Dynamic energy absorption characteristics of foam-filled conical tubes under oblique impact loading

This paper treats the crush behaviour and energy absorption response of foam-filled conical tubes subjected to oblique impact loading. Dynamic computer simulation techniques validated by experimental testing are used to carry out a parametric study of such devices. The study aims at quantifying the energy absorption of empty and foam-filled conical tubes under oblique impact loading, for variations in the load angle and geometry parameters of the tube. It is evident that foam-filled conical tubes are preferable as impact energy absorbers due to their ability to withstand oblique impact loads as effectively as axial impact loads. Furthermore, it is found that the energy absorption capacity of filled tubes is better maintained compared to that of empty tubes as the load orientation increases. The primary outcome of this study is design information for the use of foam-filled conical tubes as energy absorbers where oblique impact loading is expected.

Design of a capacitor supported dynamic voltage restorer (DVR) for unbalanced and distorted loads

The paper discusses the operating principles and control characteristics of a dynamic voltage restorer (DVR) that protects sensitive but unbalanced and/or distorted loads. The main aim of the DVR is to regulate the voltage at the load terminal irrespective of sag/swell, distortion, or unbalance in the supply voltage. In this paper, the DVR is operated in such a fashion that it does not supply or absorb any active power during the steady-state operation. Hence, a DC capacitor rather than a DC source can supply the voltage source inverter realizing the DVR. The proposed DVR operation is verified through extensive digital computer simulation studies.

Performance comparison of VSC-based shunt and series compensators used for load voltage control in distribution systems

In this paper, the performance of voltage-source converter-based shunt and series compensators used for load voltage control in electrical power distribution systems has been analyzed and compared, when a nonlinear load is connected across the load bus. The comparison has been made based on the closed-loop frequency resopnse characteristics of the compensated distribution system. A distribution static compensator (DSTATCOM) as a shunt device and a dynamic voltage restorer (DVR) as a series device are considered in the voltage-control mode for the comparison. The power-quality problems which these compensator address include voltage sags/swells, load voltage harmonic distortions, and unbalancing. The effect of various system parameters on the control performance of the compensator can be studied using the proposed analysis. In particular, the performance of the two compensators are compared with the strong ac supply (stiff source) and weak ac-supply (non-still source) distribution system. The experimental verification of the analytical results derived has been obtained using a laboratory model of the single-phase DSTATCOM and DVR. A generalized converter topology using a cascaded multilevel inverter has been proposed for the medium-voltage distribution system. Simulation studies have been performed in the PSCAD/EMTDC software to verify the results in the three-phase system.

Dynamic response of distributed generators in a hybrid microgrid

A microgrid may be supplied from inertial (rotating type) and non-inertial (converter-interfaced) distributed generators (DGs). However the dynamic response of these two types of DGs is different. Inertial DGs have a slower response due to their governor characteristics while non inertial DGs have the ability to respond very quickly. The focus of this paper is to propose better controls using droop characteristics to improve the dynamic interaction between different DG types in an autonomous microgrid. The transient behavior of DGs in the microgrid is investigated during the DG synchronization and load changes. Power sharing strategies based on frequency and voltage droop are considered for DGs. Droop control strategies are proposed for DGs to improve the smooth synchronization and dynamic power sharing minimizing transient oscillations in the microgrid. Simulation studies are carried out on PSCAD for validation.

Load modelling : induction motors

Modelling the power systems load is a challenge since the load level and composition varies with time. An accurate load model is important because there is a substantial component of load dynamics in the frequency range relevant to system stability. The composition of loads need to be charaterised because the time constants of composite loads affect the damping contributions of the loads to power system oscillations, and their effects vary with the time of the day, depending on the mix of motors loads. This chapter has two main objectives: 1) describe the load modelling in small signal using on-line measurements; and 2) present a new approach to develop models that reflect the load response to large disturbances. Small signal load characterisation based on on-line measurements allows predicting the composition of load with improved accuracy compared with post-mortem or classical load models. Rather than a generic dynamic model for small signal modelling of the load, an explicit induction motor is used so the performance for larger disturbances can be more reliably inferred. The relation between power and frequency/voltage can be explicitly formulated and the contribution of induction motors extracted. One of the main features of this work is the induction motor component can be associated to nominal powers or equivalent motors

Induction motor load impact on power system eigenvalue sensitivity analysis

Load modelling plays an important role in power system dynamic stability assessment. One of the widely used methods in assessing load model impact on system dynamic response is parametric sensitivity analysis. A composite load model-based load sensitivity analysis framework is proposed. It enables comprehensive investigation into load modelling impacts on system stability considering the dynamic interactions between load and system dynamics. The effect of the location of individual as well as patches of composite loads in the vicinity on the sensitivity of the oscillatory modes is investigated. The impact of load composition on the overall sensitivity of the load is also investigated.

Dynamic compression improves biosynthesis of human zonal chondrocytes from osteoarthritis patients

Objective: We hypothesize that chondrocytes from distinct zones of articular cartilage respond differently to compressive loading, and that zonal chondrocytes from osteoarthritis (OA) patients can benefit from optimized compressive stimulation. Therefore, we aimed to determine the transcriptional response of superficial (S) and middle/deep (MD) zone chondrocytes to varying dynamic compressive strain and loading duration. To confirm effects of compressive stimulation on overall matrix production, we subjected zonal chondrocytes to compression for 2 weeks. Design: Human S and MD chondrocytes from osteoarthritic joints were encapsulated in 2% alginate, pre-cultured, and subjected to compression with varying dynamic strain (5, 15, 50% at 1 Hz) and loading duration (1, 3, 12 h). Temporal changes in cartilage-specific, zonal, and dedifferentiation genes following compression were evaluated using quantitative real-time reverse transcriptase polymerase chain reaction (qRT-PCR). The benefits of long-term compression (50% strain, 3 h/day, for 2 weeks) were assessed by measuring construct glycosaminoglycan (GAG) content and compressive moduli, as well as immunostaining. Results: Compressive stimulation significantly induced aggrecan (ACAN), COL2A1, COL1A1, proteoglycan 4 (PRG4), and COL10A1 gene expression after 2 h of unloading, in a zone-dependent manner (P < 0.05). ACAN and PRG4 mRNA levels depended on strain and load duration, with 50% and 3 h loading resulting in highest levels (P < 0.05). Long-term compression increased collagen type II and ACAN immunostaining and total GAG (P < 0.05), but only S constructs showed more PRG4 stain, retained more GAG (P < 0.01), and developed higher compressive moduli than non-loaded controls. Conclusions: The biosynthetic activity of zonal chondrocytes from osteoarthritis joints can be enhanced with selected compression regimes, indicating the potential for cartilage tissue engineering applications. © 2012 Osteoarthritis Research Society International.

Integrated health prediction of bridge systems using dynamic object oriented Bayesian networks (DOOBNS)

The serviceability and safety of bridges are crucial to people’s daily lives and to the national economy. Every effort should be taken to make sure that bridges function safely and properly as any damage or fault during the service life can lead to transport paralysis, catastrophic loss of property or even casualties. Nonetheless, aggressive environmental conditions, ever-increasing and changing traffic loads and aging can all contribute to bridge deterioration. With often constrained budget, it is of significance to identify bridges and bridge elements that should be given higher priority for maintenance, rehabilitation or replacement, and to select optimal strategy. Bridge health prediction is an essential underpinning science to bridge maintenance optimization, since the effectiveness of optimal maintenance decision is largely dependent on the forecasting accuracy of bridge health performance. The current approaches for bridge health prediction can be categorised into two groups: condition ratings based and structural reliability based. A comprehensive literature review has revealed the following limitations of the current modelling approaches: (1) it is not evident in literature to date that any integrated approaches exist for modelling both serviceability and safety aspects so that both performance criteria can be evaluated coherently; (2) complex system modelling approaches have not been successfully applied to bridge deterioration modelling though a bridge is a complex system composed of many inter-related bridge elements; (3) multiple bridge deterioration factors, such as deterioration dependencies among different bridge elements, observed information, maintenance actions and environmental effects have not been considered jointly; (4) the existing approaches are lacking in Bayesian updating ability to incorporate a variety of event information; (5) the assumption of series and/or parallel relationship for bridge level reliability is always held in all structural reliability estimation of bridge systems. To address the deficiencies listed above, this research proposes three novel models based on the Dynamic Object Oriented Bayesian Networks (DOOBNs) approach. Model I aims to address bridge deterioration in serviceability using condition ratings as the health index. The bridge deterioration is represented in a hierarchical relationship, in accordance with the physical structure, so that the contribution of each bridge element to bridge deterioration can be tracked. A discrete-time Markov process is employed to model deterioration of bridge elements over time. In Model II, bridge deterioration in terms of safety is addressed. The structural reliability of bridge systems is estimated from bridge elements to the entire bridge. By means of conditional probability tables (CPTs), not only series-parallel relationship but also complex probabilistic relationship in bridge systems can be effectively modelled. The structural reliability of each bridge element is evaluated from its limit state functions, considering the probability distributions of resistance and applied load. Both Models I and II are designed in three steps: modelling consideration, DOOBN development and parameters estimation. Model III integrates Models I and II to address bridge health performance in both serviceability and safety aspects jointly. The modelling of bridge ratings is modified so that every basic modelling unit denotes one physical bridge element. According to the specific materials used, the integration of condition ratings and structural reliability is implemented through critical failure modes. Three case studies have been conducted to validate the proposed models, respectively. Carefully selected data and knowledge from bridge experts, the National Bridge Inventory (NBI) and existing literature were utilised for model validation. In addition, event information was generated using simulation to demonstrate the Bayesian updating ability of the proposed models. The prediction results of condition ratings and structural reliability were presented and interpreted for basic bridge elements and the whole bridge system. The results obtained from Model II were compared with the ones obtained from traditional structural reliability methods. Overall, the prediction results demonstrate the feasibility of the proposed modelling approach for bridge health prediction and underpin the assertion that the three models can be used separately or integrated and are more effective than the current bridge deterioration modelling approaches. The primary contribution of this work is to enhance the knowledge in the field of bridge health prediction, where more comprehensive health performance in both serviceability and safety aspects are addressed jointly. The proposed models, characterised by probabilistic representation of bridge deterioration in hierarchical ways, demonstrated the effectiveness and pledge of DOOBNs approach to bridge health management. Additionally, the proposed models have significant potential for bridge maintenance optimization. Working together with advanced monitoring and inspection techniques, and a comprehensive bridge inventory, the proposed models can be used by bridge practitioners to achieve increased serviceability and safety as well as maintenance cost effectiveness.

Dynamic optimization of migration topology in internet-based distributed genetic algorithms

Distributed Genetic Algorithms (DGAs) designed for the Internet have to take its high communication cost into consideration. For island model GAs, the migration topology has a major impact on DGA performance. This paper describes and evaluates an adaptive migration topology optimizer that keeps the communication load low while maintaining high solution quality. Experiments on benchmark problems show that the optimized topology outperforms static or random topologies of the same degree of connectivity. The applicability of the method on real-world problems is demonstrated on a hard optimization problem in VLSI design.

Dynamic effects of electrical pitting in steam-turbine tilting-pad thrust-bearings

This paper merges the analysis of a case history and the simplified theoretical model related to a rather singular phenomenon that may happen in rotating machinery. Starting from the first, a small industrial steam turbine experienced a very strange behavior during megawatt load. When the unit was approaching the maximum allowed power, the temperature of the babbitt metal of the pads of the thrust bearing showed constant increase with an unrecoverable drift. Bearing inspection showed that pad trailing edge had the typical aspect of electrical pitting. This kind of damage was not reparable and bearing pads had to replaced. This problem occurred several times in sequence and was solved only by adding further ground brushes to the shaft-line. Failure analysis indicated electrodischarge machining as the root fault. A specific model, able to take into consideration the effect of electrical pitting and loading capacity decreasing as a consequence of the damage of the babbitt metal, is proposed in the paper and shows that the phenomenon causes the irretrievable failure of the thrust bearing.

Optimisation of lateral load-resisting systems in composite high-rise buildings

This research is carried out by using finite element modelling of building prototypes with three different layouts (rectangular, octagonal and L-shaped) for three different heights (98.0 m, 147.0 m and 199.5 m) for the optimization of lateral load-resisting systems in composite high-rise buildings. Variations of lateral bracings (different number and varied placement along model height of belt-truss and outrigger floors) with RCC (reinforced cement concrete) core wall are used in composite high-rise building models. Prototypes of composite buildings are analysed for dynamic wind and seismic loads. The effects on serviceability (deflection and frequency) of models are studied and conclusions are deduced.

Voltage unbalance reduction in low voltage feeders by dynamic switching of residential customers among three phases

Low voltage distribution feeders with large numbers of single phase residential loads experience severe current unbalance that often causes voltage unbalance problems. The addition of intermittent generation and new loads in the form of roof top photovoltaic generation and electric vehicles makes these problems even more acute. In this paper, an intelligent dynamic residential load transfer scheme is proposed. Residential loads can be transferred from one phase to another phase to minimize the voltage unbalance along the feeder. Each house is supplied through a static transfer switch with three-phase input and single-phase output connection. The main controller, installed at the transformer will observe the power consumption in each load and determine which house(s) should be transferred from one phase to another in order to keep the voltage unbalance in the feeder at a minimum. The efficacy of the proposed load transfer scheme is verified through MATLAB and PSCAD/EMTDC simulations.

The application of BESS in load shedding scheme

With new developments in battery technologies, increasing application of Battery Energy Storage System (BESS) in power system is anticipated in near future. BESS has already been used for primary frequency regulation in the past. This paper examines the feasibility of using BESS with load shedding, in application for large disturbances in power system. Load shedding is one of the conventional ways during large disturbances, and the performance of frequency control will increase in combination with BESS application. According to the latest news, BESS which are applied in high power side will be employed in practice in next 5 year. A simple low order SMR model is used as a test system, while an incremental model of BESS is applied in this paper. As continuous disturbances are not the main concern in this paper, df/dt is not considered in article.

Vertical dynamic interaction of trains and rail steel bridges

Rail steel bridges are vulnerable to high impact forces due to the passage of trains; unfortunately the determination of these transient impact forces is not straightforward as these are affected by a large number of parameters, including the wagon design, the wheel-rail contact and the design parameters of the bridge deck and track, as well as the operational parameters – wheel load and speed. To determine these impact forces, a detailed rail train-track/bridge dynamic interaction model has been developed, which includes a comprehensive train model using multi-body dynamics approach and a flexible track/bridge model using Euler– Bernoulli beam theory. Single and multi-span bridges have been modelled to examine their dynamic characteristics. From the single span bridge, the train critical speed is determined; the minimum distance of two peak loadings is found to affect the train critical speed. The impact factor and the dynamic characteristics are discussed.

Lower partial moment and information entropy-based dynamic electricity purchasing strategy

In the electricity market environment, load-serving entities (LSEs) will inevitably face risks in purchasing electricity because there are a plethora of uncertainties involved. To maximize profits and minimize risks, LSEs need to develop an optimal strategy to reasonably allocate the purchased electricity amount in different electricity markets such as the spot market, bilateral contract market, and options market. Because risks originate from uncertainties, an approach is presented to address the risk evaluation problem by the combined use of the lower partial moment and information entropy (LPME). The lower partial moment is used to measure the amount and probability of the loss, whereas the information entropy is used to represent the uncertainty of the loss. Electricity purchasing is a repeated procedure; therefore, the model presented represents a dynamic strategy. Under the chance-constrained programming framework, the developed optimization model minimizes the risk of the electricity purchasing portfolio in different markets because the actual profit of the LSE concerned is not less than the specified target under a required confidence level. Then, the particle swarm optimization (PSO) algorithm is employed to solve the optimization model. Finally, a sample example is used to illustrate the basic features of the developed model and method.