Transition Threshold Research Articles

Understanding price momentum, market fluctuations, and crashes: insights from the extended Samuelson model

Although momentum strategies result in abnormal profitability, thereby challenging the efficient market hypothesis (EMH), concerns persist regarding their reliability due to their significant volatility and susceptibility to substantial losses. In this study, we investigate the limitations of these strategies and propose a solution. Our literature review reveals that the volatile profits are due to statistical analyses that assume the persistence of past patterns, leading to unreliable results in out-of-sample scenarios when underlying mechanisms evolve. Statistical analysis, the predominant method in financial economics, often proves inadequate in explaining market fluctuations and predicting crashes. To overcome these limitations, a paradigm shift towards dynamic approaches is essential. Drawing inspiration from three groundbreaking economists, we introduce the extended Samuelson model (ESM), a dynamic model that connects price changes to market participant actions. This paradigm transition uncovers several significant findings. First, timely signals indicate momentum initiations, cessations, and reversals, validated using S&P 500 data from 1999 to 2023. Second, ESM predicts the 1987 Black Monday crash weeks in advance, offering a new perspective on its underlying cause. Third, we classify sequential stock price data into eight distinct market states, including their thresholds for transitions, laying the groundwork for market trend predictions and risk assessments. Fourth, the ESM is shown to be a compelling alternative to EMH, offering potent explanatory and predictive power based on a single, realistic assumption. Our findings suggest that ESM has the potential to provide policymakers with proactive tools, enabling financial institutions to enhance their risk assessment and management strategies.

Green behavior propagation analysis based on statistical theory and intelligent algorithm in data-driven environment.

The correlation between green behavior and energy efficiency is growing due to the heightened focus on energy efficiency among individuals. This paper introduces a three-layer network model to analyze the relationships among information diffusion, awareness and green behavior spreading. We have analyzed the probability tree of state transfer across 12 states by using Microscopic Markov Chain Approach (MMCA) and derived the state transfer equations for each state to compute the state transition threshold. In addition, we use the reaction-diffusion system to model the interaction between space and time changes for each state in the green behavior propagation layer. The equilibrium point of the system is defined, and the criteria for Turing bifurcation are identified. The optimal control approach achieves parameter identification, and this study validates the theory through several numerical simulations. Meanwhile, the effectiveness of parameter identification based on the convolutional neural network (CNN) and optimal control is compared. The data on China's electrical energy generation is predicted and compared by using three neural networks and an autoregressive integrated moving average (ARIMA) model. Further, considering clean energy generation as a green behavior, we fit the data on the percentage of clean energy generation by applying a Microscopic Markov Chain model and a reaction-diffusion system.

Effect of SiO2 monocrystalline substrate orientation on the crystal structure and properties of VO2 film

The VO2 films were deposited on the AT-, X-, Y- and Z-SiO2 monocrystalline substrates with the magnetron sputtering. The effects of the substrate crystal planes, (011), (2—10), (100) or (001), on the crystal structure, surface morphology, optical properties and phase transformation characteristics of the VO2 film were investigated. The crystal structure differences among the VO2 films deposited on the four substrates were attributed to the lattice mismatch between the SiO2 monocrystalline substrate and the VO2 film, which led to the generation of internal stress within the VO2 film, causing the VO2 to present a diversity of crystal plane and phase at the interface. Among them, the VO2 film exhibited the M-phase on the AT- and X-SiO2 substrates, while a mixture of the M-phase and the R-phase on the Z- and Y-SiO2 substrates. The complex crystal structure resulted in the various surface morphologies, the VO2 particles on the Z- and Y-SiO2 substrates presented a smaller size and gap, as well as a more uniform distribution than those on the AT- and X-SiO2 substrates. All the VO2 films exhibited the metal-insulator phase transition during both the thermal cycling and the laser irradiation cycling processes. The Z-SiO2 substrate had a positive effect on the phase transition performance of the VO2 film, which got a thermochromic phase transition threshold of 64.62 ℃ and an infrared switching ratio of 78.99% at the wavelength of 2500nm. And its photoinduced phase transition threshold was 36.43W/cm², and its infrared switching ratio reached 59.00% under the 1989 nm laser irradiation.

Quantum and complex-valued hybrid networks for multi-principal element alloys phase prediction.

This study introduces a hybrid network model for phase classification, integrating quantum networks and complex-valued neural networks. This architecture uses elemental composition as its only input, eliminating complex feature engineering. Parameterized quantum networks handle sparse elemental data and convert data from real to complex domains, increasing information dimensionality. Complex-valued neural networks process data in the complex domain, significantly reducing information loss during transitions. The experimental results show that the hybrid model achieves a phase classification accuracy of 94.93%, outperforming the best machine learning model by 2.27% and the quantum model by 8.67%. Precision, recall, and F1-score are also excellent at 0.9494, 0.9493, and 0.9500, respectively. Additional tests on phase transitions in alloys confirm the model's robust generalization, identifying transition thresholds at 0.46 and 0.88, closely matching the 0.45 and 0.88 reported in related studies.

Simulation of β-induced Alfvén eigenmode instabilities and mode transition for HL-3 hybrid scenario

Abstract Kinetic-magnetohydrodynamic hybrid simulation is performed to investigate the Alfvén eigenmode (AE) and fishbone/fishbone-like instabilities excited by neutral beam injection (NBI) deposited energetic particles (EPs) for HL-3 hybrid scenario. The hybrid scenario is characterized by a flat q-profile in the core due to off-axis electron cyclotron current drive (ECCD). Nonlinear simulation with multiple toroidal mode numbers indicates that the n=2 β-induced AE (BAE) is excited initially in the linear stage and the n=1 fishbone has the highest nonlinear saturation level. EP distribution is modified only slightly in both real and velocity space from its initial state because of a narrow mode structure near the axis. Focusing on the n=2 mode, sensitivity analysis indicates that mode activity and transition depend on the EP pressure, injected energy and q-profile. The dominant unstable mode deviates from fishbone-like mode to BAE by raising EP pressure, and from BAE to toroidicity-induced AE (TAE) by raising NBI injected energy. The mechanism is interpreted through resonant condition and corresponding transition threshold is exhibited. In addition, extending the flat shear region could increase the BAE width, resulting in stronger EP transport. Furthermore, nonlinear simulation by only considering n=1 and n=2 modes demonstrates that the low-energy EPs, as an intermediate, gain energy from n=2 mode, which subsequently transfers energy to the n=1 mode through resonant interaction.

Optimized Trajectory Unraveling for Classical Simulation of Noisy Quantum Dynamics.

The dynamics of open quantum systems can be simulated by unraveling it into an ensemble of pure state trajectories undergoing nonunitary monitored evolution, which has recently been shown to undergo measurement-induced entanglement phase transition. Here, we show that, for an arbitrary decoherence channel, one can optimize the unraveling scheme to lower the threshold for entanglement phase transition, thereby enabling efficient classical simulation of the open dynamics for a broader range of decoherence rates. Taking noisy random unitary circuits as a paradigmatic example, we analytically derive the optimum unraveling basis that on average minimizes the threshold. Moreover, we present a heuristic algorithm that adaptively optimizes the unraveling basis for given noise channels, also significantly extending the simulatable regime. When applied to noisy Hamiltonian dynamics, the heuristic approach indeed extends the regime of efficient classical simulation based on matrix product states beyond conventional quantum trajectory methods. Finally, we assess the possibility of using a quasi-local unraveling, which involves multiple qubits and time steps, to efficiently simulate open systems with an arbitrarily small but finite decoherence rate.

Photonic Bose-Einstein Condensation in the Continuum Limit.

We investigate the properties of the photon Bose-Einstein condensate in the limit of small mode spacing. Alongside the well-known threshold of the phase transition at large mode spacings, we find an emergence of a second threshold for sufficiently small mode spacings, defining the crossover to a fully condensed state. Furthermore, we present our findings for the mode occupations in the precondensate or supercooling region towards the continuum limit.

First-Principles Molecular Dynamics Analysis of Hydride-Ion Diffusion in Ba1.75LiH2.7O0.9

Introduction In Solid State Ionics, a negatively charged hydrogen, that is, hydride (H–), diffuses in solids and contributes to ionic conduction had been a long-standing problem because it is difficult to distinguish between H– and other ions (O2–, H+, etc.). In 2016, it is shown that the ion conductivity of La2LiHO3 can be attributed to pure H– conduction, not mixed with electron, by demonstrating the electrochemical reaction of H– charge transfer in an all-solid-state TiH2/La2LiHO3/Ti cell.1 Since the milestone study, the material investigation of hydride-ion conductors has been actively conducted because of their potential to enable high-performance electrochemical device based on hydrogen. Recently, we reported that the ionic conductivity of Ba1.75LiH2.7O0.9 shows 10–2 S·cm–1 at around 300 °C after a structural phase transition.2 Their results show conductivity jump at 300 ℃ and ultra-low activation energy above the transition temperature, but this behavior has not been understood correctly. In this study, we conduct first-principles molecular dynamics (FPMD) simulations to clarify the origin of high H– conductivity and the mechanism of H– conduction in Ba1.75LiH2.7O0.9. The results of H– diffusion coefficients are compared with quasi-elastic neutron scattering (QENS) analysis. We further discuss about sublattice melting and H– collective motion in Ba1.75LiH2.7O0.9. Methods and Models K2NiF4 type structures of Ba1.75LiH2.7O0.9 at low- (β) and high-temperature (δ) phases obtained by neutron diffraction (ND) data2 were adopted as crystal structure models used in FPMD simulations. As the certain anion (and cation) sites is partially occupied by H and a small amount of O (and Ba) according to Rietveld analysis, 2×4×1 and 4×4×1 supercells were employed to reproduce the occupancy ratios to some extent by arranging H, O, and Ba atoms and their vacancy defects. It is noted that the high ionic conductivity of Ba1.75LiH2.7O0.9 is observed at an intermediate (γ) phase, and the crystallographic difference between β and γ phases can be attributed to the partial occupancy ratios of equatorial anion sites. Therefore, we consider that the phase transition from β to γ could be included in FPMD simulations at high temperatures even if we consider only the structures of β and δ phases. FPMD simulations in thermal equilibrium conditions at the temperatures of 500, 700, 900, 1100 K were performed for several hundred ps. Then, the self-diffusion coefficients, Lindemann indices (the indicators of liquid-solid transition), and van Hove time correlation functions of H were calculated from the atom trajectories of FPMD simulations. Results We obtained the self-diffusion coefficient Dab and Dc , which decomposed in ab plane and c-axis direction, from the mean square displacements (MSD) of H atoms in the β and δ phases. The diffusion process in ab plane corresponds to the H– hopping among equatorial sites. The value of diffusion coefficients Dab estimated by the extrapolation under high temperature conditions (700, 900, 1100 K, we excluded the simulation of 500 K because of the insufficient number of trajectory ensembles) are consistent with that obtained by the QENS analysis (3–4 × 10–7 cm2·s–1).2 However, the activation energy E a estimated from calculated Dab is 0.50–0.51 eV for both phases, which values are different from the estimated values from experimental ionic conductivity: E a =1.0 eV (β phase) and 0.0 eV (γ phase). From the comparison, it is indicated that the rate-determining process of conductivity is not the ab-plane diffusion of H–, but rather to the c-axis diffusion, ion movement at crystallite interfaces, or collective motions that cannot be accounted for our short time scale simulations. Furthermore, the Lindemann indices were calculated for Ba, Li, O, and H atoms. We found that the Lindemann index of H exceeds the threshold for a solid-liquid transition at high temperatures above 700 K, which suggests the sublattice melting of anion equatorial sites and the superionic conduction of H– in Ba1.75LiH2.7O0.9. In the presentation, we will further discuss the collective motion and diffusion mechanism of H− from the time correlation function.

The numerical analysis of complete and partial electrocoalescence in the droplet-layer system employing the sharp interface technique for multiphase-medium simulation

In this paper, the coalescence of a drop of water suspended in oil with a layer of water under the influence of a constant electric field is numerically investigated. Unlike most existing studies, the calculations are based on the application of the arbitrary Lagrangian-Eulerian method (ALEM), also called the moving mesh method, which belongs to the class of methods for modeling two-phase liquids with a sharp interface. Using this approach made it possible to avoid a false "escape" of the surface charge from the interface, which often occurs when using methods involving a diffuse interface. Despite the fact that ALEM does not allow describing topology changes by default, a numerical model was implemented in which the calculation is divided into three parts: the convergence of the drop and the layer before the moment of touch; the manual construction of the bridge at the moment of touch; the union of the drop and the layer. The developed model allowed us to obtain three possible modes of this process: complete coalescence, partial coalescence and a mode of stretching which has not practically been considered yet. The dependence of the volume of the separated secondary droplet on the size of the initial droplet and the average intensity of the applied electric field is obtained. The model showed good quantitative agreement with experimental studies. It has been shown that generally, the spots where the bridge and the neck are formed in case of partial coalescence do not coincide. A map of coalescence modes was obtained, i.e., the dependence of the transition threshold from coalescence to partial coalescence and from partial coalescence to stretching regime in a wide range of radii of initial droplets and electric field strengths. It has been shown that there is a maximum field strength at which droplets of any size merge with the layer. This map makes it possible to predict the coalescence regime in electrocoalescer. The proposed modeling technique can be used to calculate electrocoalescence modes at various values of the main parameters, which will help to optimize electrocoalescers at the design stage.

Study on the nano-cutting mechanism of monocrystalline silicon material with an amorphous layer by molecular dynamics simulations

Monocrystalline silicon is prone to brittle fracture during the nano-cutting process. Surface modification through ion implantation to create an amorphous layer on monocrystalline silicon significantly enhances its processability. This paper conducted molecular dynamics simulations to deeply reveal the nanometric cutting mechanism for monocrystalline silicon with an amorphous layer. The influence of the amorphous layer on material removal, subsurface damage, cutting forces, stress distribution, and temperature profiles was analyzed and thoroughly discussed. The calculating results reveal that primary material removal mode transitions from shearing to extrusion under the influence of the amorphous layer. The presence of an amorphous layer can efficiently reduce stress concentration and defects in the nanometric machining process. When the thickness of the amorphous layer equals the cutting depth of the tool, subsurface damage is reduced to approximately 2 nm, indicating that an optimal surface quality is achieved. When the thickness of the amorphous layer reaches more than cutting depth, the hydrostatic stress of the monocrystalline silicon part is significantly lower than the phase transition threshold of 12 GPa, which greatly reduces the occurrence of phase transition. Furthermore, the formation and evolution of shear bands are the primary reasons for the fluctuations in cutting force. The cutting temperature is closely related to structural transformations. The heat generated by shear slip in monocrystalline silicon material is higher than the heat generated by plastic deformation of material in the amorphous layer. Moreover, the heat energy produced by plastic deformation of amorphous layer atoms exceeds that generated by structural transformation of monocrystalline silicon atoms. This work reveals the nanometric cutting behavior of the monocrystalline silicon material with amorphous layer surfaces based on phase transformation. It can provide effective references for the preparation of amorphous layer thickness and selection of cutting parameters in nanometric cutting process of the monocrystalline silicon with amorphous layer surfaces.

Influence of electron cyclotron current drive on the pressure crashes caused by the 2/1 double tearing modes

Abstract A module with self-consistent evolution of driven current is developed and coupled with the resistive-MHD equations in the three-dimensional, toroidal, and nonlinear simulation code (CLT). The driven current equation is solved with a second-order accuracy symmetric scheme, which exhibits good conservation properties. With the new module, we find that the driven current can self-consistently concentrate inside the magnetic island when the parallel diffusion of the driven current is sufficiently large. The efficiency of the driven current on tearing mode suppression will then be much higher than those with stationary distributions. With the new module, the influence of electron cyclotron current drive (ECCD) on the nonlinear evolution of the 2/1 double tearing modes (DTMs) is investigated. When co-ECCD deposits on the outer resonant surface, the local magnetic shear is reduced, and the growth rates of the DTMs decrease; if ctr-ECCD deposits on the outer resonant surface, the local magnetic shear increases, and the DTMs become more unstable. However, things will be different if ECCD deposits on the inner resonant surface since the local magnetic shear is negative. The co-ECCD deposited on the inner resonant surface increases the negative shear and then promotes the growth of the DTMs; while the ctr-ECCD suppresses the DTMs. It is also found that the off-axis and central pressure crashes associated with the 2/1 DTMs can be converted to each other by properly depositing the driven current. To convert a central crash to an off-axis crash, the co-ECCD should be deposited on the outer resonant surface, or the ctr-ECCD deposited on the inner resonant surface. While, the co-ECCD should be deposited on the inner rational surface, or the ctr-ECCD deposited on the outer rational surface to convert an off-axis crash to a central crash. The co- or ctr-ECCD should be larger than a threshold for such transitions, and the threshold value is mainly determined by the location of the inner resonant surface.

Plasma opacity induced by laser-driven movement of background ions

Abstract The transition threshold from relativistically transparent regime to opaque regime in the interaction of an ultra-intense laser pulse and a bulk plasma with mobile background ions is investigated. The threshold corresponds to the onset of laser hole-boring. We show that for an ultra-intense laser, the threshold depends on the ion composition of the plasma, and the corresponding plasma density is significantly lower than that with ion immobile plasma. These are supported by 1D PIC simulations by using hydrogen plasma and fully ionized carbon plasma. The movement of background ions modifies the dynamics and distribution of electrons in the plasma, which results in the Doppler-red-shift of the incident laser and the increase of the effective plasma density. An intuitive model, which gives the dependence of the transparency-opaqueness threshold on laser intensity and frequency, as well as the ion composition, is established. It is tested by multi-dimensional PIC simulations with hydrogen plasma.

On learning sparse linear models from cross samples

The sample complexity of a sparse linear model where samples are dependent is studied in this paper. We consider a specific dependency structure of the samples which arises in some experimental designs such as drug sensitivity studies, where two sets of objects (drugs and cells) are sampled independently, and after crossing (making all possible combinations of drugs and cells), the resulting output (efficacy of drugs) is measured. We call these types of samples as “cross samples”. The dependency among such samples is strong, and existing theoretical studies are either inapplicable or fail to provide realistic bounds. We aim at analyzing the performance of the Lasso estimator where the underlying distributions are mixtures of Gaussians and the data dependency arises from the crossing procedure. Our theoretical results show that the performance of the Lasso estimator in case of cross samples follows that of the i.i.d. samples with differences in constant factors. Through numerical results, we observe a phase transition: When datasets are too small, the error for cross samples is much larger than for i.i.d. samples, but once the size is large enough, cross samples are nearly as useful as i.i.d. samples. Our theoretical analysis suggests that the transition threshold is governed by the level of sparsity of the true parameter vector being estimated.

Percolation Transitions in Edge-Coupled Interdependent Networks with Reinforced Inter-Layer Links.

Prior research on cascading failures within interdependent networks has predominantly emphasized the coupling of nodes. Nevertheless, in practical networks, interactions often exist not just through the nodes themselves but also via the connections (edges) linking them, a configuration referred to as edge-coupled interdependent networks. Past research has shown that introducing a certain percentage of reinforced nodes or connecting edges can prevent catastrophic network collapses. However, the effect of reinforced inter-layer links in edge-coupled interdependent networks has yet to be addressed. Here, we develop a theoretical framework for studying percolation models in edge-coupled interdependent networks by introducing a proportion of reinforced inter-layer links and deriving detailed expressions for the giant and finite components and the percolation phase transition threshold. We find that there exists a required minimum proportion of the reinforced inter-layer links to prevent abrupt network collapse, which serves as a boundary to distinguish different phase transition types of a network. We provide both analytical and numerical solutions for random and scale-free networks, demonstrating that the proposed method exhibits superior reinforcement efficiency compared to intra-layer link reinforcement strategies. Theoretical analysis, simulation results, and real network systems validate our model and indicate that introducing a specific proportion of reinforced inter-layer links can prevent abrupt system failure and enhance network robustness in edge-coupled interdependent networks.

Durability of output-dependent QRS transition and left bundle branch capture in left bundle branch area pacing

BackgroundAlthough output-dependent QRS transition is a specific indicator that confirms left bundle branch (LBB) capture during left bundle branch area pacing (LBBAP), its durability remains unclear. ObjectiveThe purpose of this study was to evaluate the presence of output-dependent QRS transition and capture thresholds of the LBB and left ventricular septal myocardium immediately and up to 1 year after the LBBAP procedure. MethodsWe enrolled 129 patients with successful LBBAP who were available for 1-year follow-up postoperatively. Threshold testing was performed immediately after LBBAP on postoperative day 0 (POD-0) and after 3 days (POD-3), 6 months (POD-180), and 1 year (POD-360). ResultsOutput-dependent QRS transition persisted in 64 patients (88%) on POD-360, from among the 73 patients with output-dependent QRS transition on POD-0. In contrast, 55 of 56 patients without QRS transition on POD-0 (98%) did not exhibit QRS transition thereafter. LBB thresholds were slightly elevated on POD-360, albeit without statistical significance, compared with those on POD-0 (1.22 ± 1.00 V vs 1.43 ± 1.29 V at 0.4 ms; P = .26). The LBB thresholds increased by ≥1.5 V in 7 patients (11%). However, in 93% of patients with an LBB threshold of ≤2.5 V on POD-0, LBB capture was maintained at 2.5 V on POD-360. Left ventricular septal thresholds were similar on POD-0 and POD-360 (0.81 ± 0.36 V vs 0.83 ± 0.24 V; P > .99) and did not increase by ≥1.5 V in any patient. ConclusionOutput-dependent QRS transitions were highly reproducible after implantation. Furthermore, LBB thresholds remained stable in most cases during the first postoperative year.

Ground-based MAX-DOAS observations of tropospheric formaldehyde and nitrogen dioxide: Insights into ozone formation sensitivity

Tropospheric profiles of HCHO, NO2, and O3 are important for analyzing ozone formation mechanism. In this study, ground-based multi-axis differential optical absorption spectroscopy (MAX-DOAS), light detection and ranging (LIDAR), and in-situ measurements were simultaneously performed to diagnose ozone formation sensitivity at the Heshan Observatory in the Pearl River Delta (PRD) region from September to end October 2019. The profiles of tropospheric HCHO and NO2 were retrieved from MAX-DOAS measurements using an optimal estimation method. The retrieved surface HCHO and NO2 results were validated with 2,4-dinitrophenylhydrazine (DNPH) and Thermo 42i measurements, and the correlation coefficients (R) were 0.78 and 0.81, respectively. The retrieved tropospheric vertical column densities (VCDs) of HCHO and NO2 were compared with TROPOMI measurements, and the correlation coefficients (R) were 0.68 and 0.87, respectively. In addition, MAX-DOAS and LIDAR measurements were combined to diagnose a typical planetary boundary layer (PBL) ozone pollution episode from September 28 to October 10, 2019; this episode was analyzed using HCHO/NO2 ratio as an indicator and was found to be dominated by the VOC-sensitive regime. Moreover, the regime transition of ozone formation sensitivity was calculated using the surface HCHO/NO2 ratio and increased O3 from the MAX-DOAS and Thermo 49i measurements, with transition thresholds of 1.43 and 1.78, respectively. Based on this definition, the ozone formation sensitivity at Heshan Observatory varied from VOC-sensitive (< 0.2 km and > 0.8 km) to NOx-sensitive (0.3–0.7 km) to VOC-NOx-sensitive (0.2–0.3 km and 0.7–0.8 km). The results improve our understanding of ozone formation sensitivity in the PRD region.

Antiferromagnetic liquid-crystal suspensions of goethite nanorods: three mechanisms of magnetic field influence on orientational structure.

The study looks into magnetically induced orientational transitions in suspensions of goethite nanorods based on a nematic liquid crystal. The study considers magnetically compensated suspension, which is a liquid-crystal analogue of an antiferromagnet. Unlike conventional magnetic particles, goethite nanorods have a remanent magnetic moment directed along the long axis of the particle and also they have negative diamagnetic anisotropy. Thus, it can be claimed that liquid-crystal composites of goethite nanorods have three mechanisms of interaction with an external magnetic field. The first two mechanisms are originally quadrupolar and are related to diamagnetic susceptibility anisotropies of liquid-crystal matrix and impurity goethite nanorods. The third mechanism is a dipolar one and is due to a remanent longitudinal magnetic moment of each dispersed particle. The magnetic-field-induced birefringence is used to show that the presence of three competing orientational mechanisms of interaction with an external magnetic field can both increase and decrease the Fréedericksz transition threshold compared to a pure liquid crystal. Diagrams of orientational phases of the suspension were constructed, and cases of various orientational mechanism predominance were analysed. Besides, a representation of the free energy of the suspension near the Fréedericksz transition in the form of the Landau expansion was obtained. This made it possible to establish that the Fréedericksz transition can occur as a phase transition of both the first and second order.

Helium plasma operations on ASDEX Upgrade and JET in support of the non-nuclear phases of ITER

For its initial operational phase, ITER has until recently considered using non-nuclear hydrogen (H) or helium (He) plasmas to keep nuclear activation at low levels. To this end, the Tokamak Exploitation Task Force of the EUROfusion Consortium carried out dedicated experimental campaigns in He on the ASDEX Upgrade (AUG) and JET tokamaks in 2022, with particular emphasis put on the ELMy H-mode operation and plasma-wall interaction processes as well as comparison to H or deuterium (D) plasmas. Both in pure He and mixed He + H plasmas, H-mode operation could be reached but more effort was needed to obtain a stable plasma scenario than in H or D. Even if the power threshold for the LH transition was lower in He, entering the type-I ELMy regime appeared to require equally much or even more heating power than in H. Suppression of ELMs by resonant magnetic perturbations was studied on AUG but was only possible in plasmas with a He content below 19%; the reason for this unexpected behaviour remains still unclear and various theoretical approaches are being pursued to properly understand the physics behind ELM suppression. The erosion rates of tungsten (W) plasma-facing components were an order of magnitude larger than what has been reported in hydrogenic plasmas, which can be attributed to the prominent role of He2+ ions in the plasma. For the first time, the formation of nanoscale structures (W fuzz) was unambiguously demonstrated in H-mode He plasmas on AUG. However, no direct evidence of fuzz creation on JET was obtained despite the main conditions for its occurrence being met. The reason could be a delicate balance between W erosion by ELMs, competition between the growth and annealing of the fuzz, and coverage of the surface with co-deposits.

Investigation of the tradeoffs between tracking performance and energetics in heterogeneous variable recruitment fluidic artificial muscle bundles

In traditional hydraulic robotics, actuators must be sized for the highest possible load, resulting in significant energy losses when operating in lower force regimes. Variable recruitment fluidic artificial muscle (FAM) bundles offer a novel bio-inspired solution to this problem. Divided into individual MUs, each with its own control valve, a variable recruitment FAM bundle uses a switching control scheme to selectively bring MUs online according to load demand. To date, every dynamic variable recruitment study in the literature has considered homogeneous bundles containing MUs of equal size. However, natural mammalian muscle MUs are heterogeneous and primarily operate based on Henneman's size principle, which states that MUs are recruited from smallest to largest for a given task. Is it better for a FAM variable recruitment bundle to operate according to this principle, or are there other recruitment orders that result in better performance? What are the appropriate criteria for switching between recruitment states for these different recruitment orders? This paper seeks to answer these questions by performing two case studies exploring different bundle MU size distributions, analyzing the tradeoffs between tracking performance and energetics, and determining how these tradeoffs are affected by different MU recruitment order and recruitment state transition thresholds. The only difference between the two test cases is the overall force capacity (i.e. total size) of the bundle. For each test case, a Pareto frontier for different MU size distributions, recruitment orders, and recruitment state transition thresholds is constructed. The results show that there is a complex relationship between overall bundle size, MU size distributions, recruitment orders, and recruitment state transition thresholds corresponding to the best tradeoffs change along the Pareto frontier. Overall, these two case studies validate the use of Henneman's Size Principle as a variable recruitment strategy, but also demonstrate that it should not be the only variable recruitment method considered. They also motivate the need for a more complex variable recruitment scheme that dynamically changes the recruitment state transition threshold and recruitment order based on loading conditions and known system states, along with a co-design problem that optimizes total bundle size and MU size distribution.

Scale effects on rotating detonation rocket engine operation

Rotating detonation rocket engines are propulsive devices employing detonation waves moving circumferentially around an annular channel that consume axially fed propellants. Theoretically, this provides benefits with respect to combustion pressure gain and thermodynamic efficiency when compared to deflagration-based combustors. To facilitate size scaling of these devices, the relationships between geometric parameters, performance, and wave dynamics have been investigated with gaseous methane-oxygen propellant. Empirical relations were derived between combustor geometry, fueling conditions, and engine operation, as well as correlation to thermodynamic parameters calculated with chemical kinetics codes. The radius of curvature effects were explored in annular combustors having outer diameters of 25 mm, 51 mm, and 76 mm with a fixed gap width of 5 mm. The injectors were scaled to have same oxidizer-to-fuel injector port area ratio, impingement distance, and injector-to-gap area ratio. Larger combustors had higher wave counts during operation at a given mass flux and equivalence ratio. Combustor axial pressures were found to be more dependent on propellant mass flux and equivalence ratio than geometry. Mass flux and the inner-to-outer radius ratio, the latter of which was related to other geometric ratios, dictated the operating mode transition thresholds and the number of resulting waves, respectively.