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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Surface engineering to enhance heat generation and joint strength in dissimilar materials AZ31 and DP590 ultrasonic welding

A multiscale simulation approach was developed and employed to optimize the sheet surface conditions for higher interfacial temperature and joint strength in ultrasonic welding of magnesium alloy AZ31 and dual-phase steel DP590. First, a mesoscale model was used to study the relationship between friction coefficient and surface roughness, which can be modified by various engineering methods. Then a macroscopic process model was employed to study the effects of surface roughness on heat generation, indicating that a temperature increase can be achieved with rougher surfaces on two sides of both DP590 and AZ31 sheets. Samples prepared by sanding and filing, as well as grinding, were first characterized for surface roughness and then welded under ultrasonic vibration. An infrared camera was used to measure temperatures in situ for model validation. Overall, lap shear test results for the welded joint showed that the joint strength can be improved by 10~25% using filing and round grinding methods as a result of the enhanced heat generation and mechanical interlocking on the interface.

42 ENGINEERING↗
DOE OSTI2021

Common workflows for computing material properties using different quantum engines

The prediction of material properties based on density-functional theory has become routinely common, thanks, in part, to the steady increase in the number and robustness of available simulation packages. This plurality of codes and methods is both a boon and a burden. While providing great opportunities for cross-verification, these packages adopt different methods, algorithms, and paradigms, making it challenging to choose, master, and efficiently use them. We demonstrate how developing common interfaces for workflows that automatically compute material properties greatly simplifies interoperability and cross-verification. We introduce design rules for reusable, code-agnostic, workflow interfaces to compute well-defined material properties, which we implement for eleven quantum engines and use to compute various material properties. Each implementation encodes carefully selected simulation parameters and workflow logic, making the implementer’s expertise of the quantum engine directly available to non-experts. All workflows are made available as open-source and full reproducibility of the workflows is guaranteed through the use of the AiiDA infrastructure.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Project DarkStar: Vision for LLNL in 2030

DarkStar was a Strategic Initiative (FY2021-FY2024) to investigate applications of Artificial Intelligence (AI) and Machine Learning (ML) to scientific problems of complex hydrodynamics, shockwave physics and energetic materials. The research focused on physics and engineering design as a process that can be tremendously accelerated through merging AI with advanced physics simulation on exascale-class platforms, and to experimentally validate this revolutionary new approach through dynamic materials campaigns. A central thread of scientific inquiry was in the application of AI to enable human understanding of how to control hydrodynamic instability (which has impacts to areas such as inertial confinement fusion) via engineering features and time-dependent sources. Motivated by an unfinished line of research started by Dr. Johnny von Neumann, AI-enabled simulation approaches were developed that allowed DarkStar researchers to uncover several ground-breaking discoveries regarding hydrodynamic instability, including how to completely suppress Richtmyer-Meshkov instability (RMI). These S&T discoveries, along with other advances, have shown the way for an entirely new approach to time-dependent problems known as inverse design – the idea that complex systems can be developed directly from a final state that is to be achieved and resolve the initial design via satisfying several constraints simultaneously via AI/ML. Through experimental campaigns conducted across a wide range of facilities in the NNSA complex (the High Explosive Application Facility at LLNL, the Dynamic Compression Sector/Advanced Photon Source at Argonne National Lab, and Special Technologies Laboratory at MSTS) the radical new AI/ML approach to engineering complex material dynamics was verified, establishing a new field of study within the realm of shock physics. As advanced manufacturing capabilities continue to develop, the great importance of inverse design as a means to apply that technology effectively for NNSA missions will feature prominently over this decade. DarkStar has positioned NNSA as a world-leader in this newly emerging cross-disciplinary area of AI methods for advanced physics simulation and pioneered multiple novel approaches that have enabled the broader scientific community. By allowing us to see past the horizon, to 2030 and beyond, DarkStar has illuminated the vast potential of AI/ML to impact a wide range of new national security missions and, consequently, multiple areas of further research have already emerged across the NNSA and DOD complex.

42 ENGINEERING↗
DOE OSTI2022

Bounds of linear time‐varying systems with applications to quantify model gap of synchronous generators

Abstract Linear time‐varying (LTV) systems play a key role in many engineering problems, for example, trajectory sensitivity analysis of power systems. Because LTV systems do not generally have closed‐form solutions, estimates of their bounds are crucial to their analysis. In this paper, bounds for LTV systems with known inputs and unknown but bounded inputs are obtained via Grönwall's inequality. The estimated bounds are then used to quantify the gap between synchronous generators and their models in different scenarios through simulation.

42 ENGINEERING↗
DOE OSTI2021

A coupled human–natural system analysis of freshwater security under climate and population change

Limited water availability, population growth, and climate change have resulted in freshwater crises in many countries. Jordan’s situation is emblematic, compounded by conflict-induced population shocks. Integrating knowledge across hydrology, climatology, agriculture, political science, geography, and economics, we present the Jordan Water Model, a nationwide coupled human–natural-engineered systems model that is used to evaluate Jordan’s freshwater security under climate and socioeconomic changes. The complex systems model simulates the trajectory of Jordan’s water system, representing dynamic interactions between a hierarchy of actors and the natural and engineered water environment. A multiagent modeling approach enables the quantification of impacts at the level of thousands of representative agents across sectors, allowing for the evaluation of both systemwide and distributional outcomes translated into a suite of water-security metrics (vulnerability, equity, shortage duration, and economic well-being). Model results indicate severe, potentially destabilizing, declines in freshwater security. Per capita water availability decreases by approximately 50% by the end of the century. Without intervening measures, >90% of the low-income household population experiences critical insecurity by the end of the century, receiving <40 L per capita per day. Widening disparity in freshwater use, lengthening shortage durations, and declining economic welfare are prevalent across narratives. To gain a foothold on its freshwater future, Jordan must enact a sweeping portfolio of ambitious interventions that include large-scale desalinization and comprehensive water sector reform, with model results revealing exponential improvements in water security through the coordination of supply- and demand-side measures.

42 ENGINEERING↗
DOE OSTI2018

Structure and propagation of two-dimensional, partially premixed, laminar flames in diesel engine conditions

We investigate here the influence of inflow velocity (V in ) and scalar dissipation rate (χ) on the flame structure and stabilisation mechanism of steady, laminar partially premixed n-dodecane edge flames stabilised on a convective mixing layer. Numerical simulations were performed for three different χ profiles and several V in (V in = 0.2 to 2.5m/s). The ambient thermochemical conditions were the same as the Engine Combustion Network’s (ECN) Spray A flame, which in turn represents conditions in a typical heavy duty diesel engine. The results of a combustion mode analysis of the simulations indicate that the flame structure and stabilisation mechanism depend on V in and χ. For low V in the flame is attached. Increasing V in causes the high-temperature chemistry (HTC) flame to lift-off, while the low-temperature chemistry (LTC) flame is still attached. A unique speed S R associated with this transition is defined as the velocity at which the lifted height has the maximum sensitivity to changes in Vin. This transition velocity is negatively correlated with χ. Near V i n = S R a tetrabrachial flame structure is observed consisting of a triple flame, stabilised by flame propagation into the products of an upstream LTC branch. Further increasing the inlet velocity changes the flame structure to a pentabrachial one, where an additional HTC ignition branch is observed upstream of the triple flame and ignition begins to contribute to the flame stabilisation. At large V in , the LTC is eventually lifted, and the speed at which this transition occurs is insensitive to χ. Further increasing V in increases the contribution of ignition to flame stabilisation until the flame is completely ignition stabilised. Flow divergence caused by the LTC branch reduces the χ at the HTC branches making the HTC more resilient to χ. The results are discussed in the context of identification of possible stabilisation modes in turbulent flames.

42 ENGINEERING↗
DOE OSTI2021

Discrete stochastic model of point defect-dislocation interaction for simulating dislocation climb

Dislocation climb is an important high temperature process in metals plasticity, responsible for the phenomena such as creep, swelling, or hardening. Climb is defined by the ability of dislocations to leave their original glide plane by interacting with point defects. As such, dislocation climb is controlled by point defect diffusion/absorption/emission, all of which involve thermal activation. The existing thermodynamically consistent models for climb are generally formulated in a continuum framework, through the definition of effective defect fluxes and climb propensities in response to thermodynamic driving forces. However, the point-wise discrete nature of vacancies (and/or self-interstitials) confers a highly discrete nature to the climb dynamics, which is also strongly affected by elastic forces. The combination of discreteness, thermal activation, and elasticity makes this process too challenging for direct atomistic methods such as molecular dynamics. Here we develop a kinetic Monte Carlo model that captures vacancy generation and transport kinetics acting in conjuction with the evolving elastic fields provided by discrete dislocation dynamics simulations. The two models are coupled via the applied stresses and stress gradients generated by dislocation structures at vacancy locations. Our simulations reveal two surprising results. First that climb is dominated by vacancy emission even when the background vacancy concentration is much higher than the equilibrium one. And, second, that climb velocities might be much faster than otherwise believed when one uses the classical theories of climb. These effects are due to the locality of vacancy-dislocation processes, which are not captured in classical treatments that assume smooth vacancy fluxes and homogeneous concentrations. We apply the method to study elementary climb processes in body-centered cubic iron and furnish climb mobility functions to be used in parametric dislocation dynamics and/or crystal plasticity simulations. Here, we apply the technique to study non-conservative plastic bypass of spherical precipitates by edge dislocations and point out the differences between our discrete approach and existing continuum formulations.

36 MATERIALS SCIENCE↗
DOE OSTI2024

FENIX: Towards a Fully Integrated Multiphysics Framework for Plasma Facing Component Modeling

Computational tools have a crucial role to play in accelerating the deployment of fusion as a clean, reliable, abundant, and sustainable energy source. Multiphysics, high-fidelity simulation capabilities can help model, study, and predict intricate interactions between materials performance, plasma exposure, neutron irradiation, and engineering processes. As such, they can assist in the resolution of scientific and engineering challenges underpinning design, construction, and commission of fusion power plants. To address these needs, ongoing efforts are leveraging the Multiphysics Object-Oriented Simulation Environment (MOOSE) framework and delivering new computational tools for the fusion community. These tools inherit crucial attributes from MOOSE. They are open-source, modular, integrated with nuclear industry-standard software quality assurance processes, and enable multiphysics, multi-fidelity, fully integrated, zero- to three-dimensional, and massively parallel simulations. After a short overview of these capabilities, we will present the development of Fusion ENergy Integrated multiphys-X (FENIX), a MOOSE-based application designed to enable plasma facing component design and performance evaluation. Throughout their lifetime, plasma facing components are exposed to extreme thermal loads, repeated thermal shocks, and irradiation by plasma ions, neutral particles, and high-energy neutrons. Consequently, designing a plasma facing component with acceptable lifetime degradation is extremely challenging. FENIX aims to model the multiphysics environment in which plasma facing components evolve to accelerate their design studies. To that end, FENIX couples existing MOOSE capabilities such as heat transfer, thermomechanics, and thermal hydraulics, with tritium transport via the MOOSE-based Tritium Migration Analysis Program, Version 8 (TMAP8), with neutronics via the MOOSE-based high-fidelity neutron-photon transport and fluid dynamics code Cardinal, and finally with Particle-in-Cell plasma simulation capabilities being developed in this project. In this study, we present the current FENIX capabilities and preliminary results of its application to model the Tritium Plasma Experiment set up at Idaho National Laboratory.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Diesel Generator Model Parameterization for Microgrid Simulation Using Hybrid Box-Constrained Levenberg-Marquardt Algorithm

Existing generator parameterization methods, typically developed for large turbine generator units, are difficult to apply to small kW-level diesel generators in microgrid applications. Here, this article presents a model parameterization method that estimates a complete set of kW-level diesel generator parameters simultaneously using only load-step-change tests with limited measurement points. This method provides a more cost-efficient and robust approach to achieve high-fidelity modeling of diesel generators for microgrid dynamic simulation. A two-stage hybrid box-constrained Levenberg-Marquardt (H-BCLM) algorithm is developed to search the optimal parameter set given the parameter bounds. A heuristic algorithm, namely Generalized Opposition-based Learning Genetic Algorithm (GOL-GA), is applied to identify proper initial estimates at the first stage, followed by a modified Levenberg-Marquardt algorithm designed to fine tune the solution based on the first-stage result. The proposed method is validated against dynamic simulation of a diesel generator model and field measurements from a 16kW diesel generator unit.

42 ENGINEERING↗
DOE OSTI2016

A new model for active nucleation site density in boiling systems

A new model for active nucleation site density in boiling systems has been developed. The model is based on parametric analysis of existing experimental data and is a function of wall superheat, pressure, and contact angle. The model is applicable for a wide pressure range - from 0.101 MPa to 19.8 MPa. Preliminary studies of temperature dependency of the contact angle have also been performed. The new model is intended to improve the predictions of the interfacial area concentration in two-fluid models and the wall temperature in subcooled boiling simulations. Validation activities have shown that the active nucleation site density predicted by the new model is in a good agreement with various published experimental data, and have demonstrated the achieved improvements as compared to existing models. (authors)

42 ENGINEERING↗
DOE OSTI2022

Pit rim decomposition into multiple quantum dots on surfaces of epitaxial thin films grown on pit-patterned substrates

Here, we report results of dynamical simulations according to an experimentally validated surface morphological evolution model on the formation of regular arrays of quantum dot molecules (QDMs) consisting of 1D arrays of smaller interacting quantum dots (QDs). These QD arrays form along the sides of each pit rim on the surface of a coherently strained thin film epitaxially deposited on a semiconductor substrate, the surface of which consists of a periodic pattern of inverted prismatic pits with rectangular pit openings. We find that this complex QDM pattern results from the decomposition of the pit rim from a “quantum fortress” with four elongated QDs into four 1D arrays of multiple smaller QDs arranged along each side of the pit rim. Systematic parametric analysis indicates that varying the pit opening dimensions and the pit wall inclination directly impacts the number of QDs in the resulting QDM pattern, while varying the pit depth only affects the dimensions of the QDs in the nanostructure pattern. Therefore, the number, arrangement, and sizes of QDs in the resulting pattern of QDMs on the film surface can be engineered precisely by proper tuning of the pit design parameters. Our simulation results are supported by predictions of morphological stability analysis, which explains the pit rim decomposition into multiple QDs as the outcome of a tip-splitting instability and provides a fundamental characterization of the post-instability nanostructure pattern. Our theoretical findings can play a vital role in designing optimal semiconductor surface patterns toward enabling future nanofabrication technologies.

36 MATERIALS SCIENCE↗
DOE OSTI2021

I.1 Heavy-Duty Diesel Combustion (Sandia National Laboratories)

Regulatory drivers and market demands for lower pollutant emissions, lower carbon dioxide emissions, and lower fuel consumption motivate the development of cleaner and more fuel-efficient engine operating strategies. Most current production heavy-duty diesel engines use a combination of both in-cylinder and exhaust emissions-control strategies to achieve these goals. The emissions and efficiency performance of in-cylinder strategies depend strongly on flow and mixing processes that can be influenced by using multiple fuel injections. Past work performed under this project showed that adding a second injection can reduce soot to levels below what would have been produced by an unchanged first injection, thereby increasing load while decreasing soot and potentially reducing brake specific fuel consumption. Information characterizing the important in-cylinder processes with multiple injections has been gleaned from ensemble-averaged planar laser-induced incandescence (PLII) imaging visualizing the soot cloud and planar induced fluorescence (PLIF) of OH characterizing the soot oxidation regions. PLII showed a consistent disruption of the first injection soot cloud by the second injection. In conjunction with OH-PLIF, differences in soot oxidation patterns for multiple injections compared to single injections were observed. This understanding was further enhanced in FY20, when high-speed imaging resolving the above-mentioned effects in a single cycle were combined with direct numerical simulations investigating the multiple-injection ignition process on the microscopic level of turbulence and chemistry interaction. In FY21, these findings in conjunction with findings from other researchers published in the scientific literature were composed into a preliminary multiple-injection conceptual model of fuel-mixing, injection and ignition processes. Remaining key research questions were also highlighted. In addition, wall heat flux was investigated experimentally and with numerical simulations to understand the potential of multiple injections to reduce the engine heat losses and further enhance the efficiency.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

Lagrangian large eddy simulations via physics-informed machine learning

High-Reynolds number homogeneous isotropic turbulence (HIT) is fully described within the Navier–Stokes (NS) equations, which are notoriously difficult to solve numerically. Engineers, interested primarily in describing turbulence at a reduced range of resolved scales, have designed heuristics, known as large eddy simulation (LES). LES is described in terms of the temporally evolving Eulerian velocity field defined over a spatial grid with the mean-spacing correspondent to the resolved scale. This classic Eulerian LES depends on assumptions about effects of subgrid scales on the resolved scales. Here, we take an alternative approach and design LES heuristics stated in terms of Lagrangian particles moving with the flow. Our Lagrangian LES, thus L-LES, is described by equations generalizing the weakly compressible smoothed particle hydrodynamics formulation with extended parametric and functional freedom, which is then resolved via Machine Learning training on Lagrangian data from direct numerical simulations of the NS equations. The L-LES model includes physics-informed parameterization and functional form, by combining physics-based parameters and physics-inspired Neural Networks to describe the evolution of turbulence within the resolved range of scales. The subgrid-scale contributions are modeled separately with physical constraints to account for the effects from unresolved scales. We build the resulting model under the differentiable programming framework to facilitate efficient training. We experiment with loss functions of different types, including physics-informed ones accounting for statistics of Lagrangian particles. We show that our L-LES model is capable of reproducing Eulerian and unique Lagrangian turbulence structures and statistics over a range of turbulent Mach numbers.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Charting the Path to Electrification: Analyzing the Economic and Technological Potential of Advanced Vehicle Powertrains

The U.S. Department of Energy’s Vehicle Technologies Office (DOE-VTO) is driving advancements in highway transportation by targeting energy efficiency, environmental sustainability, and cost reductions. This study investigates the fuel economy potential and cost implications of advanced powertrain technologies using comprehensive system simulations. Leveraging tools such as Autonomie and TechScape, developed by Argonne National Laboratory, this study evaluates multiple timeframes (2023–2050) and powertrain types, including conventional internal combustion engines, hybrid electric vehicles (HEVs), plug-in hybrid electric vehicles (PHEVs), and battery electric vehicles (BEVs). Simulations conducted across standard regulatory driving cycles provide detailed insights into fuel economy improvements, cost trajectories, and total cost of ownership. The findings highlight key innovations in battery energy density, lightweighting, and powertrain optimization, demonstrating the growing viability of BEVs and their projected economic competitiveness with conventional vehicles by 2050. This work delivers actionable insights for policymakers and industry stakeholders, underscoring the transformative potential of vehicle electrification in achieving sustainable transportation goals.

Islam, Ehsan Sabri (ORCID:0000000200220180)↗
DOE OSTI2018

Longitudinal train dynamics model for a rail transit simulation system

The paper develops a longitudinal train dynamics model in support of microscopic railway transportation simulation. The model can be calibrated without any mechanical data making it ideal for implementation in transportation simulators. The calibration and validation work is based on data collected from the Portland light rail train fleet. The calibration procedure is mathematically formulated as a constrained non-linear optimization problem. The validity of the model is assessed by comparing instantaneous model predictions against field observations, and also evaluated in the domains of acceleration/deceleration versus speed and acceleration/deceleration versus distance. A test is conducted to investigate the adequacy of the model in simulation implementation. The results demonstrate that the proposed model can adequately capture instantaneous train dynamics, and provides good performance in the simulation test. Thus, the model provides a simple theoretical foundation for microscopic simulators and will significantly support the planning, management and control of railway transportation systems.

42 ENGINEERING↗
DOE OSTI2015

Materials for Advanced Ultrasupercritical Steam Turbines Task 4: Cast Superalloy Development

The Steam Turbine critical stationary structural components are high integrity Large Shell and Valve Casing heavy section Castings, containing high temperature steam under high pressures. Hence to support the development of advanced materials technology for use in an AUSC steam turbine capable of operating with steam conditions of 760°C (1400°F) and 35 Mpa (5000 psia), Casting alloy selection and evaluation of mechanical, metallurgical properties and castability with robust manufacturing methods are mandated. Alloy down select from Phase 1 based on producability criteria and creep rupture properties tested by NETL-Albany and ORNL directed the consortium to investigate cast properties of Haynes 282 and Haynes 263. The goals of Task 4 in Phase 2 are to understand a broader range of mechanical properties, the impact of manufacturing variables on those properties. Scale up the size of heats to production levels to facilitate the understanding of the impact of heat and component weight, on metallurgical and mechanical behavior. GE Power & Water Materials and Processes Engineering for the Phase 2, Task 4.0 Castings work, systematically designed and executed casting material property evaluation, multiple test programs. Starting from 15 lbs. cylinder castings to world’s first 17,000 lbs. poured weight, heavy section large steam turbine partial valve Haynes 282 super alloy casting. This has demonstrated scalability of the material for steam Turbine applications. Activities under Task 4.0, Investigated and characterized various mechanical properties of Cast Haynes 282 and Cast Nimonic 263. The development stages involved were: 1) Small Cast Evaluation: 4 inch diam. Haynes 282 and Nimonic 263 Cylinders. This provided effects of liquidus super heat range and first baseline mechanical data on cast versions of conventional vacuum re-melted and forged Ni based super alloys. 2) Step block castings of 300 lbs. and 600 lbs. Haynes 282 from 2 foundry heats were evaluated which demonstrated the importance of proper heat treat cycles for Homogenization, and Solutionizing parameters selection and implementation. 3) Step blocks casting of Nimonic 263: Carried out casting solidification simulation analysis, NDT inspection methods evaluation, detailed test matrix for Chemical, Tensile, LCF, stress rupture, CVN impact, hardness and J1C Fracture toughness section sensitivity data and were reported. 4) Centrifugal Casting of Haynes 282, weighing 1400 lbs. with hybrid mold (half Graphite and half Chromite sand) mold assembly was cast using compressor casing production tooling. This test provided Mold cooling rates influence on centrifugally cast microstructure and mechanical properties. Graphite mold section out performs sand mold across all temperatures for 0.2% YS; %Elongation, %RA, UTS at 1400°F. Both Stress-LMP and conditional Fracture toughness plots data were in the scatter band of the wrought alloy. 5) Fundamental Studies on Cooling rates and SDAS test program. Evaluated the influence of 6 mold materials Silica, Chromite, Alumina, Silica with Indirect Chills, Zircon and Graphite on casting solidification cooling rates. Actual Casting cooling rates through Liquidus to Solidus phase transition were measured with 3 different locations based thermocouples placed in each mold. Compared with solidification simulation cooling rates and measurement of SDAS, microstructure features were reported. The test results provided engineered casting potential methods, applicable for heavy section Haynes 282 castings for optimal properties, with foundry process methods and tools. 6) Large casting of Haynes 282 Drawings and Engineering FEM models and supplemental requirements with applicable specifications were provided to suppliers for the steam turbine proto type feature valve casing casting. Molding, melting and casting pouring completed per approved Manufacturing Process Plan during 2014 Q4. The partial valve casing was successfully cast after casting methods were validated with solidification simulation analysis and the casting met NDT inspection and acceptance criteria. Heat treated and sectioned to extract trepan samples at different locations comparing with cast on coupons test data. Material properties requisite for design, such as tensile, creep/rupture, LCF, Fracture Toughness, Charpy V-notch chemical analysis testing were carried out. The test results will be presented in the final report. The typical Haynes 282 large size Steam Turbine production casting from Order to Delivery foundry schedule with the activity break up is shown in Figures 107 and 108. • From Purchase Order placement to Casting pouring ~ 26 weeks. 1. Sales and commercial review 3 2. Engineering Drawings/models review 4 3. Pattern and core box manufacturing 6 4. Casting process engineering review 4 5. FEM and solidification simulation analysis 4 6. Gating & Feeder Attachments, Ceramic tiling 2 7. Molding and coremaking production scheduling 6 8. Melting planning and schedule 3 9. Pouring, cooling and shake out 2 • From Pouring to casting Delivery ~ 29 weeks 10. Shot blast and riser cutting, gates removal 3 11. Homogenizing , solutionizing HT furnace prep 4 12. Grinding, Fettling 2 13. Aging HT Cycle, cooling 2 14. VT and LPT NDT inspections 2 15. Radiographic inspection 4 16. Mechanical testing, Chemical analysis test certs 4 17. Casting weld repair upgrades and Aging PWHT 4 18. NDT after weld repairs and casting upgrades 3 19. Casting Final Inspection and test certifications 3 20. Package and delivery 2 Hence the Total Lead time from P.O to Casting delivery is approximately 55 weeks. The Task 4.2 and Task 4.3 activities and reporting completed.

Thangirala, Mani↗
DOE OSTI2017

Using simulators to assess knowledge and behavior of “novice” operators of critical infrastructure under cyberattack events

—The transition from the traditional power grid to the smart grid improves reliability, performance, and management, while simultaneously increasing its susceptibility to cyberattacks. One of the biggest weaknesses in grid security is the human agent responsible for its maintenance and operations. As such, it is crucial to embed hands-on understanding of grid operations and security, especially for students in the Electrical and Computer Engineering (ECE) fields. This paper presents a case study where ECE students from Temple University used an interactive microgrid simulator, "Grid Game", a program developed by Idaho National Laboratory. This case study offers insights into the ECE students’ understanding of key engineering principles (microgrid stability, generation control system, generator inertia, energy storage, and grid security) gained by using the simulator program. Furthermore, the human behavior (strategies to prepare for and respond to cyberattacks, and cooperation and conflict in decision-making) of defenders/ECE students as they experience cyberattacks are also discussed. The paper then offers some limitations and possible suggestions for future research.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2017

Verification of the Two-Fluid Model in the Spectral Element Code Nek-2P for Adiabatic Flow Conditions

The simulation of multiphase flow is a difficult physical, computational, and numerical problem. Sophisticated tools are necessary to provide results encompassing a wide range of physical phenomena. The development of these tools must be supported by rigorous analysis and ongoing efforts of verification and validation to ensure the accuracy of simulations. The Nek-2P multiphase code is being developed at Argonne with the general goal of simulating a wide range of multiphase flows and the primary goal of simulating boiling flows in LWR fuel assemblies. As part of this, there is an ongoing effort to verify the code and validate the underlying physical models. The objective of this work is to present recent results in the verification of Nek-2P. As a starting point, this work is focused on adiabatic flows for the sake of simplicity with the immediate next planned step to expand the effort to include heat and mass transfer. Details of the verification of the implemented mass fraction transport, momentum conservation, and pressure equations in Nek-2P are presented. Results of simulations are compared to analytic solutions when possible, however due to the complexity of multiphase flows, these are seldom available. To overcome this difficulty, an independent model is used to provide solutions for comparison.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗