Critical Boundary Research Articles

A virtual synchronous generator control method for remote island power system considering dynamic voltage stability

Remote island power systems are difficult to install renewable energy sources (RES) because of the small system capacity and the large impact of intermittency of RES. Virtual synchronous generators (VSG) can equip inverters with the inertia of synchronous generators and can suppress frequency and voltage fluctuations. This paper proposes a VSG control method for dynamic voltage stability in remote island power systems. In conventional VSG control methods, the command of active and reactive power is determined by the Droop characteristics of frequency and transmission line voltage. However, the command are not based on dynamic voltage stability indices. Therefore, the compensation amount of active and reactive power is inappropriate. The proposed method determines the command of active and reactive power based on dynamic voltage stability indices. The dynamic voltage stability index considers the critical boundary index (CBI). The CBI is defined as the distance between the operating point of active and reactive power flowing through a transmission line and the stability limit curve calculated from the power flow between two bus lines. The proposed method improves dynamic voltage stability by determining power command so that the operating points of active and reactive power are closer to the origin direction. Simulation verification is performed for load increase and three-phase ground fault. In the three-phase ground-fault simulation, FRT requirements are considered to verify continued operation and the case of gate blocking. The conventional Droop control and the proposed method are compared for the case of continued operation with FRT requirements during load increase and ground fault. Simulation verification results show that the proposed method improves the dynamic voltage stability compared to the conventional method. Furthermore, it is shown that the proposed method is capable of stable continuous operation of the system even after a transmission line failure considering the FRT requirement.

Cause typicality and the continued influence effect.

A large body of research has focused on whether and how readers update their knowledge of events when an initial piece of causal information is corrected. These studies have indicated that corrections can reduce, but do not eliminate, readers' reliance on the initial cause when drawing inferences or making decisions about the events (i.e., the continued influence effect). Additional studies suggest that supplementing a correction with an alternative cause can further reduce reliance on discredited initial causes. In three experiments, we interrogated the importance of cause typicality for the generalizable utility of these correction strategies by manipulating the typicality of initial and alternative causes. We found evidence that participants showed greater reliance on a typical than an atypical initial cause both before and after correction, but no consistent evidence that this typicality impacted the effectiveness of the correction. Furthermore, the typicality of the alternative causes used to supplement a correction did not seem to matter with respect to updating. These results highlight the importance that characteristics of an initial cause can have for event encodings and corrections, identifying critical boundary conditions for understanding the effects of corrections on knowledge revision and the continued influence effect. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Online Adaptive Generation of Critical Boundary Scenarios for Evaluation of Autonomous Vehicles

Testing and evaluation are critical steps in the development and deployment of autonomous vehicles (AVs). This paper aims to provide an online adaptive generation framework for critical boundary driving scenarios (CBDS) with flexible complexity and diversity. Both static scenarios and dynamic scenarios are comprehensively investigated based on real traffic flow data, where the generated static scenarios contain variables of drivable area, weather visibility, and road friction coefficient on autonomous vehicles, and the generated dynamic scenarios consider the effects of mixed traffic streams of AVs, human-driven vehicles, bicycles, and pedestrians. Two complexity models are proposed to characterize the complexity of static scenarios and dynamic scenarios separately, which help to construct feedback for the adaptive generation of CBDS. The scenario-based test is carried out on a joint simulation platform, and the multi-dimensional evaluation system, including safety, driving comfort, driving performance, and traffic coordination, is developed to assess the performance of AVs. Based on the proposed complexity models and multi-dimensional evaluation system, the generation of CBDS is transformed into online environmental parameter optimization. Moreover, the naturalistic driving scenarios generation, scenario complexity calculation, intelligent driving algorithm execution, and intelligent driving evaluation are all concatenated together to form a closed loop so as to adaptively generate critical boundary driving scenarios. Extensive simulations are conducted at the intersection with two different types of intelligent driving algorithms, which show the effectiveness of the proposed framework.

The Asymptotic Structure of Strained Chain-Branching Premixed Flames with Nonunity Lewis Numbers and Their Extinction

ABSTRACT Extinction of strained chain-branching premixed flames with nonunity fuel and chain-carrier Lewis numbers is asymptotically analyzed by employing an NEF (Nearly Equidiffusional Flame) limit modified specifically for the Zel’dovich-Liñán two-step mechanism. The asymptotic chain-branching flame-structure analysis is carried out within the framework of the intermediate recombination regime, in which the recombination layer is asymptotically thicker than the inner chain-branching layer, but thinner than the outer convective-diffusive layer. In order to construct a consistent activation-energy asymptotics for the thinnest chain branching layer, thickness of the intermediate recombination-layer as well as deviation of the chain-carrier Lewis number from unity is scaled by the inverse square root of the chain-branching Zel’dovich number. Because the fuel is consumed only by the chain-branching reaction, characterized by a large chain-branching Zel’dovich number, the influences of nonunity fuel Lewis number on extinction with two-step chemistry is found to be qualitatively almost identical to that with overall one-step chemistry. Therefore, strained chain-branching flames can be extinguished by increasing the flow strain rate if the fuel Lewis number is sufficiently large. However, the chain-carrier Lewis number is found to be not capable of qualitatively influencing the extinction characteristics because the peak chain-carrier concentration tends to remain almost invariant with varying flow strain rate. Abrupt extinction is more readily observed for the faster recombination regime, for which the overall effective nonlinearity of the two-step mechanism becomes larger. Finally, the critical Lewis number boundary for extinction is predominantly dependent on the fuel Lewis number. Consequently, the overall extinction characteristics of strained chain-branching flames is found to be qualitatively similar to that found within the framework of the overall single-step activation-energy asymptotics.

Study on Impact–Echo Response of Concrete Column near the Edge

The impact–echo method is a superior method for detecting the health of concrete structures, but it has the disadvantage of significant errors when identifying structural boundaries. In order to overcome this limitation, this paper proposes a calculation method using a cross-sectional vibration mode in combination with the impact–echo method to detect concrete columns. The variation of the predominant frequency in the mid-column region and the critical boundary is studied. The influence of the edge on the detection results is analyzed. The differences in eigenvalues under different cross-section vibration modes are revealed. A quantitative method for evaluating concrete health using the impact–echo method is further established. Through field tests and finite element simulation calculations, it was verified that the eigenvalues in the fixed mode are very consistent with the predominant frequency measured near the edge region. This makes up for the defect of inaccurate measurements when the impact–echo method is used to detect the edge area of concrete members. The impact–echo method can be better used for the non-destructive testing of concrete members.

Improving resident well-being: a narrative review of wellness curricula.

To improve wellness among residents, many graduate medical education programs have implemented formal wellness curricula. Curricular development has recently shifted focus from drivers of burnout to promotion of wellness. The specific components of successful wellness curricula, however, are not yet well defined. To review the published literature assessing core components of wellness curricula in graduate medical education programs. Searches were conducted through June 2020 in PubMed, Education Resources Information Center, Google Scholar and Web of Science using the search terms wellness curricula, wellness programs, well-being and graduate medical education. Additional articles were identified from reference lists. Curricula from primarily undergraduate medical education, singular interventions, non-peer-reviewed studies and non-English language studies were excluded. Eighteen articles were selected and reviewed by three authors. Critical drivers of success included support from program leadership and opportunities for resident involvement in the curriculum implementation. Most curricula included interventions related to both physical and mental health. Curricula including challenging components of professionalisation, such as critical conversations, medical errors and boundary setting, seemed to foster increased resident buy-in. The most frequently used curricular assessment tools were the Maslach Burnout Inventory and resident satisfaction surveys. Different specialties have different wellness needs. A resource or 'toolbox' that includes a variety of general as well as specialty-specific wellness components might allow institutions and programs to select interventions that best suit their individual needs. Assessment of wellness curricula is still in its infancy and is largely limited to single institution experiences.

Identification of heat transfer coefficients in continuous casting by a GPU-based improved comprehensive learning particle swarm optimization algorithm

The heat transfer coefficients (HTCs) of the secondary cooling zone (SCZ) are a critical boundary condition for numerical modeling of solidification heat transfer in the continuous casting process. However, it is difficult to identify accurately these HTCs. Due to the high computational complexity, the computation time in the identification process is not negligible, especially during the process of optimization and heat transfer model solution. To solve those problems, we first developed an improved comprehensive learning particle swarm optimization algorithm (ICL-PSO) to identify more accurate HTCs in the SCZ of continuous casting. Secondly, a two-layer parallel algorithm that implements ICL-PSO on a graphics processing unit (GPU) was then designed and tested to reduce the computation time of identifying these HTCs. Finally, the experimental results show that the accuracy of the proposed algorithm for HTC identification and the efficiency of GPU-accelerated computation have been improved.

The S-shaped relationship between open innovation and financial performance: A longitudinal perspective using a novel text-based measure

Research on the financial performance outcomes of open innovation has been equivocal and often relies on cross-sectional data and problematic assumptions about the role of the external context. A longitudinal perspective is crucial for gaining a better understanding of the potential of decreasing innovation utility as well as the conditions under which the costs of open innovation may counteract its benefits. Additionally, much of the research largely ignores the potential role and benefits of closed innovation. In this study, we address these issues by developing a theory related to how the benefits and costs of open innovation lead to an S-shaped relationship between the degree of openness – ranging from closed to low, medium, and high levels of open innovation – and a firm's financial performance. Furthermore, we investigate two possible contingencies in which this relationship is more pronounced: in industries with high appropriability, optimizing firms' ability to extract value from innovation and in dynamic industries, where coordinating high open innovation activities amid rapid changes is exceedingly costly. To test our hypotheses, we create a longitudinal measure for firms' degree of open innovation by using machine-learning content analyses to build an open innovation dictionary and then applying this dictionary to analyze the 10-K annual reports of >9000 publicly listed firms in the U.S. between 1994 and 2017. The results support our theorizing that the relationship between the degree of open innovation and firm financial performance is S-shaped and that industries' appropriability regimes and environmental dynamism are critical boundary conditions for this relationship.

Role of fresh start mindset framing in reducing stigma and promoting mental health help‐seeking behavior

AbstractOne challenge in promoting mental health help‐seeking behaviors is the masculine norm ingrained in the U.S. Using experimental data, this article examines how fresh start mindset (FSM) framing can be effective in helping reduce the stigma associated with mental health help‐seeking behaviors and increase the promotion of positive attitudes and word‐of‐mouth of the mental health messages among men (vs. women). This study uniquely reveals that FSM framing in mental health ad campaigns might help men switch from the mindset that mental health help‐seeking behaviors equate to showing weakness to one of help‐seeking behaviors as a fresh start. Further, this study demonstrates that males with high issue involvement levels and females with low issue involvement levels respond to FSM framing more favorably. Thus, issue involvement levels form the critical boundary conditions. The authors also reveal that attitudes toward the ads operate as an underlying mechanism in FSM framing effects on responses.

Палинологическая зональность живетско-франского стратиграфического интервала в Тимано-Североуральском регионе

The zonal scheme of the Givetian-Frasnian boundary interval in the Timan-Northern Urals region was detailed according to the higher plants spores. Palynological zones were correlated with faunal, including conodont — orthostratigraphic group in the Devonian. The correlation of the identified critical boundaries in the development of plant communities with the divisions’ borders of the International Stratigraphic Scale — series and stages, were established and options for the level of the border of the Middle and Upper Devonian in the regional stratigraphic scheme of the new generation were considered.

Liquefaction Potential of Saturated Sand Reinforced by Cement-Grouted Micropiles: An Evolutionary Approach Based on Shaking Table Tests

Cement-grouted injections are increasingly employed as a countermeasure material against liquefaction in active seismic areas; however, there is no methodology to thoroughly and directly evaluate the liquefaction potential of saturated sand materials reinforced by the cement grout-injected micropiles. To this end, first, a series of 1 g shaking table model tests are conducted. Time histories of pore water pressures, excess pore water pressure ratios (ru), and the number of required cycles (Npeak) to liquefy the soil are obtained and modified lower and upper boundaries are suggested for the potential of liquefaction of both pure and grout-reinforced sand. Next, adopting genetic programming and the least square method in the framework of the evolutionary polynomial regression technique, high-accuracy predictive equations are developed for the estimation of rumax. Based on the results of a three-dimensional, graphical, multiple-variable parametric (MVP) analysis, and introducing the concept of the critical, boundary inclination angle, the inclination of micropiles is shown to be more effective in view of liquefaction resistivity for loose sands. Due to a lower critical boundary inclination angle, the applicability range for inclining micropiles is narrower for the medium-dense sands. MVP analyses show that the effects of a decreasing spacing ratio on decreasing rumax are amplified while micropiles are inclined.

Effects of short-term plasticity in UP-DOWN cortical dynamics

Neuronal dynamics are strongly influenced by short-term plasticity (STP), that is, changes in synaptic efficacy that occur on a short (from milliseconds to seconds) time scale. Depending on the brain areas considered, STP can be dominated by short-term depression (STD), short-term facilitation (STF), or both mechanisms can coexist simultaneously. These two plasticity mechanisms modulate particular patterns of electrophysiological activity characterized by alternating UP and DOWN states. In this work, we develop a network model made up of excitatory and inhibitory multi-compartment neurons endowed with both mechanisms (STD and STF), spatially arranged to emulate the connectivity circuitry observed experimentally in the visual cortex. Our results reveal that both depression and facilitation can be involved in the switching process between different activity patterns, from an alternation of UP and DOWN states (for relatively low levels of depression and high levels of facilitation) to an asynchronous firing regime (for relatively high levels of depression and low levels of facilitation). For STD and STF, we identify the critical levels of depression and facilitation that push the network into the different regimes. Furthermore, we also find that these critical levels separate different growth rates of the mean synaptic conductances of the whole network with respect to the depression levels. This latter data is paramount to understanding how excitation and inhibition are organized to generate different brain activity regimes. Finally, after observing the changes in the trajectories of excitatory and inhibitory instantaneous firing rates near these critical boundaries, we identify dynamic patterns that shed light on the type of bifurcations that should arise in a rate model for this complex network.

Making Ordinary People Actors in National History

This paper analyzes a recent exhibit in Vietnam’s national ethnology museum which depicted ordinary people’s everyday experiences during the postwar, pre-reform era in Hanoi, an era which was full of hardship and had rarely been discussed publicly prior to this. The exhibit narrated a critical yet nostalgic representation which favored the experiences of ‘ordinary citizens’’ above official discourses about this period. I argue that the exhibit designers aimed to pose ordinary citizens as significant actors in national history, thereby narrating Vietnam’s modern history in a new way. In the course of critically examiningthe past and the present, the exhibit pushed the boundaries of social criticism and public discourse, and showed that museum exhibits are not neutral spacesfor the production of knowledge but, rather, can become sites which mediate indirect negotiation between people and the state and re-interpret the past forthe present and the future.
 
 Keywords: museums, politics of memory, personal narratives, subsidy system, Vietnam

Effective Connectivity and Bias Entropy Improve Prediction of Dynamical Regime in Automata Networks.

Biomolecular network dynamics are thought to operate near the critical boundary between ordered and disordered regimes, where large perturbations to a small set of elements neither die out nor spread on average. A biomolecular automaton (e.g., gene, protein) typically has high regulatory redundancy, where small subsets of regulators determine activation via collective canalization. Previous work has shown that effective connectivity, a measure of collective canalization, leads to improved dynamical regime prediction for homogeneous automata networks. We expand this by (i) studying random Boolean networks (RBNs) with heterogeneous in-degree distributions, (ii) considering additional experimentally validated automata network models of biomolecular processes, and (iii) considering new measures of heterogeneity in automata network logic. We found that effective connectivity improves dynamical regime prediction in the models considered; in RBNs, combining effective connectivity with bias entropy further improves the prediction. Our work yields a new understanding of criticality in biomolecular networks that accounts for collective canalization, redundancy, and heterogeneity in the connectivity and logic of their automata models. The strong link we demonstrate between criticality and regulatory redundancy provides a means to modulate the dynamical regime of biochemical networks.

Service Design Handover to user experience design – a systematic literature review

Knowledge transfer plays an important role in digital Service Creation Projects where information should flow through service design, Agile UX, and software implementation phases. One context for these handovers exists in projects where the service designers participate in the early phases of exploring and scoping the service, while agile user experience specialists take over the digital parts of service design and programmers the software implementation. The purpose of this study is to summarise scientific knowledge into best practices for effective information flow in real world Service Creation Projects. Special attention is paid on an important and understudied project phase, knowledge handover from service design to software implementation, which is referred as Service Design Handover in this study. A systematic literature review was conducted to analyse the current scientific knowledge on knowledge transfer in digital Service Creation Projects. PRISMA 2020 statement was used for reporting the review, which also influenced planning and execution of the systematic review process. SCOPUS search brought up 773 publications, and the full content analysis was done for the 41 most relevant publications. Based on the literature analysis, the best practices for effective knowledge transfer are related to communication quality and quantity, circumventing the need for communication, and verifying successful communication. To provide an overview of effective knowledge transfer, frameworks of Service Creation Project information flow and Service Design Handover are proposed. The existing knowledge transfer literature is voluminous, but this literature review is the first to study knowledge transfer in Service Creation Project context. The framework, best practices, and list of potential problem sources in knowledge transfer provide new knowledge for managing the information flow in service creation. The research gaps found in this literature review show the need for future research, such as empirical studies on service creation practice. • First systematic literature review on Service Design Handover. • Information flow framework for Service Creation Projects. • Initial framework for Service Design Handover to Agile UX. • Service vision, user stories and prototype are the most critical boundary objects for the Service Design Handover.

Collapse of Superradiant Phase and Unstable Macroscopic Vacuum State in An-Optomechanical-Dual-Cavity with a Bose-Einstein Condensate

Based on spin-coherent-state variational method, we mainly study the multiple stable macroscopic quantum states and quantum phase transitions of a Bose-Einstein Condensate in an optomechanical dual-cavity by modulating the dual-cavity interaction and the nonlinear phonon-photon interaction. Especially, the collapse of superradiant phase can be tuned in the existing nonlinear photon-phonon interaction, but the critical quantum phase transition point or boundary hasn’t been influenced. As a result, the system occurs an additional phase transition from the superradiant phase to the inversely atomic populated state. Moreover, when dual-cavity coupling interaction increases to a certain value, a new quantum phase transition from the normal phase to the inversely atomic populated state will appear. Finally, the superradiant phase completely collapses and the normal phase also collapses into an unstable macroscopic vacuum state for a strong dual-cavity coupling interaction.

A confidence level estimation technique for reliable Data-Driven FRA interpretation in air-core winding faults

Frequency response analysis (FRA) data interpretation is among highly challenging tasks in transformer fault diagnosis. Among different quantitative methods, employing statistical indicators on FRA results for mechanical integrity assessment is well-stablished. However, the boundary values of indices that differentiate normal/healthy, suspicious, and abnormal transformer operating conditions are not yet agreed upon. This will make the FRA data interpretation using SIs subjective and unreliable. In this study, data-driven critical boundaries of the most frequently used SIs are introduced. To address the uncertainty of the decision boundaries, a confidence level estimation technique is developed to quantify the probability of a transformer being in a particular operating condition. Reporting a confidence level along with the classified conditions facilitates objective decision-making that can support utility operators during on-site transformer evaluation. The confidence level estimation technique proposed in this work was inspired by bolstered error estimation method widely applied in pattern recognition. Moreover, this study provides a new comprehensive technique of transformer winding fault modeling using SPICE netlists. The proposed analytical winding model is validated through practical FRA measurements with high precision. It is further used to generate various scenarios of common active part faults, such as disk space variation, radial displacement, and disk tilting. Consequently, the proposed method of confidence level estimation is examined on different winding deformations and demonstrated a high potential for comprehensive transformer winding diagnosis.

Concentration-Dependent Domain Evolution in Reaction–Diffusion Systems

Pattern formation has been extensively studied in the context of evolving (time-dependent) domains in recent years, with domain growth implicated in ameliorating problems of pattern robustness and selection, in addition to more realistic modelling in developmental biology. Most work to date has considered prescribed domains evolving as given functions of time, but not the scenario of concentration-dependent dynamics, which is also highly relevant in a developmental setting. Here, we study such concentration-dependent domain evolution for reaction–diffusion systems to elucidate fundamental aspects of these more complex models. We pose a general form of one-dimensional domain evolution and extend this to N-dimensional manifolds under mild constitutive assumptions in lieu of developing a full tissue-mechanical model. In the 1D case, we are able to extend linear stability analysis around homogeneous equilibria, though this is of limited utility in understanding complex pattern dynamics in fast growth regimes. We numerically demonstrate a variety of dynamical behaviours in 1D and 2D planar geometries, giving rise to several new phenomena, especially near regimes of critical bifurcation boundaries such as peak-splitting instabilities. For sufficiently fast growth and contraction, concentration-dependence can have an enormous impact on the nonlinear dynamics of the system both qualitatively and quantitatively. We highlight crucial differences between 1D evolution and higher-dimensional models, explaining obstructions for linear analysis and underscoring the importance of careful constitutive choices in defining domain evolution in higher dimensions. We raise important questions in the modelling and analysis of biological systems, in addition to numerous mathematical questions that appear tractable in the one-dimensional setting, but are vastly more difficult for higher-dimensional models.

Responses, optimization and prediction of energy harvesters under galloping and base excitations

In this paper, the complexification-averaging method is firstly used to derive the theoretical solutions and analyze the dynamical performance of the energy harvesters under galloping and base excitations. Based on the distributed parameter model of the energy harvesters, the model equations can be turned into a set of high-order ordinary differential equations by solving the ordinary differential equations with coupled terms, then the equation of the amplitude frequency and the analytical relationship to determine the displacement amplitude and the voltage amplitude are derived. In addition, the influence of parameters such as the wind speed, the electromechanical coupling parameter and the base excitation frequency on the nonlinear behaviors of the energy harvesters are explored. It is found that there exists very good consistency between the theoretical results and the numerical results. The response properties are verified by means of the phase portraits and time histories. Additionally, according to the implicit function derivative theorem, the critical condition for identifying the unstable region is obtained. And with the different system parameters, the critical unstable boundary can be identified. In order to improve the efficiency of energy harvesting, the parameters of the energy harvesters are optimized based on the purpose of maximum voltage amplitude. Finally, the results are predicted by means of the multilayer feedforward neural network, and the excellent prediction results can be found.

Topographic constraints on the distribution of selenium in the supergene environment: A case study at Yutangba, China

The local topography and leaching conditions significantly affect the spatial distribution of selenium (Se) in the local environment. However, the driving factors controlling Se distribution have not been well addressed. In this paper, taking Yutangba, a village known for human selenosis in China, as an example, we demonstrate how topographic factors influence the spatial distribution of Se in soils and plants. In the scenarios of slope ≤25°, the correlations among slope and soil/extractable/plant Se are significantly negative (P < 0.05), whereas they become weak or unclear when the slope is > 25°, suggesting that 25° of slope is a critical transition boundary. Similar observations were further verified by the soil erosion modulus (SEM) and the surface runoff intensity index (SRI), indicating that Se transport via soil erosion is limited and accounts for 11.2–17% of the soil Se, while surface runoff plays a dominant role in the Se distribution, accounting for 83–88.1%. Soil extractable Se is negatively correlated with SRI (Pearson r = −0.87 at slope < 25°), showing that the migration capacity of Se is higher at steep terrain and controlled by topography through soil erosion and surface runoff. The positive relationship between plant Se and soil/extractable Se demonstrates that topography indirectly influences plant Se through soil Se bioavailability. Abnormally local Se enrichment observed at the elevated steep hillside (>25°) in northwestern Yutangba primarily was resulted from the weathering of Se-rich rocks. These observations confirm that the topographic slope gradient influences the transport and spatial distribution of soil Se, implying that topography should be considered when studying the spatial distribution of soil Se at a regional scale, especially for the Se-poor belt in China.