Dynamic scaling characteristics of single-phase natural circulation based on different strain transformations

To understand the dynamical system scaling(DSS)analysis theory,the applicability of DSSβ-andω-strain transformation methods for the scaling analysis of complex loops was explored.A simplified model consisting of two loops was established based on the primary and secondary sides of a nuclear reactor,andβ-andω-strain transformation methods were used to ana-lyze the single-phase natural circulation in the primary circuit.For comparison with the traditional method,simplified DSSβ-andω-strain methods were developed based on the standard scaling criterion.The strain parameters in these four methods were modified to form multiple groups of scaled-down cases.The transient process of the natural circulation was simulated using the Relap5 code,and the variation in the dynamic flow characteristics with the strain numbers was obtained using different scaling methods.The results show that both the simplified and standard DSS methods can simulate the dynamic characteristics of natural circulation in the primary circuit.The scaled-down cases in the simplified method exhibit the same geometric scaling and correspond to small core power ratios.By contrast,different scaled-down cases in the standard DSS method correspond to different geometric scaling criteria and require more power.The dynamic process of natural circula-tion can be simulated more accurately using the standard DSS method.

Dynamic scaling behaviour of late-stage phase separation in Ni75AlxV25-x alloys

The dynamic scaling behaviour of late-stage phase separation and coarsening mechanisms of L12 and D022 in Ni75AlxV25-x （3 ≤ x ≤ 10, at.%） alloys are studied using the microscopic phase-field dynamic model. The microelaso ticity field is incorporated into the diffusion dynamic model. The results show the morphology and coarsening dynamics being greatly changed by the elastic interactions among different precipitates, the particles aligning along the dominant directions, the average domain size （ADS） of L12 and D022 deviating from the exponent of temporal power-law, and the growth slowing down due to the increasing of elastic interactions. The dynamic scaling regime of late-stage coarsening of the precipitates is attained. Thus the scaling behaviour of structure function is also applicable for elastic interaction systems. It is also found that the variations of ADS and scaling function depend on the volume fraction of precipitates.

Dynamic Scaling of Ramified Clusters Formed on Liquid Surfaces

A comprehensive simulation model -- deposition, diffusion, rotation, reaction and aggregation model is presented to simulate the formation processes of ramified clusters on liquid surfaces, where clusters can disuse and rotate easily. The mobility （including diffusion and rotation） of clusters is related to its mass, which is given by Dm = Dos^-γD and θm = θos^-γθ, respectively. The influence of the reaction probability on the kinetics and structure formation is included in the simulation model. We concentrate on revealing dynamic scaling during ramified cluster formation. For this purpose, the time evolution of the cluster density and the weight-average cluster size as well as the cluster-size distribution scaling function at different time are determined for various conditions. The dependence of the cluster density on the deposition flux and time-dependence of fractal dimension are also investigated. The obtained results are helpful in understanding the formation of clusters or thin film growth on liquid surfaces.

Numerical study of anomalous dynamic scaling behaviour of (1+1)-dimensional Das Sarma-Tamborenea model

In order to discuss the finite-size effect and the anomalous dynamic scaling behaviour of Das Sarma-Tamborenea growth model, the （1＋1）-dimensional Das Sarma-Tamborenea model is simulated on a large length scale by using the kinetic Monte-Carlo method. In the simulation, noise reduction technique is used in order to eliminate the crossover effect. Our results show that due to the existence of the finite-size effect, the effective global roughness exponent of the （1＋1）-dimensional Das Sarma-Tamborenea model systematically decreases with system size L increasing when L 〉 256. This finding proves the conjecture by Aarao Reis[Aarao Reis F D A 2004 Phys. Rev. E 70 031607]. In addition, our simulation results also show that the Das Sarma-Tamborenea model in 1＋1 dimensions indeed exhibits intrinsic anomalous scaling behaviour.

Universal dynamic scaling and Contact dynamics in quenched quantum gases

Recently universal dynamic scaling is observed in several systems,which exhibit a spatiotemporal self-similar scaling behavior,analogous to the spatial scaling near phase transition.The latter one arises from the emergent continuous scaling symmetry.Motivated by this,we investigate the possible relation between the scaling dynamics and the continuous scaling symmetry in this paper.We derive a theorem that the scaling invariance of the quenched Hamiltonian and the initial density matrix can lead to the universal dynamic scaling.It is further demonstrated both in a two-body system analytically and in a many-body system numerically.For the latter one,we calculate the dynamics of quantum gases quenched from the zero interaction to a finite interaction via the non-equilibrium high-temperature virial expansion.A dynamic scaling of the momentum distribution appears in certain momentum-time windows at unitarity as well as in the weak interacting limit.Remarkably,this universal scaling dynamics persists approximately with smaller scaling exponents even if the scaling symmetry is fairly broken.Our findings may offer a new perspective to interpret the related experiments.We also study the Contact dynamics in the BEC−BCS crossover.Surprisingly,the half-way time displays a maximum near unitarity while some damping oscillations occur on the BEC side due to the dimer state,which can be used to detect possible two-body bound states in experiments.

A unified dynamic scaling property for the unified hybrid network theory framework

In this article, we present a new type of unified dynamic scaling property for synchronizability, which can describe the scaling relationship between dynamic synehronizability and four hybrid ratios under the unified hybrid network theory framework （UHNTF）. Our theory results can not only be applied to judge and analyze dynamic synehronizability for most of complex networks associated with the UHNTF, but also we can flexibly adjust and design different hybrid ratios and sealing exponent to meet actual requirement for the dynanfic characteristics of the UHNTF.

Application study of dynamic voltage scaling policies

Based on the fundamental relationship among the circuit power, the circuit delay and the supply voltage, four theorems associated with the application of dynamic voltage scaling （DVS） policies are proposed and proved. First, the existence characteristics of the optimal supply voltage for a single task are proved, which suggests that the optimal supply voltage for the single task should be selected only within a one-dimensional term, and the corresponding task end time by the optimal supply voltage should be identical with its deadline. Then, it is pointed out that the minimum energy consumption that the DVS policy can obtain when completing a single task is certainly lower than that of the dynamic power management （DPM） policy or the combined DVS＋DPM policy under the same conditions. Finally, the theorem of energy consumption minimization for a multi-task group is proposed, which declares that it is necessary to keep the processor in the execution state during the whole task period to obtain the minimum energy consumption, while satisfying the deadline constraints of any task.

Influences of Fractal Substrate Structures on Dynamic Scaling Behaviors of Etching Model

The Etching model on various fractal substrates embedded in two dimensions was investigated by means of kinetic Mento Carlo method in order to determine the relationship between dynamic scaling exponents and fractal parameters. The fractal dimensions are from 1.465 to 1.893, and the random walk exponents are from 2.101 to 2.578.It is found that the dynamic behaviors on fractal lattices are more complex than those on integer dimensions. The roughness exponent increases with the increasing of the random walk exponent on the fractal substrates but shows a non-monotonic relation with respect to the fractal dimension. No monotonic change is observed in the growth exponent.

Two‑parameter dynamical scaling analysis of single‑phase natural circulation in a simple rectangular loop based on dilation transformation

Scaling analysis is widely used to design scaled-down experimental facilities through which the prototype phenomena can be effectively evaluated.As a new method,dynamic system scaling(DSS)must be verified as a rational and applicable method.A DSS method based on dilation transformation was evaluated using single-phase natural circulation in a simple rectangular loop.The scaled-down cases were constructed based on two parameters—length ratio and dilation number—and the corresponding transient processes were simulated using the Relap5 computational code.The results show that this DSS method can simulate the dynamic flow characteristics of scaled-down cases.The transient deviation of the temperature difference and mass flow rate of the scaled cases decrease with increases in the length ratio and dilation number.The distortion of the transient temperature difference is smaller than that of the mass flow;however,the overall deviation is within a reasonable range.

Anomalous Scaling of Surface Growth Equations with Spatially and Temporally Correlated Noise

Based on the scaling idea of local slopes by Lopez et al. [Phys. Rev. Lett. 94 （2005） 166103], we investigate anomalous dynamic scaling of （d ＋ 1）-dimensional surface growth equations with spatially and temporally correlated noise. The growth equations studied include the Kardar-Parisi-Zhang （KPZ）, Sun-Guo-Grant （SGG）, and Lai-Das Sarma-Villain （LDV） equations. The anomalous scaling exponents in both the weak- and strong-coupling regions are obtained, respectively.

Application of scaled boundary finite element method in static and dynamic fracture problems

The scaled boundary finite element method （SBFEM） is a recently developed numerical method combining advantages of both finite element methods （FEM） and boundary element methods （BEM） and with its own special features as well. One of the most prominent advantages is its capability of calculating stress intensity factors （SIFs） directly from the stress solutions whose singularities at crack tips are analytically represented. This advantage is taken in this study to model static and dynamic fracture problems. For static problems, a remeshing algorithm as simple as used in the BEM is developed while retaining the generality and flexibility of the FEM. Fully-automatic modelling of the mixed-mode crack propagation is then realised by combining the remeshing algorithm with a propagation criterion. For dynamic fracture problems, a newly developed series-increasing solution to the SBFEM governing equations in the frequency domain is applied to calculate dynamic SIFs. Three plane problems are modelled. The numerical results show that the SBFEM can accurately predict static and dynamic SIFs, cracking paths and load-displacement curves, using only a fraction of degrees of freedom generally needed by the traditional finite element methods.

Dynamic Crack Propagation Analysis Using Scaled Boundary Finite Element Method

The prediction of dynamic crack propagation in brittle materials is still an important issue in many engineering fields. The remeshing technique based on scaled boundary finite element method(SBFEM) is extended to predict the dynamic crack propagation in brittle materials. The structure is firstly divided into a number of superelements, only the boundaries of which need to be discretized with line elements. In the SBFEM formulation, the stiffness and mass matrices of the super-elements can be coupled seamlessly with standard finite elements, thus the advantages of versatility and flexibility of the FEM are well maintained. The transient response of the structure can be calculated directly in the time domain using a standard time-integration scheme. Then the dynamic stress intensity factor(DSIF) during crack propagation can be solved analytically due to the semi-analytical nature of SBFEM. Only the fine mesh discretization for the crack-tip super-element is needed to ensure the required accuracy for the determination of stress intensity factor(SIF). According to the predicted crack-tip position, a simple remeshing algorithm with the minimum mesh changes is suggested to simulate the dynamic crack propagation. Numerical examples indicate that the proposed method can be effectively used to deal with the dynamic crack propagation in a finite sized rectangular plate including a central crack. Comparison is made with the results available in the literature, which shows good agreement between each other.

Visualization of atomic scale reaction dynamics of supported nanocatalysts during oxidation and ammonia synthesis using in-situ environmental(scanning) transmission electron microscopy

Reaction dynamics in gases at operating temperatures at the atomic level are the basis of heterogeneous gas-solid catalyst reactions and are crucial to the catalyst function.Supported noble metal nanocatalysts such as platinum are of interest in fuel cells and as diesel oxidation catalysts for pollution control,and practical ruthenium nanocatalysts are explored for ammonia synthesis.Graphite and graphitic carbons are of interest as supports for the nanocatalysts.Despite considerable literature on the catalytic processes on graphite and graphitic supports,reaction dynamics of the nanocatalysts on the supports in different reactive gas environments and operating temperatures at the single atom level are not well understood.Here we present real time in-situ observations and analyses of reaction dynamics of Pt in oxidation,and practical Ru nanocatalysts in ammonia synthesis,on graphite and related supports under controlled reaction environments using a novel in-situ environmental(scanning) transmission electron microscope with single atom resolution.By recording snapshots of the reaction dynamics,the behaviour of the catalysts is imaged.The images reveal single metal atoms,clusters of a few atoms on the graphitic supports and the support function.These all play key roles in the mobility,sintering and growth of the catalysts.The experimental findings provide new structural insights into atomic scale reaction dynamics,morphology and stability of the nanocatalysts.

AdaptNF: Adaptive service chain scheduling with stateless migration and NF consolidation

The combination of network function virtualization and software-defined networking allows various network functions to process flows according to their characteristics and requirements.Due to the highly dynamic nature of the workload,the network infrastructure needs to properly schedule the underlying resources in order to respond to workload changes in a timely manner.However,the existing NFV platform lacks a comprehensive solution for how to scale under workload variation,which may seriously hurt the overall system performance.To improve the scalability of the NFV platform and ensure consistent high performance under dynamic workloads,we propose AdaptNF,a novel NFV platform designed to support a combination of course-grained and fine-grained resource scheduling strategies.To deal with resource imbalance,which is the essential scheduling problem that leads to insufficient NFV performance,AdaptNF adopts a novel algorithm that can efficiently balance the workload among multiple network function instances through stateless flow migration.Our controlled experiments show that the AdaptNF scheme can optimize resource allocation and ensure outstanding performance after scaling.In terms of network throughput and latency,AdaptNF significantly improves the performance of the underlying NFV platform.

A Review of the Current Task Offloading Algorithms,Strategies and Approach in Edge Computing Systems

Task offloading is an important concept for edge computing and the Internet of Things(IoT)because computationintensive tasksmust beoffloaded tomore resource-powerful remote devices.Taskoffloading has several advantages,including increased battery life,lower latency,and better application performance.A task offloading method determines whether sections of the full application should be run locally or offloaded for execution remotely.The offloading choice problem is influenced by several factors,including application properties,network conditions,hardware features,and mobility,influencing the offloading system’s operational environment.This study provides a thorough examination of current task offloading and resource allocation in edge computing,covering offloading strategies,algorithms,and factors that influence offloading.Full offloading and partial offloading strategies are the two types of offloading strategies.The algorithms for task offloading and resource allocation are then categorized into two parts:machine learning algorithms and non-machine learning algorithms.We examine and elaborate on algorithms like Supervised Learning,Unsupervised Learning,and Reinforcement Learning(RL)under machine learning.Under the non-machine learning algorithm,we elaborate on algorithms like non(convex)optimization,Lyapunov optimization,Game theory,Heuristic Algorithm,Dynamic Voltage Scaling,Gibbs Sampling,and Generalized Benders Decomposition(GBD).Finally,we highlight and discuss some research challenges and issues in edge computing.

Energy-Efficient Scheduling Based on Task Migration Policy Using DPM for Homogeneous MPSoCs

Increasing the life span and efficiency of Multiprocessor System on Chip(MPSoC)by reducing power and energy utilization has become a critical chip design challenge for multiprocessor systems.With the advancement of technology,the performance management of central processing unit(CPU)is changing.Power densities and thermal effects are quickly increasing in multi-core embedded technologies due to shrinking of chip size.When energy consumption reaches a threshold that creates a delay in complementary metal oxide semiconductor(CMOS)circuits and reduces the speed by 10%–15%because excessive on-chip temperature shortens the chip’s life cycle.In this paper,we address the scheduling&energy utilization problem by introducing and evaluating an optimal energy-aware earliest deadline first scheduling(EA-EDF)based technique formultiprocessor environments with task migration that enhances the performance and efficiency in multiprocessor systemon-chip while lowering energy and power consumption.The selection of core andmigration of tasks prevents the system from reaching itsmaximumenergy utilization while effectively using the dynamic power management(DPM)policy.Increase in the execution of tasks the temperature and utilization factor(u_(i))on-chip increases that dissipate more power.The proposed approach migrates such tasks to the core that produces less heat and consumes less power by distributing the load on other cores to lower the temperature and optimizes the duration of idle and sleep times across multiple CPUs.The performance of the EA-EDF algorithm was evaluated by an extensive set of experiments,where excellent results were reported when compared to other current techniques,the efficacy of the proposed methodology reduces the power and energy consumption by 4.3%–4.7%on a utilization of 6%,36%&46%at 520&624 MHz operating frequency when particularly in comparison to other energy-aware methods for MPSoCs.Tasks are running and accurately scheduled to make an energy-efficient processor by controlling and managing the thermal effects on-chip and optimizing the energy consumption of MPSoCs.

An Optimal DPM Based Energy-Aware Task Scheduling for Performance Enhancement in Embedded MPSoC

Minimizing the energy consumption to increase the life span and performance of multiprocessor system on chip(MPSoC)has become an integral chip design issue for multiprocessor systems.The performance measurement of computational systems is changing with the advancement in technology.Due to shrinking and smaller chip size power densities onchip are increasing rapidly that increasing chip temperature in multi-core embedded technologies.The operating speed of the device decreases when power consumption reaches a threshold that causes a delay in complementary metal oxide semiconductor(CMOS)circuits because high on-chip temperature adversely affects the life span of the chip.In this paper an energy-aware dynamic power management technique based on energy aware earliest deadline first(EA-EDF)scheduling is proposed for improving the performance and reliability by reducing energy and power consumption in the system on chip(SOC).Dynamic power management(DPM)enables MPSOC to reduce power and energy consumption by adopting a suitable core configuration for task migration.Task migration avoids peak temperature values in the multicore system.High utilization factor(ui)on central processing unit(CPU)core consumes more energy and increases the temperature on-chip.Our technique switches the core bymigrating such task to a core that has less temperature and is in a low power state.The proposed EA-EDF scheduling technique migrates load on different cores to attain stability in temperature among multiple cores of the CPU and optimized the duration of the idle and sleep periods to enable the low-temperature core.The effectiveness of the EA-EDF approach reduces the utilization and energy consumption compared to other existing methods and works.The simulation results show the improvement in performance by optimizing 4.8%on u_(i) 9%,16%,23%and 25%at 520 MHz operating frequency as compared to other energy-aware techniques for MPSoCs when the least number of tasks is in running state and can schedule more tasks to make an energy-efficient processor by controlling and managing the energy consumption of MPSoC.

Full-State-Constrained Non-Certainty-Equivalent Adaptive Control for Satellite Swarm Subject to Input Fault

Satellite swarm coordinated flight(SSCF)technology has promising applications,but its complex nature poses significant challenges for control implementation.In response,this paper proposes an easily solvable adaptive control scheme to achieve high-performance trajectory tracking of the SSCF system subject to actuator efficiency losses and external disturbances.Most existing adaptive controllers based on the certaintyequivalent(CE)principle show unpredictability and nonconvergence in their online parameter estimations.To overcome the above vulnerabilities and the difficulties caused by input failures of SSCF,this paper proposes an adaptive estimator based on scaling immersion and invariance(I&I),which reduces the computational complexity while improving the performance of the parameter estimator.Besides,a barrier Lyapunov function(BLF)is applied to satisfy both the boundedness of the system states and the singularity avoidance of the computation.It is proved that the estimator error becomes sufficiently small to converge to a specified attractive invariant manifold and the closed-loop SSCF system can obtain asymptotic stability under full-state constraints.Finally,numerical simulations are performed for comparison and analysis to verify the effectiveness and superiority of the proposed method.

Joint Communication and Processor Frequency Selection for Low-Energy Systems under Timing Constraints

This paper presents a method to reduce the energy consumption of multi-core systems characterized by processor cores and buses with discrete frequency levels under timing constraints.The proposed method takes the transformations of the original task graphs,which include dependent tasks located in different iterations,as inputs.The proposed method utilizes mapping selection as well as joint processor and communication frequency scaling to implement energy reduction.We conduct experiments on several random task graphs.Experimental results show that the proposed method can achieve substantial energy reduction compared with previous work under the same hard timing constraints.

Effects of grassland management on the community structure, aboveground biomass and stability of a temperate steppe in Inner Mongolia, China

Plant community structure responds strongly to anthropogenic disturbances, which greatly influence community stability. The changes in community structure, aboveground biomass（AGB）, biodiversity and community stability associated with different management practices were studied with a three-year field investigation in a temperate steppe of Inner Mongolia, China. The species richness, Shannon-Wiener index, evenness, plant functional type abundance, AGB, temporal community stability, summed covariance, scaling coefficient and dominant species stability were compared among areas subjected to long-term reservation（R）, long-term grazing（G）, mowing since enclosure in 2008（M） and grazing enclosure since 2008（E）. Site R had higher perennial grass abundance and lower species richness than sites G, M and E, although the AGB was not significantly different among the four sites. The species structure varied from a single dominant species at site R to multiple dominant species at sites G, M and E. The long-term reservation grassland had lower biodiversity but higher stability, whereas the enclosed grassland with/without mowing had higher biodiversity but lower stability. Different stability mechanisms, such as the compensatory dynamics, mean-variance scaling and dominant species stability were examined. Results showed that community stability was most closely related to the relative stability of the dominant species, which supports the biomass ratio hypothesis proposed by Grime.