Data-driven robust control of the plasma rotational transform profile and normalized beta dynamics for advanced tokamak scenarios in DIII-D
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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.
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.
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.
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Laboratory aging campaigns benchmark and elucidate the complex degradation behavior of lithium-ion batteries, and are critical not only for developing new battery chemistries and cell designs but also for engineering reliable battery management systems. Critically, these laboratory experiments aim to quantify and capture realistic aging mechanisms. In this study, we systematically compare dynamic discharge profiles representative of electric vehicle driving to the well-accepted constant-current profiles. Surprisingly, we discovered that dynamic discharge enhances lifetime substantially compared to constant current discharge. Specifically, for the same average current and voltage window, varying the dynamic discharge profile leads to an increase of up to 38 % in equivalent full cycles at end-of-life. Explainable machine learning reveals the importance of low-frequency current pulses as well as time-induced aging under these realistic discharge conditions. Our work quantifies the importance of evaluating new battery chemistries and designs with realistic load profiles, and highlights the opportunities to revisit our understanding of aging mechanisms at the chemistry, materials, and cell levels.
Large scale structures such as groups and clusters of galaxies show a universal, nearly linear entropy radial profile K(r). Using deprojected 16 clusters and 12 groups from the literature, we find that K∝r{sup 0.96±0.01}, consistent with the mean power-law index (0.9–1.1) of previous studies. A similarly good fit is given by a τ∝r{sup 0.72±0.01} ratio between cooling and free-fall times. Both profiles slightly flatten at small radii, as τ becomes of order unity. The entropy profile is usually attributed to self-similar shock accretion (shown to be inconsistent with the data), to non-standard heat conduction, or to turbulent heating. We argue that a dynamical mechanism is needed to sustain such a universal profile, oblivious to the temperature peak at the edge of the core and to the virial shock at the outskirts, and robust to the presence of ongoing cooling, merger, and active galactic nucleus activity. In particular, we show that such a profile can be naturally obtained in a spiral flow, which is likely to underlie most galaxy aggregates according to the ubiquitous spiral patterns and cold fronts observed. Generalizing a two-phase spiral flow model out to the virial radius surprisingly reproduces the thermal profile. A generalized Schwarzschild criterion indicates that observed spiral patterns must involve a convective layer, which may regulate the thermal profile.
Plasma fueling with high efficiency and deep injection is very important to enable fusion power performance requirements. It is a powerful and efficient way to study neutral transport dynamics and find methods of improving the fueling performance by doing large scale simulations. Two basic fueling methods, gas puffing (GP) and supersonic molecular beam injection (SMBI), are simulated and compared in realistic divertor geometry of the HL-2A tokamak with a newly developed module, named trans-neut, within the framework of BOUT++ boundary plasma turbulence code [Z. H. Wang et al., Nucl. Fusion 54, 043019 (2014)]. The physical model includes plasma density, heat and momentum transport equations along with neutral density, and momentum transport equations. Transport dynamics and profile evolutions of both plasma and neutrals are simulated and compared between GP and SMBI in both poloidal and radial directions, which are quite different from one and the other. It finds that the neutrals can penetrate about four centimeters inside the last closed (magnetic) flux surface during SMBI, while they are all deposited outside of the LCF during GP. It is the radial convection and larger inflowing flux which lead to the deeper penetration depth of SMBI and higher fueling efficiency compared to GP.
Purpose: The prepatient attenuator (or 'bowtie filter') in CT is used to modulate the flux as a function of fan angle of the x-ray beam incident on the patient. Traditional, static bowtie filters are tailored only for very generic scans and for the average patient. The authors propose a design for a dynamic bowtie that can produce a time-dependent piecewise-linear attenuation profile. This dynamic bowtie may reduce dynamic range, dose or scatter, but in this work they focus on its ability to reduce dynamic range, which may be particularly important for systems employing photon-counting detectors. Methods: The dynamic bowtie is composed of a set of triangular wedges. Each wedge is independently moved in order to produce a time-dependent piecewise-linear attenuation profile. Simulations of the bowtie are conducted to estimate the dynamic range reduction in six clinical datasets. The control of the dynamic bowtie is determined by solving a convex optimization problem, and the dose is estimated using Monte Carlo techniques. Beam hardening artifacts are also simulated. Results: The dynamic range is reduced by factors ranging from 2.4 to 27 depending on the part of the body studied. With a dynamic range minimization objective, the dose to the patient can be reduced from 6% to 33% while maintaining peak image noise. Further reduction in dose may be possible with a specific dose reduction objective. Beam hardening artifacts are suppressed with a two-pass algorithm. Conclusions: A dynamic bowtie producing a time-dependent, piecewise-linear attenuation profile is possible and can be used to modulate the flux of the scanner to the imaging task. Initial simulations show a large reduction in dynamic range. Several other applications are possible.
Protein reduction-oxidation (redox) modification is an important mechanism that allows microorganisms to sense environmental changes and initiate cellular responses. We have developed a quantitative chemical probe approach for live cell labeling of proteins that are sensitive to redox modifications. We utilize this in vivo strategy to identify 176 proteins undergoing ~5-10 fold dynamic redox change in response to nutrient limitation and subsequent replenishment in the photoautotrophic cyanobacterium, Synechococcus sp. PCC 7002. We detect redox changes in as little as 30 seconds after nutrient perturbation, and oscillations in reduction and oxidation for 60 minutes following the perturbation. Many of the proteins undergoing dynamic redox transformations participate in the major components for the production (photosystems and electron transport chains) or consumption (Calvin-Benson cycle and protein synthesis) of reductant and/or energy in photosynthetic organisms. Thus, our in vivo approach reveals new redox-susceptible proteins, in addition to validating those previously identified in vitro.
Terrestrial ecosystems can show sustained responses to stress events that may last for years after the initial perturbation. This phenomenon is referred to as legacy or memory and it emerges from a set of ecosystem processes that are poorly captured by Earth System and Land Surface Models. Consequently, these models struggle to predict the impact that extreme climate events have on surface energy, carbon and hydrological exchange once a stressor such as drought has relaxed or in response to repeated exposure to stress. In this project, we set out to test how the addition of dynamic root profiles in land surface models impact the capacity for Earth System Models, such as the Department of Energy’s E3SM, to capture realistic legacy effects. Observations have shown that vegetation shifts their root profiles during stress events to forage for water and these altered root profiles may take years to relax back to the initial state. We hypothesized that the alteration of the belowground root structures may be a source of terrestrial ecosystem legacy that is missing from models. To test this idea we undertook three core activities. (1) We developed a global-scale analysis of the impact of dynamic roots on ecosystem legacy building from a recently developed dynamic root module. (2) We developed new root dynamics in the DOE’s Energy Land Model (ELM) that allowed not only root profiles to shift their profile but also simultaneously alter carbon allocation to fine root pools. We then tested the impact of these new dynamics with intensive sensitivity analysis at four long-term AmeriFlux sites. (3) We undertook detailed isotopic analysis of tree rings from these AmeriFlux sites to assess ecophysiological and ecohydrological legacy to stress events that can be used to benchmark the sensitivity experiments with ELM. From these core activities, we report the following key findings. Firstly, on a global scale, the addition of dynamic roots led to chronically water-stressed ecosystems recovering faster to climate stress while wetter ecosystem showed enhanced legacy. This is because across ecosystems, stress events were almost universally associated with water shortages that led to the development of deeper root profiles. These deeper root profiles proved beneficial for recovery from drought stress. While the root dynamics did not universally improve the modeled representation of legacy it showed complex transient dynamics that emerge from the addition of dynamic roots. Secondly, the sensitivity analysis illustrated long term shifts in rooting depths away from the prescribed default profile suggesting that initializing of root profiles could benefit from spin-up simulations that converge on locally optimized root profiles. In addition, by enabling dynamic allocation some of the sites predicted unrealistically low allocation to roots (and high allocation to leaves). While these changes did not dramatically alter modeled gross primary productivity, they illustrated that without more sophisticated root processes in models, there is little penalty to dramatically disinvest in roots. Thirdly, the isotopic analysis of tree rings showed highly distinct legacy responses across species and sites. For example, T. canadensis showed reduced transpiration the year after stress events illustrated by sustained elevated $\delta^{18}$O. In contrast, A saccharum displayed elevated $\delta^{13}$C associated with reduced stomatal conductance in response to the previous years’ stress event. These geochemical signatures of legacy were present despite tree growth returning to normal the year after the stress. The results show the importance of species-level dynamics in legacy that are absent in modeling that assumes common traits within plant functional types. In summary, the work here established new avenues to explore root dynamics in models while illustrating how additional root processes are needed before dynamic carbon allocation can be implemented. Lastly, this project provided mentorship to a postdoctoral fellow, training for an early career scientist and multiple undergraduate students recruited from a minority serving institution.
Polyhydroxyalkanoates (PHAs) are versatile, biobased polyesters that are often targeted for use as degradable thermoplastic replacements for polyolefins. Given the substantial chemical diversity of PHA, their potential as cross-linked polymers could also enable similar platforms for reversible, degradable thermosets. In this work, we genetically engineered Pseudomonas putida KT2440 to synthesize poly(3-hydroxybutyrate-co-3-hydroxyundecenoate) (PHBU), which contains both 3-hydroxybutyrate and unsaturated 3-hydroxyundecenoate components. To reduce the brittleness of this polymer, we physically blended PHBU with the soft copolymer poly(3-hydroxydecanonate-co-3-hydroxyundecenoate) in mass ratios of 1:3, 1:1, and 3:1. Upon observing varying degrees of immiscibility by scanning electron microscopy, we installed dynamic boronic ester cross-links via thiol–ene click chemistry, which resulted in compatibilized dynamic thermoset blends ranging in hard, medium, and soft rubber or elastomer thermomechanical profiles. These dynamic thermoset blends were subjected to controlled biological degradation experiments in freshwater conditions, achieving timely mass loss despite the cross-linked architectures. Overall, this work highlights a two-component platform for the production of degradable and reprocessable dynamic thermoset blends suitable for several classes of cross-linked polymer technologies from tailored, biological PHA copolymers.
Integrated control of the toroidal current density profile, or alternatively the q-profile, and plasma stored energy is essential to achieve advanced plasma scenarios characterized by high plasma confinement, magnetohydrodynamics stability, and noninductively driven plasma current. The q-profile evolution is closely related to the evolution of the poloidal magnetic flux profile, whose dynamics is modeled by a nonlinear partial differential equation (PDE) referred to as the magnetic-flux diffusion equation (MDE). The MDE prediction depends heavily on the chosen models for the electron temperature, plasma resistivity, and non-inductive current drives. To aid control synthesis, control-oriented models for these plasma quantities are necessary to make the problem tractable. However, a relatively large deviation between the predictions by these control-oriented models and experimental data is not uncommon. For this reason, the electron temperature, plasma resistivity, and non-inductive current drives are modeled for control synthesis in this work as the product of an “uncertain” reference profile and a nonlinear function of the different auxiliary heating and current-drive (H&CD) source powers and the total plasma current. The uncertainties are quantified in such a way that the family of models arising from the modeling process is able to capture the q-profile and plasma stored energy dynamics from a typical EAST shot. A control-oriented nonlinear PDE model is developed by combining the MDE with the “uncertain” models for the electron temperature, plasma resistivity, and non-inductive current drives. This model is then rewritten into a control framework to design a controller that is robust against the modeled uncertainties. The resulting controller utilizes EAST's H&CD powers and total plasma current to regulate the q profile and plasma stored energy even when mismatches between modeled and actual dynamics are present. The effectiveness of the controller is demonstrated through nonlinear simulations.
We report on a novel combined laser pulse shaping and dynamic wavelength encoding capability based on a simple architecture implementing direct space to time mapping. There are several potential applications that can be enabled by the ability to control the instantaneous intensity or wavelength of an optical waveform on a picosecond-to-nanosecond timescale. To our knowledge, no known methods can access this temporal regime with a practical architecture. Here, we demonstrate an extension of the Space–Time Induced Linearly Encoded Transcription for Temporal Optimization (STILETTO) technique that can generate optical waveforms with a programmable instantaneous wavelength vs. time. We experimentally demonstrate the technique by generating self-gated spectrograms and show that it can encode dynamic wavelength vs time profiles at timescales not achievable by any other known method.
Numerical simulations of hot accretion flow, both hydrodynamical and magnetohydrodynamical, have shown that the mass accretion rate decreases with decreasing radius; consequently, the density profile of accretion flow becomes flatter than in the case of a constant accretion rate. This result has important theoretical and observational implications. However, because of technical difficulties, the radial dynamic range in almost all previous simulations usually spans at most two orders of magnitude. This small dynamical range, combined with the effects of boundary conditions, makes the simulation results suspect. In particular, the radial profiles of density and inflow rate may not be precise enough to be used to compare with observations. In this paper, we present a ''two-zone'' approach to expand the radial dynamical range from two to four orders of magnitude. We confirm previous results and find that from r{sub s} to 10{sup 4} r{sub s} the radial profiles of accretion rate and density can be well described by M-dot (r){proportional_to}r{sup s} and {rho}{proportional_to}r {sup -p}. The values of (s, p) are (0.48, 0.65) and (0.4, 0.85) for the viscous parameters {alpha} = 0.001 and {alpha} = 0.01, respectively. More precisely, the accretion rate is constant (i.e., s = 0) within {approx}10r{sub s}, but beyond 10r{sub s} we have s = 0.65 and 0.54 for {alpha} = 0.001 and 0.01, respectively. We find that the values of both s and p are similar in all numerical simulation works irrespective of whether a magnetic field is included or not and what kind of initial conditions are adopted. Such an apparently surprising ''common'' result can be explained by the most recent version of the adiabatic inflow-outflow model. The density profile we obtain is in good quantitative agreement with that obtained from the detailed observations and modeling of Sgr A* and NGC 3115. The origin and implications of such a profile will be investigated in a subsequent paper.
Recent trends of CMOS scaling and use of large last level caches (LLCs) have led to significant increase in the leakage energy consumption of LLCs and hence, managing their energy consumption has become extremely important in modern processor design. The conventional cache energy saving techniques require offline profiling or provide only coarse granularity of cache allocation. We present FlexiWay, a cache energy saving technique which uses dynamic cache reconfiguration. FlexiWay logically divides the cache sets into multiple (e.g. 16) modules and dynamically turns off suitable and possibly different number of cache ways in each module. FlexiWay has very small implementation overhead and it provides fine-grain cache allocation even with caches of typical associativity, e.g. an 8-way cache. Microarchitectural simulations have been performed using an x86-64 simulator and workloads from SPEC2006 suite. Also, FlexiWay has been compared with two conventional energy saving techniques. The results show that FlexiWay provides largest energy saving and incurs only small loss in performance. For single, dual and quad core systems, the average energy saving using FlexiWay are 26.2%, 25.7% and 22.4%, respectively.
The implosion uniformity of a directly driven spherical inertial confinement fusion capsule is considered within the context of the Laser Mégajoule configuration. Two-dimensional (2D) hydrodynamic simulations have been performed assuming irradiation with two laser beam cones located at 49° and 131° with respect to the axis of symmetry. The laser energy deposition causes an inward shock wave whose surface is tracked in time, providing the time evolution of its non-uniformity. The illumination model has been used to optimize the laser intensity profiles used as input in the 2D hydro-calculations. It is found that a single stationary laser profile does not maintain a uniform shock front over time. To overcome this drawback, it is proposed to use two laser profiles acting successively in time, in order to dynamically stabilize the non-uniformity of the shock front.