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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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At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Thermal transport dynamics in the quasi-single helicity state

A dynamical model describing oscillations between multiple and single helicity configurations in the quasi-single helicity (QSH) state of the reversed field pinch [P. W. Terry and G. G. Whelan, Plasma Phys. Controlled Fusion 56, 094003 (2014)] is extended to include electron temperature profile dynamics. It is shown that QSH dynamics is linked to the electron temperature profile because the suppression of mode coupling between tearing modes proposed to underlie QSH also suppresses magnetic-fluctuation-induced thermal transport. Above the threshold of dominant-mode shear that marks the transition to QSH, the model produces temperature-gradient steepening in the strong shear region. Oscillations of the dominant and secondary mode amplitudes give rise to oscillations of the temperature gradient. The phasing and amplitude of temperature gradient oscillations relative to those of the dominant mode are in agreement with experiment. This provides further evidence that the model, while heuristic, captures key physical aspects of the QSH state.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2019

A dynamic, unified design for dedicated message matching engines for collective and point-to-point communications

The Message Passing Interface (MPI) libraries use message queues to guarantee correct message ordering between communicating processes. Message queues are in the critical path of MPI communications and thus, the performance of message queue operations can have significant impact on the performance of applications. Collective communications are widely used in MPI applications and they can have considerable impact on generating long message queues. In this paper, we propose a unified message matching mechanism that improves the message queue search time by distinguishing messages coming from point-to-point and collective communications and using a distinct message queue data structure for them. For collective operations, it dynamically profiles the impact of each collective call on message queues during the application runtime and uses this information to adapt the message queue data structure for each collective dynamically. Moreover, we use a partner/non-partner message queue data structure for the messages coming from point-to-point communications. The proposed approach can successfully reduce the queue search time while maintaining scalable memory consumption. The evaluation results show that we can obtain up to 5.5x runtime speedup for applications with long list traversals. Moreover, we can gain up to 15% and 94% queue search time improvement for all elements in applications with short and medium list traversals, respectively.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Evaluation of dynamic testing of full-scale wind turbine drivetrains with hardware-in-the-loop

Dynamometer testing of full-scale wind turbine drivetrains involves subjecting integrated components to extreme static loads, fatigue loads, or dynamic loads to replicate field conditions. This paper provides a detailed evaluation of the uncertainty and errors in applied loads and measured responses, and their magnitude relative to established repeatability bounds for a drivetrain subjected to static and dynamic loads on the 7.5 MW test bench at the Clemson University Wind Turbine Drivetrain Testing Facility. An ideal drivetrain simulation model is utilized to isolate the influence of load tracking errors on test article responses. It is shown that the test article response variations are mainly driven by run out and clearances inherent to the drivetrain. For the dynamic profiles, the load tracking errors are within acceptable limits. Furthermore, a frequency analysis is used to show that the test bench controller tracking performance is acceptable for profiles with frequency content up to 1.5 Hz.

17 WIND ENERGY↗
DOE OSTI2020

Flexible Reinforcement Learning Framework for Building Control using EnergyPlus-Modelica Energy Models

In recent years, reinforcement learning (RL) methods have been greatly enhanced by leveraging deep learning approaches. RL methods applied to building control have shown potential in many applications due to their ability to complement or replace conventional methods such as model-based or rule-based controls. However, RL-based building control software is likely tailored either to one target building system or to a specific RL method so that significant additional effort would be required to customize the RL-based controller for use in other building systems or with other RL approaches. Also, RL-based building controls usually depend on building energy simulations to train controllers, so emulating building dynamics (i.e., thermal dynamics and control dynamics) and capturing sub-hourly dynamic profiles are crucial to further the development of effective RL-based building control methods. To address these challenges, we present an open source RL-based control software employing a high-fidelity hybrid EnergyPlus-Modelica building energy model which emulates building dynamics at 1-minute resolution. This software consists of decoupled components (environment, building emulator, control agent, and RL algorithm), which allows for quick prototyping and benchmarking of standard RL algorithms in different systems; for example, a single component can be replaced without revising all of the software. To demonstrate this software framework, we conducted a benchmark study using an EnergyPlus-Modelica building energy model for a Chicago office building with an RL-based controller to dynamically control the chilled water temperature setpoint and the air handling unit supply air temperature setpoint on selected floors.

Lee, Joon-Yong↗
DOE OSTI2017

Tractable flux-driven temperature, density, and rotation profile evolution with the quasilinear gyrokinetic transport model QuaLiKiz

Quasilinear turbulent transport models are a successful tool for prediction of core tokamak plasma profiles in many regimes. Their success hinges on the reproduction of local nonlinear gyrokinetic fluxes. We focus on significant progress in the quasilinear gyrokinetic transport model QuaLiKiz (Bourdelle et al 2016 Plasma Phys. Control. Fusion 58 014036), which employs an approximated solution of the mode structures to significantly speed up computation time compared to full linear gyrokinetic solvers. Optimisation of the dispersion relation solution algorithm within integrated modelling applications leads to flux calculations $\times {10}^{6-7}$ faster than local nonlinear simulations. This allows tractable simulation of flux-driven dynamic profile evolution including all transport channels: ion and electron heat, main particles, impurities, and momentum. Furthermore, QuaLiKiz now includes the impact of rotation and temperature anisotropy induced poloidal asymmetry on heavy impurity transport, important for W-transport applications. Application within the JETTO integrated modelling code results in 1 s of JET plasma simulation within 10 h using 10 CPUs. Simultaneous predictions of core density, temperature, and toroidal rotation profiles for both JET hybrid and baseline experiments are presented, covering both ion and electron turbulence scales. The simulations are successfully compared to measured profiles, with agreement mostly in the 5%–25% range according to standard figures of merit. QuaLiKiz is now open source and available at www.qualikiz.com.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

On hybrid scenarios in KSTAR

We report the status of hybrid scenario experiments in Korea Superconducting Tokamak Advanced Research (KSTAR). The hybrid scenario is defined as stationary discharges with ${\beta _{\rm{N}}}$ $ \geqslant $ 2.4 and ${H_{89}}$ $ \geqslant $ 2.0 at ${q_{95}}$ < 6.5 without or with very mild sawtooth activities in KSTAR. It is being developed towards reactor-relevant conditions. High performance of ${\beta _{\rm{N}}} \lesssim 3.0$, ${H_{89}} \lesssim 2.4$ and G-factor ($ \equiv {\beta _{\rm{N}}}{H_{89}}/q_{95}^2$) $ \lesssim 0.4$6 has been achieved and sustained for $ \gtrsim 40{{\tau }_{\text{E}}}$ at ne/nGW ~ 0.7 with heating power of $ \lesssim $5 MW. Some KSTAR hybrid discharges exhibit a unique feature of a slow transition from conventional H-mode to hybrid mode after the third neutral beam injection. The reason for the confinement enhancement is extensively studied in this transition period of a representative discharge exhibiting a common feature of KSTAR hybrid scenarios. 0D performance analysis with magnetohydrodynamic activities, 1D kinetic profile dynamics, power balance analysis, linear gyro-kinetic analysis and edge pedestal stability analysis were conducted. The enhancement is thought to be from both the core and the pedestal. The improvement in the core region of the ion energy channel is observed from the linear gyro-kinetic analysis considering the electromagnetic, the fast ion, the Shafranov shift, ${\it{\omega }_{E \times B}}$, and the magnetic shear effect. The electromagnetic finite $\beta $ stabilisation plays a role in the inner core region at ${\rho _{\rm{tor}}}\sim0.35$ together with the fast ion effect. The alpha stabilisation effect is also found at ${\rho _{\rm{tor}}}\sim0.5$. ${\omega _{E \times B}}$, which could reduce the linear growth of the ion temperature gradient mode in the outer core region at ${\rho _{\rm{tor}}}\sim0.5 - 0.7$ with the highest contribution from the toroidal rotation. Furthermore, regarding the improvement in the pedestal, Shafranov shift broadens the stability boundary of the pedestal in support of the diamagnetic effect. The pedestal height and width could be reproduced by the EPED model, while a realistic current profile is used to calculate the internal inductance for Shafranov shift. Based on these findings, a comprehensive confinement enhancement mechanism has been proposed by considering the core-edge interplay.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Comparative Study of High-Resolution LysB29(Nε-myristoyl) des(B30) Insulin Structures Display Novel Dynamic Causal Interrelations in Monomeric-Dimeric Motions

The treatment of insulin-dependent diabetes mellitus is characterized by artificial supplementation of pancreatic β-cell ability to regulate sugar levels in the blood. Even though various insulin analogs are crucial for reasonable glycemic control, understanding the dynamic mechanism of the insulin analogs may help to improve the best-protracted insulin analog to assist people with type 1 diabetes (T1D) to live comfortably while maintaining tight glycemic control. Here, we present the high-resolution crystal structure of NN304, known as insulin detemir, to 1.7 Å resolution at cryogenic temperature. We computationally further investigated our crystal structure’s monomeric-dimeric conformation and dynamic profile by comparing it with a previously available detemir structure (PDB ID: 1XDA). Our structure (PDB ID: 8HGZ), obtained at elevated pH, provides electrostatically triggered minor movements in the equilibrium between alternate conformational substates compared to the previous structure, suggesting it might induce an intermediate state in the dissociation pathway of the insulin detemir’s hexamer:dihexamer equilibrium. Supplemented with orientational cross-correlation analysis by a Gaussian network model (GNM), this alternate oligomeric conformation offers the distinct cooperative motions originated by loose coupling of distant conformational substates of a protracted insulin analog that has not been previously observed.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Regulation of the central safety factor and normalized beta under low NBI torque in DIII-D

An algorithm has been designed to simultaneously control the central safety factor (q 0 ) and normalized beta (β N ) while ensuring near-zero torque from the neutral beam injection in DIII-D. Feedback control of q 0 and β N in tokamaks can be beneficial due to the close relationship that these variables have with plasma performance and magneto-hydrodynamic stability. In addition, low neutral-beam-torque conditions are of special interest in present devices because future burning-plasma tokamaks such as ITER will most likely operate at very low plasma rotation. The control synthesis of the algorithm presented in this work is based on a linearized, one-dimensional (1D) model of the current-profile dynamics coupled with a zero-dimensional (0D) plasma-energy balance. The actuators considered are neutral beam injection and electron-cyclotron heating and current drive, and discrete logic determines the neutral-beam injection powers that deliver near-zero torque. Here, the algorithm has been tested in nonlinear, 1D simulations using COTSIM (Control-Oriented Transport SIMulator) and in DIII-D experiments, demonstrating satisfactory performance.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2019

Engineering Nanoscale Thermal Transport: Size- and Spacing-Dependent Cooling of Nanostructures

Nanoscale thermal transport is becoming ever more technologically important with the development of next-generation nanoelectronics, nanomediated thermal therapies, and high efficiency thermoelectric devices. However, direct experimental measurements of nondiffusive heat flow in nanoscale systems are challenging, and first-principle models of real geometries are not yet computationally feasible. In recent work, we used ultrafast pulses of short-wavelength light to uncover a previously-unobserved regime of nanoscale thermal transport that occurs when the width and separation of heat sources are comparable to the mean free paths of the dominant heat-carrying phonons in the substrate. We now systematically compare thermal transport from gratings of metallic nanolines with different periodicities, on both silicon and fused-silica substrates, to map the entire nanoscale thermal transport landscape – from closely spaced through increasingly isolated to fully isolated heat-transfer regimes. By monitoring the surface profile dynamics with subangstrom sensitivity, we directly measure thermal transport from the nanolines into the substrate. This allows us to quantify for the first time how the nanoline separation significantly impacts thermal transport into the substrate, making it possible to reach efficiencies that are within a factor of 2 of the diffusive (i.e., thin-film) limit. We also show that partially isolated nanolines perform significantly worse, because cooling occurs in a regime that is intermediate between close-packed and fully isolated heat sources. This work thus confirms the surprising prediction that closely spaced nanoscale heat sources can cool more quickly than when far apart. In conclusion, these results show that our predictive model is validated by experiment over a broad parameter space, which is important for benchmarking theories that go beyond the Fourier model of heat diffusion, and for informed design of nanoengineered systems.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2017

Architecture Independent Integrated Early Performance and Energy Estimation

The end of Dennard’s scaling, coupled to the necessity to keep increasing computational performance in constrained power envelopes, is leading developers towards the need to opti- mize applications not only for performance, but also for energy consumption. In such a scenario, solutions that enable estimating performance and energy consumption of a program as early as possible, even during development and without the necessity to access the final target hardware, can become fundamental tools to reduce the design space, the optimization effort, and provide potential opportunities to automate the optimization process itself. In this position paper, we discuss the design of a performance and energy estimation framework based on a retargetable com- piler. Our proposed approach targets the Intermediate Repre- sentation (IR) of the LLVM compiler. The IR based approach enables, after a model is built, estimation from a host different from the target architecture, even considering dynamic infor- mation. We present the rationale behind such a framework, identify opportunities and components readily available (such as the provided static analysis, quick ways to add instrumentation for dynamic profiling, and the multiple backends), and aspects that still need further research efforts (such as more effective non-linear, or machine learning based models). We also discuss a hand-developed case study, based on a simple sparse matrix vector multiplication with a linear model, to motivate the needs for such a framework.

Estimation, Compilers, Performance Analysis↗
DOE OSTI2020

Predictive Integrated Modeling of Heated Tokamak Plasmas (Final Technical Report)

The research carried out by the Lehigh University fusion group during this reporting period: (1) Self-consistent predictive core-pedestal ITER scenario modeling; (2) Microtearing instabilities and electron thermal transport in standard and spherical tokamak discharges; (3) Neural network model of the Multi-Mode anomalous transport module; (4) Anomalous transport in KSTAR, JET, EAST, Alcator C-Mod and DIII-D discharges; (5) Theory for transport in magnetized plasmas; (6) Control-oriented modeling of the q-profile dynamic response in preparation for advanced scenario control in KSTAR and in EAST; (7) Modeling of edge harmonic oscillation in DIII-D QH mode discharges; (8) Elucidating plasma dynamics in Hasegawa-Wakatani turbulence by information geometry; (9) Non-linear Langevin and Fractional Fokker–Planck equations for anomalous diffusion by Levy stable processes; and (10) Investigation of the plasma shaping effects on the H-mode pedestal structure.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Prompt core confinement improvement across the L–H transition in DIII-D: Profile stiffness, turbulence dynamics, and isotope effect

Here, we elaborate on the nature of the prompt core confinement improvement observed at the L–H transition in DIII-D, which is a long-standing issue unsolved for more than two decades and can impact future fusion reactor performance. Dynamic transport analysis suggests the essential role of the profile stiffness for understanding the mechanism of the prompt core confinement improvement. Beam emission spectroscopy shows that transport reduction at the core cannot be explained only by the ion scale turbulence density fluctuation suppression. Properties of nonlocal confinement improvement across the L–H transition are experimentally assessed in hydrogen (H) and deuterium (D) plasmas. Prompt core confinement improvement is found to be more rapid in the lighter hydrogen isotope.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2013

Combining dynamic and static depth profiling in low energy ion scattering

The advantages of combining dynamic and static depth profiling in low energy ion scattering are demonstrated for an Si/SiO{sub x}/W/Al{sub 2}O{sub 3} ALD stack. Dynamic depth profiling can be used to calibrate static depth profiling. Energy losses of 152 and 215 eV/nm were found for 3 keV {sup 4}He{sup +} and 5 keV {sup 4}He{sup +} primary ions, respectively, for the experimental configuration used. This is in good agreement with the values used in the field. Static depth profiling can be used to recognize sputter artifacts in dynamic depth profiles.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Dynamics of straight vortex filaments in a Bose–Einstein condensate with the Gaussian density profile

The dynamics of interacting quantized vortex filaments in a rotating Bose–Einstein condensate existing in the Thomas–Fermi regime at zero temperature and obeying the Gross–Pitaevskii equation has been considered in the hydrodynamic “nonelastic” approximation. A noncanonical Hamilton equation of motion for the macroscopically averaged vorticity has been derived for a smoothly inhomogeneous array of filaments (vortex lattice) taking into account spatial nonuniformity of the equilibrium density of the condensate, which is determined by the trap potential. The minimum of the corresponding Hamiltonian describes the static configuration of the deformed vortex lattice against the preset density background. The condition of minimum can be reduced to a nonlinear second-order partial differential vector equation for which some exact and approximate solutions are obtained. It has been shown that if the condensate density has an anisotropic Gaussian profile, the equation of motion for the averaged vorticity has solutions in the form of a vector exhibiting a nontrivial time dependence, but homogeneous in space. An integral representation has also been obtained for the matrix Green function that determines the nonlocal Hamiltonian of a system of several quantized vortices of an arbitrary shape in a Bose–Einstein condensate with the Gaussian density. In particular, if all filaments are straight and oriented along one of the principal axes of the ellipsoid, we have a finitedimensional reduction that can describe the dynamics of the system of pointlike vortices against an inhomogeneous background. A simple approximate expression is proposed for the 2D Green function with an arbitrary density profile and is compared numerically with the exact result in the Gaussian case. The corresponding approximate equations of motion, describing the long-wavelength dynamics of interacting vortex filaments in condensates with a density depending only on transverse coordinates, have been derived.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Eco-driving Profile Optimization by Dynamic Programming for Battery Electric Vehicles

Although full automation has not yet been achieved, automated vehicles are a valid research area. Not only would automated vehicles provide ultimate driver convenience, but they would maximize energy efficiency by eliminating undesired human driving behaviors and optimally controlling the powertrain. From the perspective of control related to energy saving, speed profile optimization is important for improving system efficiency and satisfying passenger demands. This study employs Dynamic Programming (DP) to solve the constrained optimal problem for travel time, distance, and speed limit by exploring all possible control options. The solutions obtained by DP demonstrate consistent control patterns combining four control modes-acceleration, cruising, coasting, and braking, with cruising or coasting being selective depending on the boundary conditions. Further, this study introduces DP-based simulation results and attempts to provide comprehensive interpretations of the optimal policy by analyzing the essential factors that affect the control problem, including boundary conditions, road load, and powertrain characteristics. Based on these interpretations, the control concepts can be explained as the optimal policy selecting the best control option based on system efficiency and boundary conditions. The results of DP are compared with a human-like driver model to show that the optimal speed profiles can effectively reduce energy consumption.

Autonomous vehicles↗
DOE OSTI2015

In vivo cardiac glucose metabolism in the high-fat fed mouse: Comparison of euglycemic–hyperinsulinemic clamp derived measures of glucose uptake with a dynamic metabolomic flux profiling approach

Rationale: Cardiac metabolism is thought to be altered in insulin resistance and type 2 diabetes (T2D). Our understanding of the regulation of cardiac substrate metabolism and insulin sensitivity has largely been derived from ex vivo preparations which are not subject to the same metabolic regulation as in the intact heart in vivo. Studies are therefore required to examine in vivo cardiac glucose metabolism under physiologically relevant conditions. Objective: To determine the temporal pattern of the development of cardiac insulin resistance and to compare with dynamic approaches to interrogate cardiac glucose and intermediary metabolism in vivo. Methods and results: Studies were conducted to determine the evolution of cardiac insulin resistance in C57Bl/6 mice fed a high-fat diet (HFD) for between 1 and 16 weeks. Dynamic in vivo cardiac glucose metabolism was determined following oral administration of [U-{sup 13}C] glucose. Hearts were collected after 15 and 60 min and flux profiling was determined by measuring {sup 13}C mass isotopomers in glycolytic and tricarboxylic acid (TCA) cycle intermediates. Cardiac insulin resistance, determined by euglycemic–hyperinsulinemic clamp, was evident after 3 weeks of HFD. Despite the presence of insulin resistance, in vivo cardiac glucose metabolism following oral glucose administration was not compromised in HFD mice. This contrasts our recent findings in skeletal muscle, where TCA cycle activity was reduced in mice fed a HFD. Similar to our report in muscle, glucose derived pyruvate entry into the TCA cycle in the heart was almost exclusively via pyruvate dehydrogenase, with pyruvate carboxylase mediated anaplerosis being negligible after oral glucose administration. Conclusions: Under experimental conditions which closely mimic the postprandial state, the insulin resistant mouse heart retains the ability to stimulate glucose metabolism. - Highlights: • Insulin clamp was used to determine the evolution of cardiac insulin resistance. • Clamp measures were compared to a dynamic metabolomics approach. • The clamp revealed the presence of cardiac insulin resistance after 3 weeks of HFD. • Cardiac glucose metabolism was not affected by HFD during an oral glucose challenge.

60 APPLIED LIFE SCIENCES↗