Balance Energy Dissipation Research Articles

Unveiling the Architectural Impact on the Salt-Tunable Adhesion Performance and Toughness of Polyzwitterions.

Developing tough adhesives with superior strength and ductility is challenging yet highly sought-after. In this work, we address a strategic approach to achieving diverse toughness and performance by meticulously harnessing weak electrostatic interactions. Two polyzwitterions (PZIs), derived from sulfobetaine methacrylate (SBMA), of different topologies: bottlebrush (BB-PSBMA) and linear (L-PSBMA), were designed. BB-PSBMA was synthesized using a rational "grafting-from" strategy, while L-PSBMA was prepared via atom transfer radical polymerization. Despite their architectural disparities, both PZIs demonstrated a comparable substantial lap-shear adhesion strength of ∼0.4 MPa. Intriguingly, the introduction of NaCl during adhesive preparation revealed contrasting adhesion behaviors. BB-PSBMA transitioned from a strong-brittle to strong-ductile adhesive upon the addition of 70 mM NaCl, evidenced by a 77.4% increase in the work of debonding, i.e., toughness. Further increases in NaCl concentration continued to impart the ductile properties to BB-PSBMA. Conversely, L-PSBMA adhesive predominantly transformed from strong-brittle to ductile regardless of the salt content. We propose a synergistic mechanism involving viscosity-governed optimal adhesion-cohesion balance and mechanical energy dissipation through sacrificial electrostatic association to elucidate the strong and ductile nature of the BB-PSBMA adhesive at 70 mM NaCl. Our findings emphasize the significance of precise control over architecture and salt concentration is necessary in constructing adhesives with enhanced toughness and performance.

Exploring the tradeoff between energy dissipation, delay, and the number of backbones for broadcasting in wireless sensor networks through goal programming

Broadcasting, which is an essential mode of operation in wireless sensor networks (WSNs), dissipates a non-negligible portion of the energy budget of a sensor node. Broadcasting is achieved by the dissemination of broadcast packets (originated at the BS) by a set of relay nodes, which constitute a backbone so that all sensor nodes receive broadcast packets. Utilization of multiple backbones is necessary to achieve balanced energy dissipation of sensor nodes in broadcasting. In this study, we propose two mixed integer programming (MIP) models (i.e., the flow-based model and the node-based model), which minimize the energy dissipation of the highest energy-consuming node for broadcasting by utilizing multiple backbones. Balanced energy minimization and delay minimization objectives are integrated through a goal programming (GP) framework built upon the foundation provided by the scalable node-based model. Performance evaluations based on the optimal solutions of our models reveal that maximum energy dissipation and delay in WSN broadcasting can be significantly reduced, simultaneously, by utilizing multiple backbones (e.g., with two backbones maximum energy dissipation and delay can be, concurrently, reduced by more than 2% and 22%, respectively, in comparison to the single backbone case, likewise, it is also possible to simultaneously reduce maximum energy dissipation and delay more than 8% and 13%, respectively, depending on the priorities assigned to the objectives). Nevertheless, employing more than two backbones does not provide any significant performance improvements.

A novel carbon nanotubes doped natural rubber nanocomposite with balanced dynamic shear properties and energy dissipation for wave energy applications

Mechanical characterizations of natural rubber filled with carbon-based nanomaterials were extensively studied in tensile and tear modes whereas fewer attempts have been conducted on a dynamic shear condition using a double-bonded shear test piece. This is of importance since natural rubbers are widely used as flexible membranes for wave energy harvesting devices. Therefore, this study was aimed to explore the microstructural, rheological, and dynamic viscoelastic characteristics of natural rubbers filled with different Multi-Walled Carbon Nanotubes (MWCNTs) contents. A combined compounding approach was employed to ensure a homogenous CNT dispersion was achieved. Transmission electron microscopy (TEM) was performed for the materials characterization while the processability and curing parameters of the compounds were investigated using the Mooney viscosity and rheometry test. Dynamic shear properties were compared using a cyclic test performed on a double-bonded shear test piece. TEM images showed that an optimum CNTs dispersion was reached at 3 phr MWCNTs loading whereas increasing CNT content resulted in further inhomogeneity. The addition of CNTs into the natural rubber not only improved the curing properties of the compound, i.e., low scorch and curing times, but it also increased the Mooney viscosity, the rheological properties, and the dynamic shear properties of the nanocomposite compared to the pristine rubber. The Payne and Mullins effects were also observed for all compounds manifesting dependency on the CNTs content and applied strain amplitude. Finally, MWCNT enhanced the dissipated energy of the nanocomposites with respect to the neat rubber in which an increase of 1040 % in energy dissipation for 10 phr MWCNTs compared to the control at a strain amplitude of 200 % was achieved.

Magnetic energy dissipation during the current quench of disruption in EAST

A disruption database characterizing the current quench of disruptions with ITER-like tungsten divertor has been developed on EAST. It provides a large number of plasma parameters describing the predisruptive plasma, current quench time, eddy current, and mitigation by massive impurity injection, which shows that the current quench time strongly depends on magnetic energy and post-disruption electron temperature. Further, the energy balance and magnetic energy dissipation during the current quench phase has been well analysed. Magnetic energy is also demonstrated to be dissipated mainly by ohmic reheating and inductive coupling, and both of the two channels have great effects on current quench time. Also, massive gas injection is an efficient method to speed up the current quench and increase the fraction of impurity radiation.

Self-Assembled Bioinspired Nanocomposites.

Bioinspired materials engineering impacts the design of advanced functional materials across many domains of sciences from wetting behavior to optical and mechanical materials. In all cases, the advances in understanding how biology uses hierarchical design to create failure and defect-tolerant materials with emergent properties lays the groundwork for engaging into these topics. Biological mechanical materials are particularly inspiring for their unique combinations of stiffness, strength, and toughness together with lightweightness, as assembled and grown in water from a limited set of building blocks at room temperature. Wood, nacre, crustacean cuticles, and spider silk serve as some examples, where the correct arrangement of constituents and balanced molecular energy dissipation mechanisms allows overcoming the shortcomings of the individual components and leads to synergistic materials performance beyond additive behavior. They constitute a paradigm for future structural materials engineering-in the formation process, the use of sustainable building blocks and energy-efficient pathways, as well as in the property profiles-that will in the long term allow for new classes of high-performance and lightweight structural materials needed to promote energy efficiency in mobile technologies.This Account summarizes our efforts of the past decade with respect to designing self-assembling bioinspired materials aiming for both mechanical high-performance structures and new types of multifunctional property profiles. The Account is set out to first give a definition of bioinspired nanocomposite materials and self-assembly therein, followed by an in-depth discussion on the understanding of mechanical performance and rational design to increase the mechanical performance. We place a particular emphasis on materials formed at high fractions of reinforcements and with tailor-made functional polymers using self-assembly to create highly ordered structures and elucidate in detail how the soft polymer phase needs to be designed in terms of thermomechanical properties and sacrificial supramolecular bonds. We focus on nanoscale reinforcements such as nanoclay and nanocellulose that lead to high contents of internal interfaces and intercalated polymer layers that experience nanoconfinement. Both aspects add fundamental challenges for macromolecular design of soft phases using precision polymer synthesis. We build upon those design criteria and further develop the concepts of adaptive bioinspired nanocomposites, whose properties are switchable from the outside using molecularly defined triggers with light. In a last section, we discuss how new types of functional properties, in particular flexible and transparent gas barrier materials or fire barrier materials, can be reached on the basis of the bioinspired nanocomposite design strategies. Additionally, we show new types of self-assembled photonic materials that can even be evolved into self-assembling lasers, hence moving the concept of mechanical nanocomposite design to other functionalities.The comparative discussion of different bioinspired nanocomposite architectures with nematic, fibrillar, and cholesteric structures, as based on different reinforcing nanoparticles, aims for a unified understanding of the design principles and shall aid researchers in the field in the more elaborate design of future bioinspired nanocomposite materials based on molecular control principles. We conclude by addressing challenges, in particular also the need for a transfer from fundamental molecular materials science into scalable engineering materials of technological and societal relevance.

Energy dissipation and self‐centering capacities of posttensioning precast segmental ultra‐high performance concrete bridge columns

AbstractThe research aims to better balance energy dissipation (ED) and self‐centering capacities of posttensioning (PT) precast segmental ultra‐high performance concrete bridge columns by adjusting common design parameters. A numerical model is established based on the equivalent plastic hinge model and validated by the cyclic loading test. The validated model is used to conduct a parametric study to investigate the effects of seven common design parameters on ED and self‐centering capacities. The results show the proposed numerical model can accurately predict ED and self‐centering capacities of the proposed bridge columns. The effect of the strength‐yield ratio can be neglected when it is more than 1.2. The lower aspect ratio can first weaken and then improve the equivalent viscous damping ratio with drift ratio up, while the lower aspect ratio can reduce the residual drift ratio. With larger ED bar ratio, smaller unbonded length of ED bars and lower PT tendon ratio, the equivalent viscous damping ratio, and the residual drift ratio are significantly increased. It is not a perfect way to improve ED capacity by increasing the ED bar ratio, which can significantly magnify the residual drift ratio and limitedly enhance the equivalent viscous damping ratio, besides economical considering. Improving the gravity loading ratio and the initial PT stress are deemed to be effective ways to reduce the residual drift ratio because they not only have little influence on the equivalent viscous damping ratio but also result in no more costs.

K-CHRA: A Clustering Hierarchical Routing Algorithm for Wireless Rechargeable Sensor Networks

Routing technology is an indispensable part of wireless sensor networks (WSNs) in contemporary studies. Considerable attention is being given to the energy problem and the delay of data transmission. However, a few studies have explored routing algorithms in wireless rechargeable sensor networks (WRSNs) using mobile charging equipment. In this paper, we propose a clustering hierarchical routing algorithm for WRSNs based on $K$ -means method (K-CHRA), which takes the energy distribution and data transmission into consideration under the influence of mobile equipment (ME) while combining mobile sink and mobile charger in WRSNs. The mobile sink is responsible for data collection and mobile charger replenishes energy for sensor nodes. The simulations demonstrate that K-CHRA can reduce energy consumption and the data transmission delay. Thus, K-CHRA has excellent equilibrium characteristics with balanced energy dissipation throughout all sensor nodes in the networks. Finally, a large number of experiments demonstrate that our proposed algorithm K-CHRA suits for many kinds of scenarios of networks.

Lifetime Maximization via Hole Alleviation in IoT Enabling Heterogeneous Wireless Sensor Networks.

In Internet of Things (IoT) enabled Wireless Sensor Networks (WSNs), there are two major factors which degrade the performance of the network. One is the void hole which occurs in a particular region due to unavailability of forwarder nodes. The other is the presence of energy hole which occurs due to imbalanced data traffic load on intermediate nodes. Therefore, an optimum transmission strategy is required to maximize the network lifespan via hole alleviation. In this regard, we propose a heterogeneous network solution that is capable to balance energy dissipation among network nodes. In addition, the divide and conquer approach is exploited to evenly distribute number of transmissions over various network areas. An efficient forwarder node selection is performed to alleviate coverage and energy holes. Linear optimization is performed to validate the effectiveness of our proposed work in term of energy minimization. Furthermore, simulations are conducted to show that our claims are well grounded. Results show the superiority of our work as compared to the baseline scheme in terms of energy consumption and network lifetime.

Metal Ion Mediated Cellulose Nanofibrils Transient Network in Covalently Cross-linked Hydrogels: Mechanistic Insight into Morphology and Dynamics

Utilization of reversible interactions as sacrificial bonds in biopolymers is critical for the integral synthesis of mechanically superior biological materials. In this work, cellulose nanofibrils (CNFs) reinforced covalent polyacrylamide (PAAm) composite hydrogels are immersed into multivalent cation (Ca2+, Zn2+, Al3+, and Ce3+) aqueous solution to form ionic association among CNFs, leading to the ionic-covalent cross-linked hydrogels. The cations promote the formation of porous networks of nanofibrils by screening the repulsive negative charges on CNF surface and dominate the mechanical properties and self-recovery efficiency of the hydrogels, resulting in mechanically reinforced ionic hydrogels with stiff (Young's modulus 257 kPa) and tough properties (fracture toughness 386 kJ/m3). The in situ Raman spectroscopy during stretching corroborates the stress transfer medium of CNF, and the microscopic morphologies of stable crack propagation validates that the multiple toughening mechanisms occur in a balanced energy dissipation manner, enabling synergistic combination of stiffness and toughness. Moreover, the depth-sensing instrumentation by indentation test also demonstrates that the CNF ionic coordination contributes simultaneous improvement in hardness and elasticity by as much as 600% compared to those pristine gels. This work demonstrates a facile way to transfer nanoscale building blocks to bulk elastomers with tunable dynamic properties and may provide a new prospect for the rational design of CNF reinforced hydrogels for applications where high-bearing capability is needed.

Optimal path selection under different data

ABSTRACTA wireless sensor network (WSN) consists of energy-limited autonomous tiny devices spatially distributed so as to monitor their environments. They have a very wide application domain ranging from military applications to health care services, logistics, or agriculture. Efficient use of sensor energies and network security are of utmost importance, given their possible application domains and operational properties. Multipath routing and multi-copy forwarding are well-known approaches shown to be useful against several threats. In this paper we study the design of an energy-efficient and reliable WSN. We discuss four different routing strategies with multipath routing and various levels of multi-copying, namely, the no, full, and partial redundancy cases. Moreover, we incorporate balanced energy dissipation in our models not only to improve network lifetime, which is the time until the first sensor in the network exhausts its energy, but also to eliminate critical nodes, which are appealing for malicious attacks. We construct mathematical models of all these protocols and present some test results so as to display the trade-off between energy efficiency and network reliability. We compare their performance in terms of network lifetime and the amount of data successfully transmitted in case of an inconvenience. The full data redundancy protocol yields a more reliable design than the balanced utilization with no redundancy or the partial redundancy protocols in exchange for a quite significant degradation in network lifetime. However, the partial redundancy protocol provides a slightly less reliable WSN than the full redundancy case with almost 60% longer lifetime. As a result, we can suggest that our partial multi-copy protocol with extended balanced utilization rule is quite favourable for operating networks energy efficiently and securely.

Balanced Energy Dissipation at Propagating Crack Tip in Quasi-Brittle Materials? - Analysis via Soft-Computing Methods

Analysis on the aspects of the energy dissipation in the case of quasi-brittle fracture is presented. Dissipation both via cohesive forces at the crack faces and the one taking place within the volume of the fracture process zone is considered. Tools from the field of soft computing techniques are employed. The analysis is conducted on results from extensive experimental campaign.

A Kind of Energy-efficient Routing Algorithm for WSN Based on HQEA

This paper proposes a new hierarchical routing algorithm for wireless sensor networks called hybrid QEA-based energy-efficient routing algorithm (HERA), which is based on LEACH and PEGASIS algorithms in the environment of wireless sensor networks. In order to reduce the data transmission distance, this algorithm uses the hybrid quantum evolutionary algorithm (HQEA) to establish the best cluster-based multi-chain topology. For the sake of balancing energy dissipation, node’s residual energy and its distance from the target are considered as criterions of cluster head election, and each cluster head relays the sensed data of other clusters to the sink. Simulation results demonstrate comparing with LEACH and PEGASIS, this proposed algorithm HERA can shorten total transmission distance significantly, which is also more efficient to save and balance energy of consumption, meanwhile it prolongs the living time of whole network and eliminates the affection of sink’s location on the network lifetime.

Energy-Balanced Separating Algorithm for Cluster-Based Data Aggregation in Wireless Sensor Networks

Clustering provides an effective way to prolong the lifetime of wireless sensor networks. However, the head node may die much faster than other nodes due to its overburden. In this paper, we design a method to mitigate the uneven energy dissipation problem. Considering the relaying load undertaken by each cluster, we use the network topology and energy consumption to calculate a cluster radius for obtaining the intercluster energy balancing. A new cluster-leader election algorithm is proposed wherein the task of a single cluster head is separated to two nodes so that the critical nodes in each cluster will not exhaust their power so quickly. Furthermore, cross-level data transmission is used to prolong network lifetime. Extensive simulation experiments are carried out to evaluate the method with several performance criteria. Our simulation results show that this method obtains satisfactory performance on balancing energy dissipation and prolonging the networks lifetime.

Systematic energy-balanced cooperative transmission scheme in wireless sensor networks

Energy efficiency is a critical issue in wireless sensor networks (WSNs). In order to minimize energy consumption and balance energy dissipation throughout the whole network, a systematic energy-balanced cooperative transmission scheme in WSNs is proposed in this paper. This scheme studies energy efficiency in systematic view. For three main steps, namely nodes clustering, data aggregation and cooperative transmission, corresponding measures are put forward to save energy. These measures are well designed and tightly coupled to achieve optimal performance. A half-controlled dynamic clustering method is proposed to avoid concentrated distribution of cluster heads caused by selecting cluster heads randomly and to get high spatial correlation between cluster nodes. Based on clusters built, data aggregation, with the adoption of dynamic data compression, is performed by cluster heads to get better use of data correlation. Cooperative multiple input multiple output (CMIMO) with an energy-balanced cooperative cluster heads selection method is proposed to transmit data to sink node. System model of this scheme is also given in this paper. And simulation results show that, compared with other traditional schemes, the proposed scheme can efficiently distribute the energy dissipation evenly throughout the network and achieve higher energy efficiency, which leads to longer network lifetime span. By adopting orthogonal space time block code (STBC), the optimal number of the cooperative transmission nodes varying with the percentage of cluster heads is also concluded, which can help to improve energy efficiency by choosing the optimal number of cooperative nodes and making the most use of CMIMO.

Energy Efficient and Balanced Cluster-Based Data Aggregation Algorithm for Wireless Sensor Networks

Data aggregation is an effectual approach for wireless sensor networks (WSNs) to save energy and prolong network lifetime. Cluster-based data aggregation algorithms are most popular because they have the advantages of high flexibility and reliability. But the problem of unbalanced energy dissipation is the inherent disadvantage in clusterbased WSNs. This paper addresses this problem in cluster-based and homogeneous WSNs in which cluster heads transmit data to base station by one-hop communication, and proposes an energy efficient and balanced cluster-based data aggregation algorithm (EEBCDA). It divides the network into rectangular grids with unequal size and makes cluster heads rotate among the nodes in each grid respectively, the grid whose cluster head consumes more energy has more sensor nodes to take part in cluster head rotation and share energy load, by this way, it is able to balance energy dissipation. Besides, it adopts some measures to save energy. The results of simulation show that EEBCDA can remarkably enhance energy efficiency, balance energy dissipation and prolong network lifetime.

An Energy-Efficient Data Gathering Method for Sensor Networks with Mixed Communication Modes

One critical issue in wireless sensor networks is how to gather sensed information in an energy-efficient way since the energy is a scarce resource in a sensor node. Cluster-based architecture is an effective architecture for data-gathering in wireless sensor networks. In this paper, by taking the nodes energy consumption into account, we first derive the optimal number of clusters for data gathering in sensor networks. To balance the cluster heads energy consumption, we propose a mixed communication modes where the cluster heads can transmit data to the base station in either single-hop or multi-hop. We then develop a data gathering method based on the optimal number of clusters and mixed communication modes. The simulation results show that the proposed method outperforms LEACH and HEED in terms of network lifetime by balancing energy dissipation.

Cuckoo Search for data gathering in Wireless Sensor Networks

In this paper a meta-heuristic optimisation technique, Cuckoo Search (CS) is used to aggregate data in the Sensor Network. In the proposed technique, the least energy nodes are formed as subordinate chains (or) clusters for sensing the data and high energy nodes as Cluster Head for communicating to the Base Station (BS). The modified CS is proposed to get enhanced network performance incorporating balanced energy dissipation and results in the formation of optimum number of clusters and minimal energy consumption. The feasibility of the scheme is manifested by the simulation results on comparison with the traditional cluster based routing methods.

Energy Balanced Strategies for Maximizing the Lifetime of Sparsely Deployed Underwater Acoustic Sensor Networks

Underwater acoustic sensor networks (UWA-SNs) are envisioned to perform monitoring tasks over the large portion of the world covered by oceans. Due to economics and the large area of the ocean, UWA-SNs are mainly sparsely deployed networks nowadays. The limited battery resources is a big challenge for the deployment of such long-term sensor networks. Unbalanced battery energy consumption will lead to early energy depletion of nodes, which partitions the whole networks and impairs the integrity of the monitoring datasets or even results in the collapse of the entire networks. On the contrary, balanced energy dissipation of nodes can prolong the lifetime of such networks. In this paper, we focus on the energy balance dissipation problem of two types of sparsely deployed UWA-SNs: underwater moored monitoring systems and sparsely deployed two-dimensional UWA-SNs. We first analyze the reasons of unbalanced energy consumption in such networks, then we propose two energy balanced strategies to maximize the lifetime of networks both in shallow and deep water. Finally, we evaluate our methods by simulations and the results show that the two strategies can achieve balanced energy consumption per node while at the same time prolong the networks lifetime.

Net Energy Dissipation Rates in the Tropical Ocean and ENSO Dynamics

Abstract How unstable is the tropical ocean–atmosphere system? Are two successive El Niño events independent, or are they part of a continual (perhaps weakly damped) cycle sustained by random atmospheric disturbances? How important is energy dissipation for ENSO dynamics? These closely related questions are frequently raised in connection with several climate problems ranging from El Niño predictability to the impact of atmospheric “noise” on ENSO. One of the factors influencing the system’s stability and other relevant properties is the damping (decay) time scale for the thermocline anomalies associated with the large-scale oceanic motion. Here this time scale is estimated by considering energy balance and net energy dissipation in the tropical ocean and it is shown that there are two distinct dissipative regimes: in the interannual frequency band the damping rate is approximately (2.3 yr)−1; however, in a near-annual frequency range the damping appears to be much stronger, roughly (8 months)−1.

Kink with Allowance for the Energy Dissipation and Pumping

In the present work, the (1+1)-dimensional nonlinear equation of motion of ϕ4 scalar theory is examined with simultaneous allowance for the processes of energy dissipation and pumping in the system. The energy dissipation is described in the equation by a linear term, and the energy pumping is described by a squared time derivative of the field. A single-kink solution is constructed for the given problem. It is demonstrated that a scalar field expansion in the inflationary model can occur with balanced energy dissipation and pumping.