Dynamics Simulation of the Swordfish Oxygen/Methane Rotating Detonation Rocket Engine

Rotating Detonation Rocket Engines (RDREs) provide several theoretical performance benefits over traditional deflagration combustion rocket engines. RDREs can potentially generate higher specific impulse (ISP) for a given propellant combination enabling significant consumable mass savings for a spaceflight vehicle. Conversely, RDREs are a relatively new technology with a shallower analytical modeling base compared to traditional combustion engine architectures. In this work, we utilize time-accurate, Computational Fluid Dynamics (CFD) modeling to simulate the complex fluid environment inside an RDRE combustion chamber and propellant manifolds. The selected engine of study is the Swordfish RDRE which was developed and tested and at the National Aeronautics and Space Administration (NASA) Marshall Space Flight Center (MSFC). CFD simulations were conducted using the as-tested Swordfish geometry and conditions to facilitate comparison between the analytical predictions and experimental results.

Brian R. Richardson↗
NASA NTRS2024

Spacecraft Priming Analysis and Research Test Apparatus: Number 1 (SPARTAN 1), Test and Analysis Results

Spacecraft with Earth-storable propellants are required by range safety to launch with propellant isolated from the thrusters for ground operations, which is often accomplished by placing a pyrotechnic, or a latching isolation valve between the tank and the thrusters. Once on-orbit, downstream lines are vented out to space through the thrusters and are left evacuated and at vacuum pressure. Propellant isolation valve then opens and floods the lines with high velocity propellant which can lead to a significant pressure surge upon filling. Replicating this event during ground testing using water as a propellant simulant has always been difficult and costly to accurately perform due to the low vacuum pressure targeted on the downstream side of the system. This report describes the Spacecraft Priming Analysis and Research Test Apparatus (SPARTA) at Marshall Space Flight Center’s (MSFC) Component Development Area (CDA) and the initial test series meant to be a pathfinder for construction methods and test procedures to reduce the cost of future testing. The test data collected are critical to analytical models as the details to replicate prior ground tests are often lacking in enough detail to adequately model the test that was conducted. This report also describes the Thermal Desktop/FloCAD analysis that was performed alongside the test series. The test methods defined for this campaign showed a dramatic improvement on heritage test procedures. Test pace increased due to faster drying and pulling vacuum more effectively. Results generated in this test matched analytical predictions very well and provide a releasable set of test data to be leveraged on future NASA and commercial partner spacecraft development programs.

spacecraft↗
NASA NTRSDate not supplied

Experimental Setup for Mechanically Testing Subscale Triangular, Rollable, and Collapsible Deployable Composite Booms

High-strain composite deployable space structures are used for space infrastructure and science applications such as solar array supports, antennae, camera masts, and lightweight structures supporting solar sailing propulsion ele-ments. Triangular, Rollable, and Collapsible (TRAC) deployable composite booms are one example of a high-strain composite deployable structure and were studied using novel experimental test and characterization methods developed under the Gravity Offloading and Analysis of Long Imperfection-sensitive Ele-ments (GOALIE) project. In the present work, a subscale 7-m-long TRAC boom was suspended vertically to orient gravity along the length of the boom. By ori-enting vertically, highly nonlinear and unstable behavior often encountered dur-ing horizontally oriented gravity offload testing of similar structures was reduced. Pretest analytical predictions of TRAC booms indicated three unique failure modes, loads, and locations for three unique loading cases of in-plane bending, out-of-plane bending, and axial compression. To investigate the predicted behav-ior, an experimental test was set up to impart mechanical loads to a subscale TRAC boom. The experimental setup, loading cases, and instrumentation used to characterize the mechanical response of a subscale TRAC boom are described in this paper.

High-strain composites↗
NASA NTRSDate not supplied

Quantum Leap: Evaluating the Feasibility of Quantum Machine Learning Using NASA Earth Observational Data

This study explores the feasibility of leveraging quantum machine learning (QML) to analyze NASA Earth Observational (EO) data for climate change research, with a particular focus on the phenomenon of ”crop frosting” which has become more prevalent due to climate change. We implemented and evaluated two QML models, the Variational Quantum Classifier (VQC) and Quantum Support Vector Classifier (QSVC), in both simulated and real quantum computing environments using a 127 qubit IBM quantum processor. Our study emphasizes the scientific rigor in comparing these quantum models with a classical Support Vector Machine (SVM) classifier, highlighting their performance in processing climate data. The results offer valuable insights into the potential scientific advantages, limitations, and scalability of QML for analyzing EO datasets, thus paving the way for more advanced climate modeling and predictive analytics using quantum computing. We showcased how Environmental Interaction Knowledge Graphs (EIKGs) and Digital Twins (DTs) can be integrated into this study. This research underscores the transformative potential of Classical and QML leveraging KGs and DT to address the multifaceted challenges posed by climate change.

Quantum Computing↗
NASA NTRSDate not supplied

Objective Structured Clinical Evaluation (OSCE) of an Artificial Intelligence (AI) Clinical Decision Support System (CDSS) Tool

BACKGROUND Objective Structured Clinical Evaluations (OSCEs) have long been established as a robust methodology for summative assessment of clinical skills and decision-making during medical education. The recent integration of Artificial Intelligence (AI) into clinical decision-making processes has prompted the need for novel evaluation frameworks to assess the efficacy and reliability of AI clinical decision support system (CDSS) tools. This abstract outlines the process of quantitatively evaluating a novel CDSS (“Doc in a Box” Google 2024) trained on curated medical spaceflight data in the psychomotor domain as it interfaces with a human volunteer acting as the crew medical officer (CMO). PURPOSE The AI CDSS under review was developed as part of the Lunar Command and Control Interoperability (LuCCI) project, which is intended to address a gap in how Lunar Surface Systems (LSS) would interoperate across multiple programs, commercial partners, and international partners. The project objective is to define, prototype, integrate, and evaluate an interoperable lunar command, control, data, and software reference architecture to enable autonomy and informatics capability through common standards across LSS. A multi-modal AI-based CDSS compatible with Federated LSS will assist clinicians in diagnosing and managing complex medical conditions by providing evidence-based recommendations through predictive analytics. Given the critical role of decision-support as NASA continues to evolve its Earth-independent medical operations (EIMO), it is imperative to ensure that such AI tools perform reliably and align with clinical standards during progressive lunar and Martian exploration class missions. METHODS The OSCE framework, traditionally used for evaluating human clinicians, was adapted to assess the AI tool's decision-making capabilities in simulated clinical scenarios. In this adapted OSCE, the AI CDSS was tested across a series of structured clinical scenarios designed to mimic real-life spaceflight patient cases. These scenarios included a range of conditions and complexities, allowing for comprehensive assessment of the tool's performance. Key evaluation metrics included accuracy of diagnosis, timeliness of decision-making, and appropriate recommendations for therapies. The OSCE was scored by human physician evaluators who assessed the AI's recommendations in comparison with expert clinicians' medical decision making to ensure alignment with best practices and the standard of care. RESULTS Preliminary results indicate that the AI CDSS demonstrated high accuracy in diagnostic recommendations and decision support across various scenarios. However, certain limitations were noted, such as occasional discrepancies in handling complex or nuanced cases that required a more contextual understanding. Additionally, the tool scored higher on the diagnostic portion of the rubric, with lower scores in the therapeutic recommendations. These findings highlight the importance of continuous refinement and validation of AI tools through rigorous evaluation frameworks like the OSCE. The adaptation of OSCEs for AI tools presents several advantages, including a structured and reproducible approach to evaluation, the ability to test AI systems in diverse clinical scenarios, and the opportunity to benchmark AI performance against established clinical standards to permit charting of future progress as aerospace medicine evolves as a discipline. Remaining challenges include ensuring that these evaluations capture the full spectrum of clinical decision-making scenarios that will be confronted by CMOs during missions and adequately reflecting real-world variability of the austere spaceflight environment. CONCLUSION Employing OSCEs to evaluate AI clinical decision support tools offers a promising approach to validating their clinical utility and efficacy. This methodology not only provides insights into the tool's performance but also fosters ongoing improvement and alignment with standard of care practices. Future research should focus on refining these evaluation processes and addressing limitations to enhance the integration of AI tools in clinical spaceflight settings. REFERENCES Scott S, Hearns V, Barker MA. Testing Clinical Skills: A Look at the OSCE and USMLE Clinical Skills Exams. S D Med. 2019 Oct;72(10):451-453. Majumder MAA, Kumar A, Krishnamurthy K, Ojeh N, Adams OP, Sa B. An evaluative study of objective structured clinical examination (OSCE): students and examiners perspectives. Adv Med Educ Pract. 2019 Jun 5;10:387-397. Karam VY, Park YS, Tekian A, Youssef N. Evaluating the validity evidence of an OSCE: results from a new medical school. BMC Med Educ. 2018 Dec 20;18(1):313.

Ariana M Nelson↗
NASA NTRSDate not supplied

Experimental Setup for Mechanically Testing Subscale Triangular, Rollable, and Collapsible Deployable Composite Booms

High-strain composite deployable space structures are used for space infrastructure and science applications such as solar array supports, antennae, camera masts, and lightweight structures supporting solar sailing propulsion elements. Triangular, Rollable, and Collapsible (TRAC) deployable composite booms are one example of a high-strain composite deployable structure and were studied using novel experimental test and characterization methods developed under the Gravity Offloading and Analysis of Long Imperfection-sensitive Elements (GOALIE) project. In the present work, a subscale 7-m-long TRAC boom was suspended vertically to orient gravity along the length of the boom. By orienting vertically, highly nonlinear and unstable behavior often encountered during horizontally oriented gravity offload testing of similar structures was reduced. Pretest analytical predictions of TRAC booms indicated three unique failure modes, loads, and locations for three unique loading cases of in-plane bending, out-of-plane bending, and axial compression. To investigate the predicted behavior, an experimental test was set up to impart mechanical loads to a subscale TRAC boom. The experimental setup, loading cases, and instrumentation used to characterize the mechanical response of a subscale TRAC boom are described in this paper.

Experimental testing↗
DOE OSTI2012

Tiny Bubbles in my BEC

Ultracold atomic gases provide a unique way for exploring many-body quantum phenomena that are inaccessible to conventional low-temperature experiments. Nearly two decades ago the Bose-Einstein condensate (BEC) - an ultracold gas of bosons in which almost all bosons occupy the same single-particle state - became experimentally feasible. Because a BEC exhibits superfluid properties, it can provide insights into the behavior of low-temperature helium liquids. We describe the case of a single distinguishable atom (an impurity) embedded in a BEC and strongly coupled to the BEC bosons. Depending on the strength of impurity-boson and boson-boson interactions, the impurity self-localizes into two fundamentally distinct regimes. The impurity atom can behave as a tightly localized 'polaron,' akin to an electron in a dielectric crystal, or as a 'bubble,' an analog to an electron bubble in superfluid helium. We obtain the ground state wavefunctions of the impurity and BEC by numerically solving the two coupled Gross-Pitaevskii equations that characterize the system. We employ the methods of imaginary time propagation and conjugate gradient descent. By appropriately varying the impurity-boson and boson-boson interaction strengths, we focus on the polaron to bubble crossover. Our results confirm analytical predictions for the polaron limit and uncover properties of the bubble regime. With these results we characterize the polaron to bubble crossover. We also summarize our findings in a phase diagram of the BEC-impurity system, which can be used as a guide in future experiments.

36 MATERIALS SCIENCE↗
DOE OSTI2013

A Study of Turbulence-Driven Inward Momentum Flux & Construction of a Difference Scheme for Fokker-Planck-Landau Operator

Momentum transport driven by microinstability is studied via analytic theories, gyrokinetic simulations, and experimental data analysis. A scenario for rotation profile evolution is constructed based on experimental observation that parallel flow initiates at edge region and penetrates into core region of tokamak [1]. In particular, turbulent diffusion and inward convective pinch are studied according to this scenario. For study of convective momentum pinch, toroidal ion temperature gradient mode near marginal stability is examined in kinetic limit. It is found from quasilinear estimation that the inward turbulent equipartition momentum pinch remains as the most robust part of pinch. In addition, it is found that ion temperature gradient driven momentum pinch is inward for typical parameters, while ion density gradient driven momentum pinch is outward. It is shown by theoretical formulas and experimental data analysis that momentum pinch velocity is sensitive to the electron to ion temperature ratio. For study of diffusive momentum transport, parallel shear flow instability is studied in fluid limit. Diffusion coefficient using mixing length estimate from nonlocal theory reveals that it has a strong dependence on the parallel flow shear and is mainly carried by fluctuations in short wavelength regime. Gyrokinetic simulation of collisionless parallel shear flow instability shows that the analytic prediction of diffusion coefficient is comparable to numerical values in the linear phase of the simulations. In the nonlinear phase, fluctuation energy gets transferred to the long wavelength regime. A two-dimensional, uniform velocity-grid based solver for the nonlinear Fokker-Planck-Landau (FPL) collision operator has been developed in the limit of strong magnetic field. The conservative and entropy increasing semidiscretized numerical scheme for the isotropic FPL equation by C. Buet et al. (2002) has been extended to 2D velocity space. A Picard fixed point method is used for semi-implicit time advance. One time evaluation of interpolation coefficients for probability distribution function is introduced so that numerical equilibrium is achieved with Maxwellian. However, positivity property is sacrificed at the saving of computational costs. In addition, a highly practical method is suggested to apply the velocity-grid based collision solver to particle-in-cell code.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2018

ATF Transient Prescription Tests in TREAT

EXECUTIVE SUMMARY The Transient Reactor Test facility (TREAT) was constructed in the late 1950’s and provided thousands of transient irradiations before being placed in standby mode in 1994. In 2017, it resumed operation in order to reclaim its crucial role in nuclear-heated safety research. TREAT is a transient reactor where inherently-safe core physics, a nimble transient rod drive system, and a philosophy of continual facility improvement work together to enable flexible power maneuvers for fuel safety research. While the facility’s flexible design and multi-mission nature saw historic experiments for numerous transient types, TREAT was not specifically adapted to optimize or demonstrate its full performance capability for Light Water Reactor (LWR) postulated accidents including Hot Zero Power Reactivity Initiated Accidents (HZP-RIA) and Loss of Coolant Accidents (LOCA). The physics of HZP-RIA drive very brief pulses with fairly large energy excursions. TREAT is currently capable of approaching HZP-RIA pulse widths through transients initiated on a large step insertion of reactivity and terminated shortly thereafter by rapid re-insertion of the transient rods (“clipping”). LOCAs are postulated to occur quite differently, starting from normal power operations followed by a long period of lower power decay heat. TREAT is able to simulate LOCA events with an initial flattop transient for tens of seconds, followed by a sizeable power reduction, to a longer segment where specimen fission heating represents internal decay heat generation. Two reactor physics testing campaigns were undertaken to address the HZP-RIA type transients, neither of which had been performed in any great measure historically to address data gaps in the timing, repeatability of clipping and effect of dynamic transient rod motions on core-to-specimen fission power coupling. The first campaign, referred to as the Accident Tolerant Fuel (ATF) transient prescription tests, employed dosimeters in the core to characterize the effect of rod motions on specimen power coupling for clipped, unclipped, and low-level steady state operations each with approximately the same moderate core energy release. This campaign was accompanied by efforts to measure dosimetry and compare results to analytic predictions. The other HZP-RIA campaign, referred to as Narrow Pulse Width (NPW) transient prescriptions, employed higher step insertions with increased core energy release to demonstrate TREAT’s capability in achieving the narrowest-possible pulse width. Additionally, a series of LOCA transient prescriptions were also performed to demonstrate how well TREAT could perform long-duration shaped transients. Both NPW and LOCA transient prescriptions did not include dosimeters but used existing plant power instrumentation to produce transient power data. All three transient prescription campaigns were successfully carried out in TREAT. The ATF-3 transient prescriptions showed that TREAT can perform clipped transients with remarkable repeatability. Measurement and modeling both showed that the power coupling in small, fissile dosimeters does not change by more than 8% between clipped, unclipped, and steady state runs while uncertainty sources in both the modeling and measurement methods were identified and found to be on the order of 20% in total. Overall, the ATF-3 transient prescription tests were successful in determining repeatability and consistency of dosimeter power coupling, developing processes for modeling and measuring this crucial parameter, and demonstrating the need for continued efforts in transient prescription work at TREAT in support of future experiment design and post test data interpretation. The NPW and LOCA transient prescriptions were also successfully performed to exhibit TREAT’s capability for these important LWR accident categories. The NPW transients showed pulse widths of ~90 ms, which were the narrowest ever achieved in TREAT to date and relevant for the upper end range of HZP-RIA simulation. This effort provided crucial data for calibrating kinetic models to be used in enhanced pulse-narrowing strategies in upcoming irradiations. Similarly, The LOCA transient prescriptions showed that TREAT can simulate the needed nuclear heating and event time scales for LOCA fuel safety research and provided essential data for future experiment design.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Integrated Risk-Informed Condition Based Maintenance Capability and Automated Platform: Technical Report 3

This project is a collaborative research effort between PKMJ Technical Services LLC, Idaho National Laboratory, and Public Service Enterprise Group (PSEG) Nuclear, LLC. The collaboration, led by PKMJ Technical Services LLC, is part of the industry Funding Opportunity Announcement (FOA) award under Advanced Nuclear Technology Development FOA #DE-FOA-0001817. The pilot demonstration focuses on the Circulating Water System (CWS), an important non-safety-related system that impacts the power generation capability of the plant site. Achieving riskinformed condition-based Predictive Maintenance (PdM) on the CWS will result in significant economic benefits, and the developed methodologies can also be applied to other plant systems. This approach supports an industry goal of ensuring that nuclear power generation remains a viable, economically competitive option in the energy market. Operation and Maintenance (O&M) costs include labor-intensive Preventive Maintenance (PM) programs that involve manually performed inspection, calibration, testing, and maintenance of plant assets at periodic frequencies as well as time-based replacement of assets, irrespective of condition. This project offers an alternative by focusing on riskinformed condition-based maintenance to reduce O&M costs while still maintaining plant health and safety. This report summarizes the progress made toward achieving a risk-informed condition-based maintenance approach. The research and development (R&D) activities presented in this report are associated with development of a nuclear digital platform application, integration of fault signature models, and automated work management processes. The fault signatures and Machine Learning (ML) models are key components in predictive analytics and are heavily leveraged to improve the insights received by existing plant process data sources. Availability of the analysis results within a centralized digital platform enhances efficiency by enabling automation of activities otherwise performed manually. Personnel are presented with enhanced information that can be used to evaluate plant status and risks. Utilizing the enhancements to data analytics supports automated responses, (i.e. issuance of work orders) to address developing equipment faults and thus preventing forced, unplanned shutdowns of components or systems. The R&D activities described within this report lay the foundation for developing and demonstrating a digital automated platform to centralize the implementation of condition monitoring and response to equipment faults. The digital automated platform is cloud-based and designed to enable improved efficiency of plant processes. The digital platform includes content related to maintenance optimization, fault signature analysis, and plant records, which can all be used to support efficiencies when located within a centralized digital platform. These efficiencies could be further enhanced when deployed through industry-wide deployment of the technology to improve insights and processes based upon economies of scale.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2016

Seismic and LOCA safety testing and analysis program for Westinghouse PWR fuel under end of life conditions

The NRC issued Information Notice - IN 2012-09 in June 2012 which challenges approved assumptions based on the beginning of life (BOL) conditions in seismic and LOCA analysis. Westinghouse manufactures a variety of PWR fuel designs, including 14*14, 15*15, 16*16 and 17*17 array, also different fuel lengths from 12 feet to 14 feet. The fuels are supplied to the cores designed by Westinghouse and Combustion Engineering, and other cores around world. To address IN 2012-09 efficiently and economically, Westinghouse and PWR Owner Groups launched a testing and analysis program funded by PWROG. The program planed testing and analysis matrices based on types of fuel designs. The testing plan includes grid crush tests, fuel assembly mechanical tests and flowing water damping tests. Applying modelling technique, the program will reduce the number of test and cost. The ultimate goal of the program is to generate fuel assembly EOL models for all fuel designs manufactured by Westinghouse and to be ready for any plant specific seismic and LOCA analysis to address NRC IN for EOL effect. The phase I of PWROG for EOL conditions has been completed and several conclusions are obtained. First, the gapped grids reduce grid dynamic stiffness, local impact stiffness and crush strength. Also, due to gapped grids, both the fuel assembly natural frequency and stiffness are reduced. Secondly, applying higher fuel assembly damping due to the flowing water effect can significantly reduce fuel assembly impact forces. However, during a seismic event the reactor coolant pumps may trip resulting in a coast-down. As such, reduced flow rates that occur during the pump coast-down must be considered. Thirdly, the analytical model representation of a reactor core adequately characterizes the core response under seismic and LOCA excitations. Static and dynamic structural test results of a fuel assembly compared with analytical predictions indicate that the fuel assembly lateral and axial structural behavior can be fully determined with finite element models. Fourthly, analyses for EOL fuel assemblies under seismic and LOCA loads demonstrate EOL effect and flowing water damping effect. With flowing water damping benefit, significant margin can be recovered for fuel assemblies with EOL conditions and under seismic loads.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

Sockeye Heat Pipe Analysis Code Verification and Validation

Some of the most promising microreactor designs currently under development utilize heat pipe technology to transfer heat from the reactor core to the secondary side heat exchanger, due to the technology’s compactness, efficiency, passivity, and reliability. Sockeye is an engineering-scale heat pipe tool developed under the Nuclear Energy Advanced Modeling and Simulation Program to be used for the design and safety analysis of microreactors. Sockeye’s core capability lies in a 1D, two-phase, compressible flow model, used to simulate the working fluid inside the heat pipe. Sockeye is built on the Multiphysics Object-Oriented Simulation Environment framework, which allows for seamless multiphysics coupling with other Nuclear Energy Advanced Modeling and Simulation tools and can thus be used in a full-scale simulation of a microreactor assembly, which can include hundreds of heat pipes. This paper presents some initial verification and validation assessments performed for Sockeye. We demonstrate good agreement between Sockeye’s numerical results and steady-state analytic solutions for velocity and pressure drop, with differences attributable to the underlying assumptions made by the analytic solutions. We also show that Sockeye reproduces analytic predictions of key operational limits, such as the capillary limit and the sonic limit. Finally, we compare Sockeye results to experimental data for the SAFE-30 heat pipe module test.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

Dynamically suppressing cavity dephasing induced by frequency fluctuations of a coupled nonlinear mode

High-coherence superconducting cavities offer a promising platform for quantum information, with long coherence times and negligible intrinsic dephasing. However, cavity control generally relies on nonlinear Josephson elements whose frequency fluctuations are inherited by the cavity as dephasing, potentially limiting control fidelities and eroding the noise bias used in error-correction protocols. Here, we introduce Stark-Assisted Flux-noise Evasion (SAFE), a hardware-efficient protocol that protects the cavity from inherited dephasing using only a weak off-resonant microwave drive applied to the nonlinear element. As a concrete setup, we analyze a 3D superconducting cavity dispersively coupled to a flux-tunable transmon (FTT) subject to $1/f$ flux noise. Analytical predictions are confirmed by Monte Carlo simulations with realistic parameters, which show that SAFE can extend the cavity dephasing time by more than an order of magnitude while keeping residual drive-induced decoherence subdominant.

Lu, Yunwei [Northwestern U.] (ORCID:00000003401756↗
NASA NTRS1974

Evaluation of analytical procedures for prediction of turbulent boundary layers on a porous wall

An analytical study has been made to determine how well current boundary layer prediction techniques work when there is mass transfer normal to the wall. The data that were considered in this investigation were for two-dimensional, incompressible, turbulent boundary layers with suction and blowing. Some of the bleed data were taken in an adverse pressure gradient. An integral prediction method was used three different porous wall skin friction relations, in addition to a solid-surface relation for the suction cases. A numerical prediction method was also used. Comparisons were made between theoretical and experimental skin friction coefficients, displacement and momentum thicknesses, and velocity profiles. The integral method with one of the porous wall skin friction laws gave very good agreement with data for most of the cases considered. The use of the solid-surface skin friction law caused the integral to overpredict the effectiveness of the bleed. The numerical techniques also worked well for most of the cases.

Towne, C. E.↗
DOE OSTI2014

Predicting Student Success using Analytics in Course Learning Management Systems

Educational data analytics is an emerging discipline, concerned with developing methods for exploring the unique types of data that come from the educational context. For example, predicting college student performance is crucial for both the student and educational institutions. It can support timely intervention to prevent students from failing a course, increasing efficacy of advising functions, and improving course completion rate. In this paper, we present the efforts carried out at Oak Ridge National Laboratory (ORNL) toward conducting predictive analytics to academic data collected from 2009 through 2013 and available in one of the most commonly used learning management systems, called Moodle. First, we have identified the data features useful for predicting student outcomes such as students scores in homework assignments, quizzes, exams, in addition to their activities in discussion forums and their total GPA at the same term they enrolled in the course. Then, Logistic Regression and Neural Network predictive models are used to identify students as early as possible that are in danger of failing the course they are currently enrolled in. These models compute the likelihood of any given student failing (or passing) the current course. Numerical results are presented to evaluate and compare the performance of the developed models and their predictive accuracy.

Educational data mining↗
NASA NTRS1979

An analytical technique for predicting the characteristics of a flexible wing equipped with an active flutter-suppression system and comparison with wind-tunnel data

An analytical technique for predicting the performance of an active flutter-suppression system is presented. This technique is based on the use of an interpolating function to approximate the unsteady aerodynamics. The resulting equations are formulated in terms of linear, ordinary differential equations with constant coefficients. This technique is then applied to an aeroelastic model wing equipped with an active flutter-suppression system. Comparisons between wind-tunnel data and analysis are presented for the wing both with and without active flutter suppression. Results indicate that the wing flutter characteristics without flutter suppression can be predicted very well but that a more adequate model of wind-tunnel turbulence is required when the active flutter-suppression system is used.

Abel, I.↗
DOE OSTI2021

Data analytics approach to predict high-temperature cyclic oxidation kinetics of NiCr-based Alloys

Abstract Although of practical importance, there is no established modeling framework to accurately predict high-temperature cyclic oxidation kinetics of multi-component alloys due to the inherent complexity. We present a data analytics approach to predict the oxidation rate constant of NiCr-based alloys as a function of composition and temperature with a highly consistent and well-curated experimental dataset. Two characteristic oxidation models, i.e., a simple parabolic law and a statistical cyclic oxidation model, have been chosen to numerically represent the high-temperature oxidation kinetics of commercial and model NiCr-based alloys. We have successfully trained machine learning (ML) models using highly ranked key input features identified by correlation analysis to accurately predict experimental parabolic rate constants ( k p ). This study demonstrates the potential of ML approaches to predict oxidation kinetics of alloys over wide composition and temperature ranges. This approach can also serve as a basis for introducing more physically meaningful ML input features to predict the comprehensive cyclic oxidation behavior of multi-component high-temperature alloys with proper constraints based on the known underlying mechanisms.

36 MATERIALS SCIENCE↗