Search

Droughts are often long-lasting phenomena, without a distinct start or end and with impacts cascading across sectors and systems, creating long-term legacies. Nevertheless, our current perceptions and management of droughts and their impacts are often event-based, which can limit the effective assessment of drought risks and reduction of drought impacts. Here, we advocate for changing this perspective and viewing drought as a hydrological–ecological–social continuum. We take a systems theory perspective and focus on how “memory” causes feedback and interactions between parts of the interconnected systems at different timescales. We first discuss the characteristics of the drought continuum with a focus on the hydrological, ecological, and social systems separately, and then we study the system of systems. Our analysis is based on a review of the literature and a study of five cases: Chile, the Colorado River basin in the USA, northeast Brazil, Kenya, and the Rhine River basin in northwest Europe. We find that the memories of past dry and wet periods, carried by both bio-physical (e.g. groundwater, vegetation) and social systems (e.g. people, governance), influence how future drought risk manifests. We identify four archetypes of drought dynamics: impact and recovery, slow resilience building, gradual collapse, and high resilience–big shock. The interactions between the hydrological, ecological, and social systems result in systems shifting between these types, which plays out differently in the five case studies. We call for more research on drought preconditions and recovery in different systems, on dynamics cascading between systems and triggering system changes, and on dynamic vulnerability and maladaptation. Additionally, we advocate for more continuous monitoring of drought hazards and impacts, modelling tools that better incorporate memories and adaptation responses, and management strategies that increase societal and institutional memory. This will help us to better deal with the complex hydrological–ecological–social drought continuum and identify effective pathways to adaptation and mitigation.

Multi-Speed resolvers are desirable position sensors for high performance closed-loop control of inverter driven machines due to their high accuracy. However, developing a winding with high number of poles with limited number of slots is a main challenge in achieving multi-speed function. Therefore, in this paper different winding configuration are proposed to achieve 5-X performance of a disk type wound-rotor resolver. Then, the best winding is chosen for experimental verification. In addition to the accuracy of the sensor, the optimal winding selection index is defined considering copper usage, number of winding layers (overlapping or non-overlapping configurations), the number of turns for each coil of the winding (variable or constant turn configurations), and the amplitude of the fundamental harmonic. An objective function is defined involving all the mentioned indices with different weights determined based on the importance of each index. Finally, a prototype of the sensor with the best winding is built and tested. The experimental measurements verify the results of the simulations that are obtained using 3-D time setting finite element analysis.

Background and Objectives: Wound-Rotor resolvers are the most widely used position sensors in applications with harsh environmental conditions.Methods the resolver performance is exposed to failure due to the high risk of short circuit (SC) fault. Although the output current of the resolver is negligible, its thin copper wires increase the probability of the short circuit fault. To avoid the propagation of the turn-to-turn SC fault to the whole coil and undesirable performance of the motion control drive, it is necessary to diagnose it at the very beginning of its development. Meanwhile, the first step of diagnosing faults is their modeling. Time stepping finite element analysis is the most accurate, but computationally expensive method for modeling electromagnetic devices. Therefore, it is required to establish an accurate,Results: In this paper, an analytical model based on d-q axes theory is proposed to consider multiple faults, simultaneously. Then, the success of the proposed model is validated by experimental tests on the studied sensor.Conclusion: the proposed model is fast and accurate, so it can be used for the design process.

Disk Type Variable Reluctance (DTVR) resolvers have distinguished performance under run out fault comparing to conventional sinusoidal rotor resolvers. However, their accuracy under inclined rotor fault along with different types of eccentricities includes static and dynamic eccentricities are questioned. Furthermore, due to thin copper wires that are used for signal and excitation coils of resolver there is high risk of short circuit fault in the coils. So, in this study the performance of the sinusoidal rotor DTVR resolver under the mentioned faults are studied. The quality of output voltages along with position error of the sensor is discussed. 3-D time stepping finite element method is used to show the effect of different faults. Finally, the prototype of the studied resolver is constructed and tested. The employed test bed is built in such a way that is able to apply controllable level of different mechanical faults. Good agreement is obtained between the finite element and the experimental results, validating the success of the presented analysis.

Resolvers are widely used in electric driven systems especially in high precision servomechanisms. Both encapsulated and pancake resolvers suffer from a major drawback: static eccentricity (SE). This drawback causes a significant increase in resolver output position error (RPE) which could not be corrected electronically. To reduce RPE, this paper proposes a novel structure with axial flux. Proposed topology, design guidelines, optimization procedure and several key features to improve the sensitivity of axial flux resolver (AFR) against SE are studied. Furthermore, to minimize RPE an optimized design is attained. The machines are investigated in detail by using d-q model and 3D time stepping finite-element analysis. The results of theses two methods are compared and both prototype machines (proposed and optimized) are built. In order to evaluate proposed topologies, an experimental test setup is devised. Finally, the experimental results of the prototype machines verified the analysis results.

In this paper particle swarm optimization (PSO) is used for a design optimization of a linear permanent magnet synchronous motor (LPMSM) considering ultra low thrust force ripples, low magnet consumption, improved efficiency and thrust. The influence of PM material is discussed, too and the modular poles are proposed to achieve the best characteristic. PM dimensions and material, air gap and motor width are chosen as design variables. Finally 2-D finite element analyses validate the optimization results.

In this paper a brushless permanent magnet motor is designed considering minimum thrust ripple and maximum thrust density (the ratio of the thrust to permanent magnet volumes). Particle Swarm Optimization (PSO) is used as optimization method. Finite element analysis (FEA) is carried out base on the optimized and conventional geometric dimensions of the motor. The results of the FEA deal to the significant improvement of the all objective functions.

A mathematical model based on d-q axis theory and dynamic performance characteristic of brushless resolvers is discussed in this paper. The impact of rotor eccentricity on the accuracy of position in precise applications is investigated. In particular, the model takes the stator currents of brushless resolver into account. The proposed model is used to compute the dynamic and steady state equivalent circuit of resolvers. Finally, simulation results are presented. The validity and usefulness of the proposed method are thoroughly verified with experiments.

Because of temperature independence, high resolution and noiseless outputs, brushless resolvers are widely used in high precision control systems. In this paper, at first dynamic performance characteristics of brushless resolver, considering parameters identification are presented. Then a mathematical model based on d-q axis theory is given. This model can be used for studying the dynamic behavior of the resolver and steady state model is obtained by using dynamic model. The main object of this paper is to present an approach to identify electrical and mechanical parameters of a brushless resolver based on DC charge excitation and weight, pulley and belt method, respectively. Finally, the model of resolver based on the obtained parameters is simulated. Experimental results approve the validity of proposed method.

Hunting is a flutter associated with the synchronous speed that gives rise to the gyro drifting errors and may cause objectionable time-displacement errors in video head wheel drives and other precision scanning systems. In this paper, dynamic characteristics of permanent Magnet hysteresis motors are presented and hunting is explained. New damping techniques have been developed using optimized eigenvalues calculation. They are calculated from LQR optimization method. In this damping method, a distinct reduction in hunting has been archived. Furthermore field oriented control result of motor is presented that have good effect on Hunting. Nearest agreement between simulated and measurement results shows the accuracy of motor model. Comparison between this paper results and other measured damping methods result are shown its success.

The future risk for droughts and water shortages calls for substantial efforts by authorities to adapt at local levels. Understanding their perception of drought hazards, risk and vulnerability can help to identify drivers of and barriers to drought risk planning and management in a changing climate at the local level. This paper presents a novel interdisciplinary drought case study in Sweden that integrates soft data from a nationwide survey among more than 100 local practitioners and hard data based on hydrological measurements to provide a holistic assessment of the links between drought severity and the perceived levels of drought severity, impacts, preparedness, and management for two consecutive drought events. The paper highlights challenges for drought risk planning and management in a changing climate at the local level and elaborates on how improved understanding of local practitioners to plan for climate change adaptation can be achieved., (© 2023. The Author(s).)

For climate-change impact studies at the catchment scale, meteorological variables are typically extracted from ensemble simulations provided by global and regional climate models, which are then downscaled and bias-adjusted for each study site. For bias adjustment, different statistical methods that re-scale climate model outputs have been suggested in the scientific literature. They range from simple univariate methods that adjust each meteorological variable individually, to more complex and more demanding multivariate methods that take existing relationships between meteorological variables into consideration. Over the past decade, several attempts have been made to evaluate such methods in various regions. There is, however, still no guidance for choosing appropriate bias adjustment methods for a study at hand. In particular, the question whether the benefits of potentially improved adjustments outweigh the cost of increased complexity, remains unanswered. This paper presents a comprehensive evaluation of the performance of two commonly used univariate and two multivariate bias adjustment methods in reproducing numerous univariate, multivariate and temporal features of precipitation and temperature series in different catchments in Sweden. The paper culminates in a discussion on trade-offs between the potential benefits (i.e., skills and added value) and disadvantages (complexity and computational demand) of each method to offer plausible, defensible and actionable insights from the standpoint of climate-change impact studies in high latitudes. We concluded that all selected bias adjustment methods generally improved the raw climate model simulations, but that not a single method consistently outperformed the other methods. There were, however, differences in the methods' performance for particular statistical features, indicating that other practical aspects such as computational time and heavy theoretical requirements should also be taken into consideration when choosing an appropriate bias adjustment method., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 The Authors. Published by Elsevier B.V. All rights reserved.)