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At least 775 records · Page 43

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DOE OSTI2024

Assessing the release, transport, and retention of radioactive aerosols from hypothetical breaches in spent fuel storage canisters

Interim dry storage of spent nuclear fuel involves storing the fuel in welded stainless-steel canisters. Under certain conditions, the canisters could be subjected to environments that may promote stress corrosion cracking leading to a risk of breach and release of aerosol-sized particulate from the interior of the canister to the external environment through the crack. Research is currently under way by several laboratories to better understand the formation and propagation of stress corrosion cracks, however little work has been done to quantitatively assess the potential aerosol release. The purpose of the present work is to introduce a reliable generic numerical model for prediction of aerosol transport, deposition, and plugging in leak paths similar to stress corrosion cracks, while accounting for potential plugging from particle deposition. The model is dynamic (changing leak path geometry due to plugging) and it relies on the numerical solution of the aerosol transport equation in one dimension using finite differences. The model’s capabilities were also incorporated into a Graphical User Interface (GUI) that was developed to enhance user accessibility. Model validation efforts presented in this paper compare the model’s predictions with recent experimental data from Sandia National Laboratories (SNL) and results available in literature. We expect this model to improve the accuracy of consequence assessments and reduce the uncertainty of radiological consequence estimations in the remote event of a through-wall breach in dry cask storage systems.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2025

Developing a robust strength model using physically-informed genetic programming

The strength of materials is influenced by a range of external conditions, such as temperature and deformation rate. Consequently, materials that demonstrate substantial variations in their mechanical behavior due to fluctuations in temperature and strain rate require complex strength models to accurately predict material performance in real-world applications. To predict such complex behavior, a robust and flexible strength model is necessary. In this work, we utilize genetic programming-based symbolic regression (GPSR) to develop data-driven strength models that accurately represent the measured stress–strain responses of tin across a wide range of strain, strain rate and temperature regimes. The GPSR models are constrained by physically-informed conditions, which leads to significant improvement in extrapolation. The best model is integrated into a multi-physics code to perform Taylor impact simulations, validating the model’s accuracy and robustness. In conclusion, the model predictions showed excellent agreement with experimental results, particularly when compared to predictions using traditional strength models.

Genetic programming↗

DOE OSTI2018

Kinetics calculation of fast periodic pulsed reactors using MCNP6

Fast periodic pulsed reactor is a type of reactor in which the fission bursts are formed entirely with external reactivity modulation with a specified time periodicity. This type of reactors could generate much larger intensity of neutron beams for experimental use, compared with the steady state reactors. In the design of fast periodic pulsed reactors, the time dependent simulation of the power pulse is majorly based on a point kinetic model, which is known to have limitations. A more accurate calculation method is desired for the design analyses of fast periodic pulsed reactors. Monte Carlo computer code MCNP6 is used for this task due to its three dimensional transport capability with a continuous energy library. Some new routines were added to simulate the rotation of the movable reflector parts in the time dependent calculation. Fast periodic pulsed reactor IBR-2M was utilized to validate the new routines. This reactor is periodically in prompt supercritical state, which lasts for similar to 400 mu s, during the equilibrium state. This generates long neutron fission chains, which requires tremendously large amount of computation time during Monte Carlo simulations. Russian Roulette was applied for these very long neutron chains in MCNP6 calculation, combined with other approaches to improve the efficiency of the simulations. In the power pulse of the IBR-2M at equilibrium state, there is some discrepancy between the experimental measurements and the calculated results using the point kinetics model. MCNP6 results matches better the experimental measurements, which shows the merit of using MCNP6 calculation relative to the point kinetics model.

Zhong, Z.↗

NASA NTRS2005

A Method for Assessing the Accuracy of a Photogrammetry System for Precision Deployable Structures

The measurement techniques used to validate analytical models of large deployable structures are an integral Part of the technology development process and must be precise and accurate. Photogrammetry and videogrammetry are viable, accurate, and unobtrusive methods for measuring such large Structures. Photogrammetry uses Software to determine the three-dimensional position of a target using camera images. Videogrammetry is based on the same principle, except a series of timed images are analyzed. This work addresses the accuracy of a digital photogrammetry system used for measurement of large, deployable space structures at JPL. First, photogrammetry tests are performed on a precision space truss test article, and the images are processed using Photomodeler software. The accuracy of the Photomodeler results is determined through, comparison with measurements of the test article taken by an external testing group using the VSTARS photogrammetry system. These two measurements are then compared with Australis photogrammetry software that simulates a measurement test to predict its accuracy. The software is then used to study how particular factors, such as camera resolution and placement, affect the system accuracy to help design the setup for the videogrammetry system that will offer the highest level of accuracy for measurement of deploying structures.

Moore, Ashley↗

DOE OSTI2025

Modeling a High-Temperature Electrochemically Driven Water-Gas-Shift Process Using a Mixed-Conducting Membrane without External Electrical Power

This paper develops a model to predict and interpret the performance of an elevated-temperature, electrochemical, membrane-assisted, water-gas-shift process. The process uses separated feed streams of H 2 O and CO to produce separated streams of H 2 and CO 2 , without an external electrical power source. The dense ceramic membrane is mixed ionic-electronic-conducting (MIEC) gadolinium-doped ceria (GDC) and the porous composite electrodes are Ni-YSZ. At elevated temperature, GDC conducts both oxygen ions and small polarons. The present process uses chemical potential to drive the process. Electrochemical oxidation of CO proceeds within the composite anode and H 2 O reduction proceeds within the composite cathode. At high temperature (e.g., T > 700 °C), GDC has significant electronic leakage in the form of a reduced-cerium small polaron, which supports the charge-transfer reactions. In a typical electrolyzer or fuel cell, this leakage is significantly problematic. However, the present process depends on the leakage current to complete the electrochemical circuit. Model development and validation is based on measured material properties and reactor performance. Potential applications include using CO-rich blast-furnace off gases in steel processing, producing separated streams of H 2 and CO 2 .

Zhu, Huayang↗

DOE OSTI2026

Amplified response of cavity-coupled quantum-critical systems

A quantum critical point develops when matter undergoes a continuous transformation between distinct ground states at absolute zero. It hosts pronounced quantum fluctuations, which render the system highly susceptible to external perturbations. While light-matter coupling has rapidly moved forward as a means to probe and control quantum materials, the capacity of quantum critical fluctuations in the photon-mediated responses has been largely unexplored. Here we advance the notion that directly coupling a quantum critical mode to a quantized cavity field dramatically facilitates the realization of the elusive superradiant phase transition in equilibrium, circumventing at once the key obstacles that have prevented its attainment in spite of decades of pursuit. The superradiant phase transition develops far below the ultrastrong regime of light-matter couplings, and the transition is accompanied by the light-matter hybrid system showing strongly enhanced intrinsic squeezing and amplified quantum Fisher information. We also identify candidate cavity quantum materials platforms for validating the proposed effect. Our findings suggest a general principle by which quantum criticality amplifies the response to cavity photons. They also demonstrate that cavity coupling accesses the elevated quantum entanglement of the underlying matter at quantum criticality, thereby pointing to a pathway towards realizing the potential of highly collective quantum materials to expand the capacities of quantum information science.

Sur, Shouvik [Rice Univ., Houston, TX (United Stat↗

NASA NTRSDate not supplied

An Initial Electric Motor Rotor Vibration Model

Ongoing integration of outrunner brushless electric motors into drones and Advanced Air Mobility aircraft presents a need for accurate acoustic predictions derived from prediction of the motor rotor vibrations. In outrunner motors, the external rotor vibrates and drives the acoustic field. At resonant frequencies of the rotor, the rotor displacements will be the largest. The vibrations can lead to acoustic tones that are relevant to the overall acoustic design of these types of vehicles. This study performs a finite element analysis to assess the modes in two electric motor rotors. This model is then refined into a simple parameterized geometry that can make the same predictions for motors of the same class. A parametric sweep and least-squares-curve fit to the finite element analysis data results in a series of simple curves that can predict the mode shapes and frequencies that are likely to appear in this class of motors without the need for any simulation. The simulations are validated by comparison to acoustic and experimental modal-analysis data.

Electric Motor Noise↗

NASA NTRSDate not supplied

An Initial Electric Motor Rotor Vibration Model

Electric Motor Noise↗

DOE OSTI2024

Multiple Pathways of Influence for Tightly and Loosely Structured Organizations: Implications for Systems Resilience

Organizations play a key role in supporting various societal functions, ranging from environmental governance to the manufacturing of goods. Here, the behaviors of organization are impacted by various influences, including information, technology, authority, economic leverage, historical experiences, and external factors, such as regulations. This paper introduces a generalized framework, focused on the relative structure of an organization (tight vs. loose), that can be used to understand how different influence pathways can impact decision-making within differently structured organizations. This generalized framework is then translated into a modeling and simulation platform to support and assess implications of these structural differences in resilience to disinformation (measured by organizational behaviors of timeliness and inclusion of quality information) using a systems dynamics approach Preliminary results indicate that a tightly structured organization may be less timely at processing information but could be more resilient against using poor quality information in organizational decisions compared to a loosely structured organization. Ongoing work is underway to understand the robustness of these findings and to validate current model design activities with empirical insights.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

NASA NTRS1997

Laser Shearographic Inspection for Debonds in Sprayed On Foam Insulation (SOFI)

Preliminary results of shearographic inspections of the test panels simulating the Space Shuttle's external tank (ET) spray on foam insulation (SOFI) are presented. Debonding of SOFI may introduce flight debris that may damage the orbiter's thermal protection system (TPS) exposing the orbiter (as well as the ET) to thermal loading. It is estimated that 90 percent of the TPS damage on the orbiter's 'belly' results from debonded SOFI during ascent. A series of test panels were fabricated, with programmed debonds of different geometries and sizes, to determine the sensitivity of shearography as a function of debond size, SOFI thickness,'and vacuum excitation. Results show that a Probability of Detection (POD) of 0.95 or better can be expected for debonds with a diameter equal to the SOFI thickness as less than 0.4-psi pressure reduction. More testing will be required to validate the laser shearography imaging process for certifying its use in nondestructive evaluation (NDE) of Space Shuttle space flight components.

Adams, F. W.↗

NASA NTRS2010

Full-Scale Crash Test of a MD-500 Helicopter with Deployable Energy Absorbers

A new externally deployable energy absorbing system was demonstrated during a full-scale crash test of an MD-500 helicopter. The deployable system is a honeycomb structure and utilizes composite materials in its construction. A set of two Deployable Energy Absorbers (DEAs) were fitted on the MD-500 helicopter for the full-scale crash demonstration. Four anthropomorphic dummy occupants were also used to assess human survivability. A demonstration test was performed at NASA Langley's Landing and Impact Research Facility (LandIR). The test involved impacting the helicopter on a concrete surface with combined forward and vertical velocity components of 40-ft/s and 26-ft/s, respectively. The objectives of the test were to evaluate the performance of the DEA concept under realistic crash conditions and to generate test data for validation of dynamic finite element simulations. Descriptions of this test as well as other component and full-scale tests leading to the helicopter test are discussed. Acceleration data from the anthropomorphic dummies showed that dynamic loads were successfully attenuated to within non-injurious levels. Moreover, the airframe itself survived the relatively severe impact and was retested to provide baseline data for comparison for cases with and without DEAs.

Kellas, Sotiris↗

DOE OSTI2019

Additive Manufacturing of Biomechanically Tailored Meshes for Compliant Wearable and Implantable Devices

Abstract Additive manufacturing (AM) of medical devices such as orthopedic implants and hearing aids is highly attractive because of the potential of AM to match the complex form and mechanics of individual human bodies. Externally worn and implantable tissue‐support devices, such as ankle or knee braces, and hernia repair mesh, offer a new opportunity for AM to mimic tissue‐like mechanics and improve both patient outcomes and comfort. Here, it is demonstrated how explicit programming of the toolpath in an extrusion AM process can enable new, flexible mesh materials having digitally tailored mechanical properties and geometry. Meshes are fabricated by extrusion of thermoplastics, optionally with continuous fiber reinforcement, using a continuous toolpath that tailors the elasticity of unit cells of the mesh via incorporation of slack and modulation of filament–filament bonding. It is shown how the tensile mesh mechanics can be engineered to match the nonlinear response of muscle. An ankle brace with directionally specific inversion stiffness arising from embedded mesh is validated, and further concepts for 3D mesh devices are prototyped.

Pattinson, Sebastian W.↗

DOE OSTI2023

Pool-Based Tow System for Testing Tethered Hydrokinetic Devices Being Developed to Harvest Energy From Ocean Currents

Abstract The immense potential for ocean current energy harvesting is being actively explored as the push for renewable energy becomes more urgent. This paper demonstrates a tow testing platform built to examine and validate mathematical models related to the performance of tethered, underwater, hydrokinetic devices in development to harvest energy from ocean currents, and presents experimental results illustrating how such a system can be used. The platform has been modularly designed to allow for the testing of various tethered, underwater energy-generation systems, including kite-based systems, coaxial turbines, and duct sails. Previous research on tethered energy-generating systems has primarily been focused on airborne systems. Additionally, the limited experimental research on tethered, underwater energy-generation systems has relied on a rigid rod for mechanical and electrical connections between the test articles and instrumentation. The tow testing platform presented in this paper accomplishes the mechanical and electrical connection through a dual-function tether, featuring internal conductors and an external sheath to support towing loads. The goal of this platform was to enable the emulation of ocean currents, which are largely unidirectional, and to retrofit a regular pool into a cost-effective, adaptable, small-scale tow tank test bed. The capabilities of the system include two-way communication with tethered devices, multiple towing profiles in order to emulate different flow regimes, real-time control, and differential velocities via dual winch operation.

Engineering↗

DOE OSTI2024

Myna

The additive manufacturing (AM) community has been developing digital factory tools over the past decade to better leverage the multi-modal process data coming out of the advanced manufacturing process. As a result, numerous databases of additive manufacturing process data exist in the literature and in the archival storage of disparate research groups. While some efforts have been made to create a standard ontology for storing and sharing AM data, in practice a variety of data structures are used to store AM build data, even within a single institution. This causes many problems for maintainability and extensibility when attempting to integrate computational modeling tools with experimental data to either validate models or to provide further insight into results and trends. Myna is a Python-based framework that aims to decrease the effort needed to connect individual computational models to the variety of AM process data that exist in different research groups and institutions. This type of software is sometimes referred to as "middleware" or “glueware,” in that it connects disparate databases and applications into a single computational ecosystem. Instead of maintaining unique interfaces between each application and each database, developers can create a single interface from each application to Myna and thereby gain access to the implemented database connections. Similarly, developing a database connection in Myna provides access to the developed simulation applications. This framework greatly simplifies the maintainability of model applications that rely on experimental data. Using external simulation tools, users will also be able to run pre-configured workflows using the built-in workflow manager. Several examples of input files are provided with Myna for different workflows, including melt pool geometry predictions and detailed melt pool and solidification microstructure predictions.

Knapp, GerryL. [Oak Ridge National Laboratory (ORN↗

DOE OSTI2019

Partition Density Functionals: Theory and Applications. Final Technical Report

Partition Density Functional Theory is a method to calculate the energy and density of a molecule via self-consistent calculations on isolated fragments. At the start of this project, Partition Density Functional Theory (PDFT) had only been applied to one-dimensional model systems of non-interacting electrons. Its most appealing feature (the reason why PDFT was born in the first place) was that it allowed one to construct an internally-consistent Density Functional Theory (DFT) valid for non-integer electron numbers to be used in the context of Chemical Reactivity Theory. Many formal properties of the quantities entering the theory, such as partition potentials, were unknown when the project started. The connections with other fragment-based electronic structure methods, and especially with embedding theories, were unclear, and the potential of PDFT for fixing problems of approximate exchange-correlation functionals was unanticipated. Supported by grant DE-SC0005031, we made progress in developing, understanding, implementing, and applying PDFT. We discovered its potential for applications in situations where approximate DFT fails, such as when stretching bonds or when calculating the energy of weakly-interacting systems, both cases of importance for energy research applications. We extended PDFT in several directions (spin-densities, current densities, external electric and magnetic fields), and carried out many calculations on diatomic molecules and small clusters to test ideas for approximate non-additive functionals. As a result, we were able to propose physically-motivated fragment-density approximations for both covalent and weak bonds. Because many applications will increasingly benefit from efficient and accurate electronic-structure calculations via density-embedding techniques, the research results enabled by this grant should prove useful for addressing complex problems in a wide variety of fields, from chemistry to molecular biology and materials engineering.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

BETO 2021 Peer Review - WBS 4.1.2.32: Bioeconomy Scenario Analysis

The Bioeconomy Scenario Analysis project uses systems thinking and analysis to assess current and/or prospective techno-economics, research and development, deployment strategies, policy, and market conditions and their impact on the potential development trajectories of the bioenergy industry over time. Results from this project include identification of opportunities and constraints to industrial development, quantification of multiple metrics (energy, economic, environmental) and informing researchers, decision makers, and industry of the steps needed for a sustainable, nationwide biofuels industry. Analyses from this project enable the creation of a bioenergy industry by (1) inciting policy-makers to explore scenarios for nationwide biofuels production, identifying policy actions consistent with pathways for growth; (2) improving industry’s understanding of industry growth potential under different technology and investment conditions, better targeting their development efforts; and (3) providing universities and other interested stakeholders with tools and analyses that can be adapted to meet research and teaching objectives, connecting students with careers that build the industry. One of the many modeling tools used in this project, the Biomass Scenario Model (BSM) is a publicly-available, unique, validated, state-of-the-art, award-winning, fourth-generation model of the domestic biofuels supply chain which explicitly focuses on how and under what conditions biofuel technologies might be deployed to contribute to the U.S. transportation energy sector. We use models like the BSM to examine the implications of policies and incentives as well as their potential side-effects. The BSM uses a system-dynamics simulation to model dynamic interactions and transitions across the supply chain; it tracks the deployment of biofuels given industrial learning and the reaction of the investment community in the context of land availability, projected oil markets, consumer demand for biofuels, and government policies over time. Under expected market conditions, analyses using the BSM suggest that the biofuels industry may require significant external actions in the early years to thrive. Interventions that accelerate the industrial learning process (e.g. operation of pre-commercial and commercial facilities) have been identified as having strong influence in starting the growth of a commercial biofuel industry. Policies which are coordinated across the whole supply chain in BSM foster the growth of the biofuels industry and production of tens of billions of gallons of biofuels may occur under sufficiently favorable conditions.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

NASA NTRS1998

Noninvasive measurement of pulsatile intracranial pressure using ultrasound

The present study was designed to validate our noninvasive ultrasonic technique (pulse phase locked loop: PPLL) for measuring intracranial pressure (ICP) waveforms. The technique is based upon detecting skull movements which are known to occur in conjunction with altered intracranial pressure. In bench model studies, PPLL output was highly correlated with changes in the distance between a transducer and a reflecting target (R2 = 0.977). In cadaver studies, transcranial distance was measured while pulsations of ICP (amplitudes of zero to 10 mmHg) were generated by rhythmic injections of saline. Frequency analyses (fast Fourier transformation) clearly demonstrate the correspondence between the PPLL output and ICP pulse cycles. Although theoretically there is a slight possibility that changes in the PPLL output are caused by changes in the ultrasonic velocity of brain tissue, the decreased amplitudes of the PPLL output as the external compression of the head was increased indicates that the PPLL output represents substantial skull movement associated with altered ICP. In conclusion, the ultrasound device has sufficient sensitivity to detect transcranial pulsations which occur in association with the cardiac cycle. Our technique makes it possible to analyze ICP waveforms noninvasively and will be helpful for understanding intracranial compliance and cerebrovascular circulation.

NASA Center ARC↗

NASA NTRSDate not supplied

Machine-learning Solution for Automatic Spacesuit Motion Recognition and Measurement from Conventional Video

Extravehicular Activity (EVA) spacesuits exhibit unique movement patterns due to their design characteristics. Mobility assessments using traditional motion capture systems are cost prohibitive and not feasible for some training conditions (e.g., simulated lunar outdoor terrain). This paper aims to present the ongoing development of machine learning solutions to quantify suit motions from conventional videos without special sensors or hardware. Preliminary work into this field was promising but given the fast growth in deep/machine learning technologies, external expertise was sought from open-source communities. Partnerships were formed with the NASA JSC Center of Excellence for Collaborative Innovation (CoCEI) and an execution crowdsourcing platform partner to solicit machine learning framework developments from external contenders. NASA provided contenders with images and video clips of spacesuits with simultaneously measured motion capture data during EVA simulation tasks. The contenders used this data to train and develop generalized algorithms to predict motions. At the end of the crowdsourcing event, the top five solutions were selected from 250 submissions. Each submission was tested and scored using video clips not previously disclosed to the contenders. The weighted scoring metrics measured how well the algorithm detected the suit shape, the 2D suit joint detection accuracy, and 3D joint detection accuracy. The winning solution was able to achieve roughly 85% prediction accuracy. Overall, the algorithms could efficiently detect various types of spacesuits and motions across different EVA environments such as the NASA Active Response Gravity Offload System (ARGOS). After continued improvements and validation, the fully developed system will enable EVA stakeholders to quantify suit kinematic patterns, which can help optimize suit, hardware, and task designs.

Linh Vu↗