Theory of Intermittent Cutting. 4. Interpretation of Empirical Data Regarding Tool Exit from the Blank
Empirical observations of tool exit from the blank are interpreted on the basis of the model developed.
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Results for “engine simulation”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Determining the Tolerances in Fitting for Joints with Interference
A formula for the theoretical tolerance in fitting is derived by analysis of the components in the model of parametric failure for joints with interference. The formula takes account of the life of the joint and the specified probability of fault-free operation. It is found that selection of the fit without a margin of precision does not ensure the necessary reliability of the joint, while correct selection of the margin of precision extends the fault-free operation of the joint.
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A Hybrid Multi-Scale Model of Crystal Plasticity for Handling Stress Concentrations
Microstructural effects become important at regions of stress concentrators such as notches, cracks and contact surfaces. A multiscale model is presented that efficiently captures microstructural details at such critical regions. The approach is based on a multiresolution mesh that includes an explicit microstructure representation at critical regions where stresses are localized. At regions farther away from the stress concentration, a reduced order model that statistically captures the effect of the microstructure is employed. The statistical model is based on a finite element representation of the orientation distribution function (ODF). As an illustrative example, we have applied the multiscaling method to compute the stress intensity factor K I around the crack tip in a wedge-opening load specimen. The approach is verified with an analytical solution within linear elasticity approximation and is then extended to allow modeling of microstructural effects on crack tip plasticity.
36 MATERIALS SCIENCE↗
The Straightening of a River Meander Leads to Extensive Losses in Flow Complexity and Ecosystem Services
To assist river restoration efforts we need to slow the rate of river degradation. This study provides a detailed explanation of the hydraulic complexity loss when a meandering river is straightened in order to motivate the protection of river channel curvature. We used computational fluid dynamics (CFD) modeling to document the difference in flow dynamics in nine simulations with channel curvature (C) degrading from a well-established tight meander bend (C = 0.77) to a straight channel without curvature (C = 0). To control for covariates and slow the rate of loss to hydraulic complexity, each of the nine-channel realizations had equivalent bedform topography. The analyzed hydraulic variables included the flow surface elevation, streamwise and transverse unit discharge, flow velocity at streamwise, transverse, and vertical directions, bed shear stress, stream function, and the vertical hyporheic flux rates at the channel bed. The loss of hydraulic complexity occurred gradually when initially straightening the channel from C = 0.77 to C = 0.33 (i.e., the radius of the channel is three-times the channel width), and additional straightening incurred rapid losses to hydraulic complexity. Other studies have shown hydraulic complexity provides important riverine habitat and is positively correlated with biodiversity. This study demonstrates how hydraulic complexity can be gradually and then rapidly lost when unwinding a river, and hopefully will serve as a cautionary tale.
54 ENVIRONMENTAL SCIENCES↗
Method for controlling start-up and steady state performance of a closed split flow recompression brayton cycle
A method of resolving a balanced condition that generates control parameters for start-up and steady state operating points and various component and cycle performances for a closed split flow recompression cycle system. The method provides for improved control of a Brayton cycle thermal to electrical power conversion system. The method may also be used for system design, operational simulation and/or parameter prediction.
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TABULATED EQUIVALENT SDR FLAMELET (TESF) MODEFL
The code consists of an implementation of a novel tabulated combustion model for non-premixed flames in CFD solvers. This novel technique/model is used to implement an unsteady flamelet tabulation without using progress variables for non-premixed flames. It also has the capability to include history effects which is unique within tabulated flamelet models. The flamelet table generation code can be run in parallel to generate tables with large chemistry mechanisms in relatively short wall clock times. The combustion model/code reads these tables. This framework can be coupled with any CFD solver with RANS as well as LES turbulence models. This framework enables CFD solvers to run large chemistry mechanisms with large number of grids at relatively lower computational costs. Currently it has been coupled with the Converge CFD code and validated against available experimental data. This model can be used to simulate non-premixed combustion in a variety of applications like reciprocating engines, gas turbines and industrial burners operating over a wide range of fuels.
KUNDU, PRITHWISH↗
Additive Manufacturing Simulator (AMS)
Explore the source record for details and available documents.
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TABULATED EQUIVALENT SDR FLAMELET (TESF)
The code consists of an implementation of a novel tabulated combustion model for non-premixed flames in CFD solvers. This novel technique/model is used to implement an unsteady flamelet tabulation without using progress variables for non-premixed flames. It also has the capability to include history effects which is unique within tabulated flamelet models. The flamelet table generation code can be run in parallel to generate tables with large chemistry mechanisms in relatively short wall clock times. The combustion model/code reads these tables. This framework can be coupled with any CFD solver with RANS as well as LES turbulence models. This framework enables CFD solvers to run large chemistry mechanisms with large number of grids at relatively lower computational costs. Currently it has been coupled with the Converge CFD code and validated against available experimental data. This model can be used to simulate non-premixed combustion in a variety of applications like reciprocating engines, gas turbines and industrial burners operating over a wide range of fuels.
Kundu, Prithwish↗
Parametric spline “mesh” generation for nuclear engineering
Explore the source record for details and available documents.
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Theory of Carbon Dioxide Absorption by Hanford Waste - 18208
Hanford nuclear waste has a very high pH, and Hanford tanks are ventilated with air. Air has CO{sub 2(g)} in it, which is an acid, so it has some affinity for the waste. The absorption of CO{sub 2} by the waste is important because CO{sub 2} absorption consumes hydroxide at the liquid-air interface, and the hydroxide is important for inhibiting tank corrosion. NaOH is periodically added to some tanks in order to mitigate the surface acidification. The NaOH added then becomes part of the waste and must be treated as waste, increasing the cost of the mission. The Hobbs Equation, developed at the Savannah River site, is used at Hanford to predict CO{sub 2} absorption from the tank ventilation system. In this study, the Hobbs Equation functional form is theoretically evaluated from thermodynamic calculations of CO{sub 2} absorption, and diffusion rates in the waste surface. This study theoretically justifies the empirical equation reported by Hobbs. Thermodynamic calculations performed using the Environmental Simulation Program (ESP) software on a typical double-shell tank waste composition indicate that essentially 100 % of CO{sub 2} that contacts the waste will react with the waste whenever the pH is above 10. In the 1990's, a substantial amount of data was collected on the concentration of CO{sub 2} in the off-gas of ventilated double-shell tanks at Hanford. This historic data was mined in order to determine the quantity of CO{sub 2} absorbed by the waste. The results of this data mining activity determined that tanks below approximately pH 10 (i.e., tank 241-AN-107) will show limited CO{sub 2} absorption, consistent with both the Hobbs model and the theory developed here. Two other tank with higher pH showed contrasting CO{sub 2} absorption. One showed substantial CO{sub 2} absorption, and the other showed minimal CO{sub 2} absorption despite the high waste pH in one tank, presumably because there was minimal contact between the waste surface and most of the air flow. (authors)
12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
Modeling PWR systems with a unique framework for hybrid energy systems
Hybrid energy system (HES) is used to utilize the wind, solar, nuclear and other energy sources. Within the study and design of a nuclear power plant and HES, extensive system modeling is necessary to determine how the reactor is going to perform in any given situation, not only in the normal performance of the reactor but also transients including unanticipated transients without scram and hypothetical accidents. A modelling tool that is capable of solving governing equations of mass, momentum and energy for two-phase application is necessary to model the coolant systems of HES. Therefore, this study shows the development of a new coupling tool that is capable of modelling several components of HES and experimental validation of the model. For the initial development phase, the primary and secondary coolant systems (which use several components similar to the components of HES) are modelled by using this new tool. Code-to-code benchmark is also used for the performance evaluation of the new tool. It is observed that there is a good agreement between the new tool and RELAP5 predictions. (authors)
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Critical Heat Flux Model Improvement in CTF for Natural Circulation Type Reactors
The objective of this study was to enhance the departure from nucleate boiling (DNB) modeling capabilities of the subchannel analysis code CTF. The intent was to include consideration for PWR-type reactors which are characterized by relatively low subchannel mass flux and high inlet subcooling during normal operation. Identifying a CHF model appropriate for these type of conditions is required for an accurate thermal-hydraulics performance analysis. Several CHF models that are available in open literature, including those already implemented in CTF, were studied for their applicability. This includes the CHF models by Westinghouse (W-3), Electric Power Research Institute (EPRI-1), Biasi, Bowring, and Groeneveld. Since the models were developed within a certain validity range of operating conditions (mass flux, equilibrium quality, pressure, hydraulic diameter, and others), these ranges were used as a measure of acceptability. It was found in these considerations that the Groeneveld and Bowring models were the most appropriate. Therefore, the models by Bowring and Groeneveld were selected for implementation in CTF. (authors)
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Modeling the Molten Salt Reactor Experiment with the RELAP5-3D code
The Molten Salt Reactor Experiment (MSRE) is a liquid-fueled, graphite-moderated, thermal reactor that was operated at Oak Ridge National Laboratory (ORNL) between 1965 and 1969 at a power of ∼8 MWt (thermal). The fuel (as enriched UF{sub 4}) was dissolved in the coolant, a fluoride liquid salt. In the MSRE, the fuel and the coolant were together in the same fluid-the molten salt. The objective of this effort is to modernize and recapture dynamic modeling capability for molten salt reactors. As part of this effort, the MSRE has been modeled with the code RELAP5-3D. This paper presents calculated results and compares them to available data.
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Final report presentation - Memory compute gap project
This is the final presentation we provided to our program director, Hal Finkel. He was quite impressed with our progress and results. This is considered as the final report of the project.
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High Fidelity Simulation and Validation of Crossflow through a Tube Bundle and the Onset of Vibration
Flow induced vibrations can be detrimental to all manner of engineering applications with fluid flow. Heat exchangers with bundles of thin tubes experiencing a crossflow are especially susceptible to the unexpected onset of vibration. Heat-exchanger design necessarily involves extensive modeling and testing to ensure that significant vibrations cannot develop for any expected flow conditions. A properly validated numerical simulation can work in conjunction with physical experiments to identify problematic vibrations and allow for rapid iteration of design at relatively low expense. A high-fidelity fluid-structure interaction code has been developed by fully coupling CFD LES/DNS code Nek5000 and CSM code Diablo. The coupled code is used to simulate crossflow through a tube bundle in a geometry recreated after a physical experiment. Validation against this experiment involves comparing the amplitude and frequency spectrum for three different flow velocities. The velocities compared straddle the onset of large magnitude vibrations. The simulation accurately captures the onset of the vibrations with a marginally lower predicted frequency of vibration. When the onset velocity is compensated for the difference in natural frequency, the simulation results closely match the experiment. The continuous nature of the simulation measurements helps illustrate the fluid mechanics behind the pin motion and reveals the front to back propagation of the vibrations as the fluid velocity increases.
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AI-Enabled Discovery and Physics-Based Optimization of Energy Efficient Processing Strategies for Advanced Turbine Alloys (Final Technical Report)
In this project, the multi-organizational team of academic and industrial researchers from the University of Kentucky an aerospace and energy generation OEM partner has leveraged novel Digital Process Twin (DPT) models of process/structure interactions (i.e., process-induced surface integrity) to advance a paradigm of fully integrated computational materials engineering (ICME). Using efficient process models as the core of a digital process simulator for a reinforcement learning algorithm, the team has integrated industrial data and metrics of structure/performance/energy relationships and manufacturing-related energy metrics to optimize dynamic processing parameters for significantly improved life-cycle energy efficiency of advanced γ-TiAl low-pressure turbine (LPT) alloys, as indicated by a set of design relevant parameters (e.g., residual stresses and scrap rate). The key objective and anticipated outcome of the project was at least a 10% reduction in life-cycle embodied energy for a recently developed, γ-TiAl low-pressure turbine (LPT) alloy and nickel-based superalloy Inconel 718, through the adoption of the proposed AI-enabled process optimization approach. The final project outcomes significantly exceeded this original target, realizing manufacturing-related energy efficiency improvements of more than 130% for TiAl and up to 80% for Inconel 718. Rather than following the prevailing and highly inefficient empirical paradigm, the proposed study demonstrated the feasibility of adopting a digital, physics-based process design and optimization paradigm. The recurring need for manual intervention, rework, reinspection causes significant production bottlenecks and unnecessary expense associated with delivering the requisite component quality. The OEM partner, and turbine industry in general, expect to reap significant cost and resource savings if an AI-optimized set of parameters can be applied to specific machining operations. The technical scope of the proposed project involved the paving of a realistic path towards model-based and AI-enabled Integrated Computational Materials Engineering (ICME), and away from inefficient empirical process optimization and legacy manufacturing practices, which are no longer able to efficiently process novel high-performance turbine alloy materials. The project team will address the fundamental knowledge gap that currently exists within the ICME paradigm with respect to the process/structure/performance/energy impacts of finishing processes. While significant resources have been devoted to the ‘early stages’ of manufacturing, such as alloy design, primary and secondary processing, finishing processes have not been adequately integrated within ICME. To provide an actionable path towards model-based finishing process design (e.g., machining, burnishing, grinding, polishing), we will employ a novel AI-enabled process optimization paradigm, based on a computationally efficient, physics-based process simulator. Through limited experimental work to calibrate and validate our process simulator model via an advanced in-situ characterization technique and process optimization via reinforcement learning, the project will seek to demonstrate a viable alternative to the inefficient ‘legacy’ processing strategies, empirical testing and broad scope machining learning approaches, all of which fail to adequately consider complex process physics. The project team has identified an intermetallic γ-TiAl LPT alloy, which is currently being used as part of the OEM partner’s advanced gas turbine designs. This particular alloy poses significant manufacturing challenges during finishing operations, which limit the degree to which the current turbine design can be manufactured in an energy- and cost-efficient manner. Empirical testing and numerical modeling efforts to optimize processing parameters for γ-TiAl have not been able to resolve these manufacturing challenges, so the proposed physics-based AI-enabled optimization technology would offer a truly novel and transformative capability. The multi-organizational team of academic and industry experts from the UKY and the OEM partner will work together closely to demonstrate the analytical and experimental critical function and characteristic proof of concept of this novel approach.
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MO-DE-BRA-02: SIMAC: A Simulation Tool for Teaching Linear Accelerator Physics
Purpose: The first goal of this work is to develop software that can simulate the physics of linear accelerators (linac). The second goal is to show that this simulation tool is effective in teaching linac physics to medical physicists and linac service engineers. Methods: Linacs were modeled using analytical expressions that can correctly describe the physical response of a linac to parameter changes in real time. These expressions were programmed with a graphical user interface in order to produce an environment similar to that of linac service mode. The software, “SIMAC”, has been used as a learning aid in a professional development course 3 times (2014 – 2016) as well as in a physics graduate program. Exercises were developed to supplement the didactic components of the courses consisting of activites designed to reinforce the concepts of beam loading; the effect of steering coil currents on beam symmetry; and the relationship between beam energy and flatness. Results: SIMAC was used to teach 35 professionals (medical physicists; regulators; service engineers; 1 week course) as well as 20 graduate students (1 month project). In the student evaluations, 85% of the students rated the effectiveness of SIMAC as very good or outstanding, and 70% rated the software as the most effective part of the courses. Exercise results were collected showing that 100% of the students were able to use the software correctly. In exercises involving gross changes to linac operating points (i.e. energy changes) the majority of students were able to correctly perform these beam adjustments. Conclusion: Software simulation(SIMAC), can be used to effectively teach linac physics. In short courses, students were able to correctly make gross parameter adjustments that typically require much longer training times using conventional training methods.
60 APPLIED LIFE SCIENCES↗
Bio-compatible and highly sensitive two-dimensional plasmonic sensor
We propose a novel bio-compatible two dimensional plasmonic sensor with array of ring and the hole structure on an optically thick gold film for biochemical sensing. We use finite-difference time-domain simulation for design and calculation of sensitivity in the near-infrared region. The bio-compatible and cheap plasmonic glycerol sensor with high sensitivity by interferometer style as a motif in the sensor’s structure. The proposed sensor can be applied as highly sensitivity sensor with a good linear response under different glycerol concentrations.
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