Chapter 5 - Modeling spatiotemporal dynamics of flood risk change

System performance tracking is critical to state identification, fault detection and subsequent remaining useful life (RUL) prediction. It is not uncommon that dynamic systems degrade gradually in a non-linear manner, occasionally accompanied with abrupt faults, before and after which the degradation rates vary. In addition, uncertainty coming from sensor measurements poses more challenges to solving this problem. Existing state estimation techniques that are eligible for uncertainty evaluation, such as the extended or unscented Kalman filter and particle filter (PF), can only be applied to non-linear system state tracking excluding abrupt faults, in which case they cannot: 1) detect transient changes of the system states; and 2) track the degradation with varying rate. To address these challenges, a total variation (TV) filter synthesized with an advanced particle filter is developed in this paper. The transient changes of the noisy system states due to abrupt faults are first filtered out by the TV filter. The outputs of the TV filter and the noisy states are then routed to a local search particle filter (LSPF), which is proposed in this paper that can dynamically accommodate its resampling to track the state variation and combat the sample impoverishment problem associated with conventional PFs. The corrected transient changes and estimated gradual degradation of the system states, as well as the uncertainty quantification can be obtained from the LSPF. The proposed approach is presented and demonstrated for automatic fault detection and performance tracking at a component level in heating, ventilation, and air conditioning (HVAC) systems, such as the heat exchanger. To evaluate the developed method, a finite element model for the heat exchanger is established to simulate both normal and faulty cases. The simulation results exhibit the effectiveness of proposed method in fault detection and degradation estimation in heat exchanger.

Aim. Industrial safety (OS) is the state of protection of operating personnel from harmful effects of manufacturing processes, energy, equipment, objects, conditions and schedule of work [1]. The most efficient evaluation of OS in railway transportation is ensured by composite indicators, one of which is the risk assessment indicator. That is also reflected in the Russian legislation that stipulates the requirement to evaluate fire, occupational and other types of risks that affect industrial safety. According to the definition set forth in GOST 33433-2015 [2] risk is a combination of the probability and consequences of an event. The most complicated task related to risk assessment is the choice of the evaluation model for the probability of an undesired event. The model must enable practical applicability of evaluation results for planning of risk compensation measures. Currently, there are a large number of probability evaluation methods that can be divided into two large groups, i.e. expert and quantitative. Expert methods have several well-known shortcomings. The quantitative methods require the construction of a system of equations or an analytical model. In the context of railway facilities the construction of analytical models of probability evaluation is of principal interest due to the possibility of demonstration of the factors that are taken into consideration by the model. The aim of the article is to formalize the analytical method for evaluation of the probability of railway facility transfer into a hazardous state (in the context of industrial safety). Methods . Undesirable events that cause industrial safety incidents in railway facilities are random; they can be represented as a random process. A random system development process, including objects transition from a safe state into hazardous (undesirable) states, i.e. system state change in time, can under some assumptions be described with a semi-Markov process. In general, the construction and solution of semi-Markov models comes down to building a system of homogenous differential equations. This procedure always involves mathematical difficulties. [3] shows the possibility of representation and solution of semi-Markov models with a coupled graph model. Such models are highly visual, and allow formalizing the wanted system states, as well as paths of transition from safe into hazardous states. The main problem of modelling random processes of industrial safety state changes is the requirement to identify the complete list of hazardous states and preceding non-hazardous or pre-hazardous states. The processes typical to railway facilities are characterized by a multitude of states that cause various events. The concept of “state” usually characterizes an instantaneous image, a “cross-section” of a system. Thus, at the first stage of construction and solution of a model of random process of a system’s industrial safety state change, the finite sets of safe and hazardous states of the railway facility under consideration are identified in accordance with the known hazardous state criterion [4]. As the process of state change of a system’s industrial safety in railway transportation is random in time, in this article system operation is described with a semi-Markov process with the assumption that the discrete process is described with an embedded Markov chain. The set of system states and their connections are represented with a directed state graph with defined topological concepts [3]. For a constructed model, the article provides the proof of the theorem identifying the probability of system transition from an initial non-hazardous into a hazardous state, as well as the formula for calculation of such probability. Results . The graph method for evaluation of industrial safety in railway facilities developed in this article includes both the rules of construction of a system’s safety states graph and the tool for evaluation of the probability of system transition into a specific hazardous state. The graph is the basis of the practical method for calculation and forecasting of industrial safety incidents. The article provides the proof of the theorem identifying the probability of system transition from an initial non-hazardous into a hazardous state, as well as an example of application of graph method for evaluation of probability of fire in a fixed facility. The proposed probability evaluation method can be used in planning of industrial safety measures in terms of specification of new states or rules of transition into associated states.

For space robots, it is difficult to track continuous time-varying manifolds on SE(3) by using traditional closed-loop control strategies, which are designed to track the position and the attitude separately. Therefore, the dynamics model should be rebuilt, and the corresponding control strategy should be redesigned. Firstly, the dynamics equations for a space robot in the joint space and workspace are established separately in the framework of Lie group SE(3) and screw theory based on the Lagrange principle. Secondly, based on the proposed feedback form, a PD (proportional derivative) control law of output force on the end-effector is designed, and a closed-loop continuous tracking control strategy is proposed using the force Jacobian matrix and the kinematic model. The simulation results show that the control scheme has good performance when the system state changes gently. Furthermore, a robust sliding mode tracking control scheme is designed. The simulation results show that the proposed robust control law has better accuracy than the PD control law because the system state changes wildly. Finally, a robust fuzzy sliding mode tracking control scheme is designed to deal with the chattering phenomenon. The simulation results show that the proposed robust fuzzy control law can eliminate the chattering well and decrease the joint control torque significantly. The robustness of the proposed robust fuzzy control law is also verified by numerical simulation.

近年来国内森林生态系统服务功能研究较多,但应用价值不高,其科学性受到诸多质疑。从森林水源涵养功能的多尺度内涵、过程以及其计量方法出发,对国内外研究动态和发展趋势进行了总结分析,重新审视森林水源涵养功能的研究意义,探讨森林水源涵养功能的多尺度特征。从森林水源涵养功能作用的空间尺度上看,其拦蓄洪水削减洪峰的功能仅在较小尺度上有效,而调节径流的功能只有当森林土壤的入渗量超过蒸散量时,才可能有更多地下水补给河道径流,进而增加旱季河道流量。同时森林水源涵养功能也具有明显的时间尺度特征,具体表现为在次降水事件中,由于蒸散发量较小,森林水源涵养功能的物质量等于森林不同层次的截留量,在功能上表现为拦蓄降水;在长时间尺度上,由于林地蒸散要耗去大量水分,森林水源涵养功能的物质量等于森林不同层次的截留量减去林地蒸散发量,在功能上表现为净化水质和调节径流。大多数研究仅对单一林分的个别层次蓄水功能进行研究,缺乏流域尺度或者更大空间尺度的森林水源涵养功能研究。建议从区域降尺度到流域或将坡面尺度上推到流域,集中在流域尺度解决森林水源涵养空间异质性将是解决森林水源涵养功能尺度外推的有效办法。就目前国内流行的森林水源涵养功能计量方法而言,其与尺度及研究目的有较大相关性,在研究中应根据研究目的、研究尺度和可获取的数据情况选择合适的计量方法。研究突出了不同尺度作用下森林水文过程的复杂性及重要性,并结合森林与水关系的争论问题,分析目前国内对森林水源涵养功能研究的一些误区,提出森林水源涵养功能研究的一些关键科学问题及未来可能的发展方向,主要包括:1)明确界定森林水源涵养功能的边界,探索森林水源涵养功能计量的新方法;2)加强不同时空尺度关联的森林水源涵养功能研究,包括正确评价森林水源涵养功能的时空变异规律,森林生态系统水源涵养功能的尺度效应,森林水源涵养与下游水生态安全,森林水源涵养研究范式转变等核心问题。;Forest water conservation as an important ecosystem function has caused a rising interests in the scientific community in recent years. However, there remain some arguments in several aspects regarding the forest water conservation function. For the concept of the forest water conservation, there is no clear definition about its connotation. Another concern is the scaling issue. It is a challenge to scale up the estimation for the forest water conservation from the plot scale to larger scale, e.g., watershed scale or regional scale. Many quantification methods have been developed, but their suitability, performance, advantages and disadvantages are unknown. Many of such argument issues are significant limits of the forest water conservation in science and management. On the basis of the literature review, we clarify the important role of the water conservation in forest ecosystem function. We also summarize and analyze the concepts of the forest water conservation and its multi-scale connotation, processes and quantification methods. On the spatial scale, function of the forest in mitigating peak flow is effective at a smaller scale but not necessarily at a larger scale. More groundwater recharges into stream flow when forest soil infiltration exceeds evapotranspiration, thus increasing stream flow in the dry season. During a rainfall event, forest water conservation has different features at different temporal scales. For example, the amount of the forest conservation during a rainfall event dominates by the forest canopy interception and most water is stored in the forest due to less evapotranspiration in the rainfall event scale. At the longer temporal scale, the forest water conservation can be determined by the forest canopy interception subtracting evapotranspiration. The functional roles of the forest water conservation at longer temporal scale dominate by purifying water from natural rainfall and mitigating seasonal flow peaks of the river discharges. Most previous studies of the forest water conservation focused on water storage function at the plot scale, but lack better understanding in the forest water conservation function at the watershed or regional scales. We suggest the approach that combines downscaling from the regional to watershed scales and upscaling from the hillside to the watershed scales can an effective way of the scale extrapolation. This idea can be used to address the heterogeneity issue of the forest water conservation function at different spatio-temporal scales. Among the existing quantification approaches of the forest water conservation function, each one highly relies on the temporal and spatial scales and its application goal. An appropriate calculation method should be carefully evaluated and considered based on the objectives, data availability, temporal and spatial scales of each study case. The suitability difference in different calculation methods of the forest water conservation demonstrates the complexity and importance of the multi-scale consideration in forest hydrological processes. In the context of the long-term debates about the relationship between the forest and water, we figure out a few confusing points in the current studies of the forest water conservation function. We also propose the critical scientific questions that should be addressed and a few directions in future studies of forest water conservation function including: 1) to clearly define the connotation and boundary of the forest water conservation function, and develop innovatory methods for determining the forest water conservation function; 2) to pay more attentions on the forest water conservation function studies associated with the different spatial and temporal scales, including evaluation of the spatio-temporal variations in forest water conservation function, the scaling effects on estimation of the water conservation function, the trade-off relationship between the upstream forest water conservation and the downstream ecological water need, and the development of the innovatory ways of forest water conservation practices.

Drinking water extracted near rivers in alluvial aquifers is subject to potential microbial contamination due to rapidly infiltrating river water during high discharge events. The heterogeneity of river-groundwater interaction and hydrogeological characteristics of the aquifer renders a complex pattern of groundwater quality. The quality of the extracted drinking water can be managed using decision support and HACCP (Hazard Analysis and Critical Control Point) systems, but the detection of potential contamination remains a complex task to master. The methodology proposed herein uses a combination of high-resolution measurements and multivariate statistical analyses to characterise actual groundwater quality and detect potential contamination. The aim of this project was to improve the protection of riverine groundwater extraction wells and to increase the degrees of freedom available to the management of fluvial planes with drinking-water production and aquifer recharge by river-groundwater interaction. The monitoring network was set up in the Reinacherheide in North-west Switzerland and encompassed the depth-oriented installation of multiparameter instruments, a surface-water monitoring station and a flow-through cell with an automated sampler and high-precision measurement instruments. The parameters recorded included temperature, electrical conductivity, spectral absorption coefficient, particle density and turbidity. Two of the observation wells were equipped with a telemetry system and the flow cell could be controlled remotely. The well-field encompassed eight groundwater extraction wells. The optimal choice of observation wells and indicator parameters was assessed using principal component analysis of groundwater head, temperature and electrical conductivity time-series to detect the influence of, for example, river-water infiltration or river-stage fluctuations on the time-series recorded in the groundwater observation wells. Groundwater head was susceptible to pressure waves induced by both river-stage fluctuations and groundwater extraction. Temperature time-series showed only weak responses to high discharge events. Electrical conductivity, however, showed a distance-driven response pattern to high discharge events. To further assess the representative strength of individual groundwater quality indicator parameters for identifying microbial contamination, a bi-weekly and a high-resolution sampling campaign were carried out. The results showed high faecal-indicator bacteria densities (E. coli and Enterococcus sp.) at the beginning of high discharge events, followed by a rapid decrease, leading to a strong hit-and-miss characteristic in the bi-weekly sampling campaign. The third approach applied used the neural network-based combination of self-organizing maps and Sammon's projection (SOM-SM) to detect shifts in groundwater quality system states. The nonlinear analysis was carried out with groundwater head, temperature and electrical conductivity time-series from six observation wells. The subsequent shading of the projected trajectory of system states with independent time-series (spectral absorption coefficient and particle density) allowed the identification of critical system states, when actual groundwater quality decreased and contamination of the extraction wells was imminent. The time at which the changes in system state occurred and were detected were used as potential warning indicators for the water supplier. The effects of altered groundwater extraction (as a consequence of the SOM-SM warning) were then simulated using a groundwater flow model. The outcome of the SOM-SM analysis is, thus, proposed as an interface between the monitoring system and extraction-well management system. The proposed approach incorporates hydrogeological knowledge and the analysis of prevalent conditions concerning river-groundwater interaction with real-time telemetric data transfer, data-base management and nonlinear statistical analysis to detect deterioration in actual groundwater quality due to rapidly infiltrating river water. As the SOM-SM is not based on threshold values and independent of indicator parameters, the approach can be transferred to other sites with similar characteristics.

Beginning from the second-order input constraint systems, the paper pays attention to study the control prob- lem for a class of the constraint systems with the nalyzes the stability of the second-order input constraint systems under the condition of linear state feedback. On the basis of that, it gives the non-smooth feedback control law of the third-order state constraint systems. At the same time, it sets up the relationship between system's steady state and its initial condi- tions. Finally, it has verified the validity of the conclusion by simulation. In the daily life, systems usually work under the condi- tion of some constraints or limits which is often showed by one link from systems that has been affected by a certain degree of the characteristics of saturation nonlinearity. Influ- enced by saturation nonlinearity, this kind of systems will make the analysis and design of the systems difficult because it is not only deferent from normal one in system perfor- mance, but also difficult to adopt common means to judge its stability, especially for the situation that the change of some system state affected by the saturation nonlinearity, under which it is very difficult to use existing methods to analyze the stability of the systems. Therefore, judging from the re- searches on saturation nonlinearity control problem, there is not an effective theoretical framework to solve the stability of the systems and the design. However, although saturation nonlinearity on independent variable is continuous, it is not continuous for the derivative of variable. So that is a kind of non- smooth nonlinearity which has the system with satura- tion nonlinear. What's more, in essence, it is a class of non- smooth system, whose control problem can be considered from non-smooth control theories and design methods. Just from the perspective of non-smooth feedback design view, this paper studies that the change of system state has the con- trol problem of saturation non-linear constraint systems. In fact, as for the control problem of the system with sat- uration nonlinearity, there has been a lot of research achievements published. Reference (1) gives the sufficient and necessary condition of system stability for the reliability problem of a class of linear saturation nonlinear system. That condition shows that, in the case that the state of linearity system is completely affected by saturation nonlinearity, the system would make the global asymptotic stability come true if the system matrix met certain conditions. Especially for the second-order system, it is required that System Matrix A belongs to Hurwitz's with a line which has diagonally domi- nant characteristic. Reference (2), based on Reference (1), further discusses the convergence problem for the second- order system. In regard to the study of the second-order sys- tem, it can be found that Reference (3) studies detailed the track of a class of the second-order system under the condi- tion of saturation constraints (4). And input limited system is discussed in Reference (4) where there are the design meth- ods that linear system gets the maximum convergence rate of elliptic invariant sets in the sate of saturation constraints. These research results generally focus on a class of systems whose saturation nonlinearity has an effect on all the system states, and the restricted states of many systems are usually limited in practice (5-7). T hus, the conclusion above can not be used directly. This paper studies a class of systems which is in the lim- ited state. The systems have three states, among which there is a kind of state-saturation nonlinearity-which is often seen under the condition of actuator torque limited. Firstly, the paper starts with the feedback designs with the state of the second-order input constraint systems and draws the conclu- sion of the stability of the systems that are in the status of linearity. And then, the linear state feedback controller gotten by the second-order system directly extends to the target sys- tem and gets non-smooth feedback controller. At the same time, it further discusses the relationship between system sta- bility and initial conditions and establishes the relationship between the two. Finally, it has verified the conclusion under different initial conditions by numerical simulation.

Event detection and localization is at the heart of all automated system restoration processes. Localizing an event can help in alleviating the root cause behind such disturbances. During an event, the operating states of the power distribution network may undergo significant changes. These variations are more prominent in buses which are close to the source of the event. Thus, events in a distribution system can be localized by analyzing the changes in the system states. This paper proposes an event locator based on the results of a event triggered distribution network state estimator. The state estimation is performed using measurements from a limited number of micro phasor measurement units (μ PMUs). An l 1 regularization based state estimator is designed to estimate the change in system states, using limited number of μ PMU measurements. The results of the state estimation process are further analyzed to locate any event. The algorithm is designed for active distribution networks with radial and meshed topologies. The proposed method is validated on a 13-node test distribution feeder simulated using OPAL-RT real-time simulator.

In some applications, an indicator is needed for sudden system state changes, where the direct measurement of the system states is neither possible nor practical. In this brief, it is shown that the error of robust integral of the sign of the error observer can be used as an indicator of sudden system state changes. The application of this method for collision detection in a linear vapor compressor is investigated. Linear vapor compressors are becoming more widely utilized in cooling appliances, such as household refrigerators and portable coolers due to their high efficiency. The fact that the piston is free in a linear vapor compressor allows for the possibility of collisions between the compressor piston and other components of the linear vapor compressor within the compression chamber. Sensorless crash detection is preferred for purposes of reliability, ease of production, and cost effectiveness. For this purpose, a novel head crash detection scheme applying a nonlinear observer is developed. This scheme not only detects all head crashes accurately, but also provides an indicator proportional to the piston velocity at the time of impact. This indicator can be used to estimate how much the force command needs to be reduced to prevent further collision. A set of simulation and experimental test results validate the performance of the head crash detection scheme.

The variation of parameter settings and their effects on performance for the simulated annealing algorithm

Temporal and spatial scales play important roles in fishery ecology, and an inappropriate spatio-temporal scale may result in large errors in modeling fish distribution. The objective of this study is to evaluate the roles of spatio-temporal scales in habitat suitability modeling, with the western stock of winter-spring cohort of neon flying squid (Ommastrephes bartramii) in the northwest Pacific Ocean as an example. In this study, the fishery-dependent data from the Chinese Mainland Squid Jigging Technical Group and sea surface temperature (SST) from remote sensing during August to October of 2003–2008 were used. We evaluated the differences in a habitat suitability index model resulting from aggregating data with 36 different spatial scales with a combination of three latitude scales (0.5°, 1° and 2°), four longitude scales (0.5°, 1°, 2° and 4°), and three temporal scales (week, fortnight, and month). The coefficients of variation (CV) of the weekly, biweekly and monthly suitability index (SI) were compared to determine which temporal and spatial scales of SI model are more precise. This study shows that the optimal temporal and spatial scales with the lowest CV are month, and 0.5° latitude and 0.5° longitude for O. bartramii in the northwest Pacific Ocean. This suitability index model developed with an optimal scale can be cost-effective in improving forecasting fishing ground and requires no excessive sampling efforts. We suggest that the uncertainty associated with spatial and temporal scales used in data aggregations needs to be considered in habitat suitability modeling.

We questioned the different interpretations of ecological sexual segregation from a novel perspective, i.e., by carrying out diverse temporal and spatial scale analyses within a long-term study (1984–2003). Thus we combined spatial (small/large) and temporal (small/large) scale analyses to identify the factors generating sexual segregation in fallow deer in San Rossore, Italy. The study site was divided into an eastern sector characterized by human disturbance (DS) and a western undisturbed sector (US). According to census data, human presence increased in DS from 1984, and while females gradually abandoned it, males remained—thus supporting the predation risk hypothesis (large spatial and temporal scale)—and actually increased their presence in DS, where they seemingly benefited from a lower female density. This supported the indirect competition hypothesis. The analysis of data on a large temporal and small spatial scale confirmed that intersexual competition, in particular for grass, was higher in a crowded pasture in US. Observations by means of radio-telemetry of 23 adult females and 25 adult males (1997–2001, reduced temporal and large spatial scale) showed that large scale segregation was relevant during the day and disappeared at night, when disturbance was absent and also the females reached DS. This also supported the predation risk hypothesis. Moreover, sexes showed different habitat choices inside DS at night, thus supporting the forage selection hypothesis (small spatial and temporal scale). In conclusion, failure to address the whole set of combinations of spatial and temporal scale analyses would have led to monocausal explanations of ecological sexual segregation.

Analysis of dynamic behavior in p-persistent CSMA/CD using cusp catastrophe

Abstract: This study explored the potential for enhancing pilot performance via an alerting system that adapts according to an eye-tracking-based measure of monitoring. The novel measure combines gaze analysis with system state assessment to estimate the pilot’s understanding of the current system state. On this basis, an alerting system was developed to direct pilot attention to unnoticed system state changes, thereby improving system state monitoring. In a flight simulator study involving 10 participants in a generic jet cockpit, we compared the adaptive alerting system with a no-assistance condition. Although alerting improved the participants’ performance in two tracking tasks, it adversely impacted performance in a third task. Nonetheless, alerting resulted in a decrease in both variance and mean detection time of critical changes. Participants’ subjective ratings were generally positive, yet they criticized the lack of transparency of the alerting mechanism. Alerts triggered based on eye-tracking and system state show potential for improving operator task performance. Nonetheless, for the system to reach its full performance potential, it is critical that the operator understand the principles underlying the alert triggers. False positives and alert design were identified as key areas for improvement to maintain user trust and task flow.

Event-driven architecture (EDA) facilitates the efficient generation and processing of events, which signify changes in system states. This architectural paradigm enhances the flexibility of system interactions, streamlines cross-system processes, and enables near real-time updates. In an event-driven model, events are produced irrespective of whether consumers are actively listening, and consumers do not send acknowledgments upon receipt. The key components of EDA include event producers, event consumers, event channels, event messages, and events themselves. EDA is particularly beneficial for large-scale distributed systems as it eliminates direct dependencies between event producers and consumers, simplifying system interactions. This paper presents a comparative analysis of various EDA models, their applications across industries, and their advantages in promoting scalability while reducing system coupling. Although various event-driven architectures are examined, the primary focus of this article is on Salesforce Event-Driven Architecture and its applications.

Predicting modes of spatial change from state-and-transition models