Minimum Energy Dissipation Research Articles

A new HVAC ductwork steady-state flow analysis method: The Minimum Energy Dissipation Principle applied to flow networks including the effects of branched junctions

The fact that the popular head loss coefficient concept, may become negative in branched junctions, is a symptom that something is not correctly managed. The paper makes a review of recent works which have sought new models based on physical concepts, as a way to avoid speaking about “negative losses”. Herwing and Schmandt [1], showed that the origin of the negative sign was a diffusive shear work exchange between the two streams of a branched junction. Traditionally, the head losses at the branched junctions are neglected, but definitely it cannot be done in HVAC air-duct networks.Firstly, the paper illustrates how, by ignoring this “negative loss” contradiction, traditional duct network analysis may encounter unexpected numerical difficulties. Secondly, it shows that the Minimum Energy Dissipation Principle (MinEDP) can be successfully applied to analyze the steady-state of any flow network (not necessarily HVAC ductworks), with or without shear work at junctions. Moreover, the new method does not need to know the latter, beforehand, although the nature of the solution is very different in either case.Finally, the paper includes a practical example of an HVAC ductwork to illustrate the outcomes. The new method works smoothly and quickly and does not need any ad hoc modification to cope with an eventual “negative” head loss.

Energy dissipation capacity of precast concrete beam-column joint connected by double notch subjected to cyclic lateral loading

This paper presents the experimental investigation of full-scale precast concrete beam-column connections subjected to cyclic lateral loading. The specimen consists of three models. Two of which are precast beam-column connections and one is monolith. The precast and monolith specimen were designed for the same strength. The cross-sectional dimensions of the beam 250 mm x 300 mm and column 300 mm x 300 mm. Connections are placed in plastic hinge area, with a distance of h (beam height) from the face of the column which is expected to occur first destruction. Precast construction joints are distinguished, with 3 different models, namely monolith, double notch type 1 (STR-1), and double notch type 2 (STR-2). Maximum load capacity, hysterical behavior and energy dissipation are measured, and capacity is compared. The results showed that beam-column joint STR-2 are better able to absorb energy than beam column joint monolith and beam-column joint STR-1. Kumulative energy dissipation of monolith about 9333.07 kN-mm, STR-1 is 8336.76 kN-mm, and STR-2 is 10162.52 kN-mm. The use of dual notch connections (STR-1 and STR-2) provides satisfactory performance, which is marked by meeting the minimum relative energy dissipation ratio at a 3.5% drift according to the ACI Committee 374.1-05. The results show that the STR-2 beam-column connection is more capable of absorbing energy than the monolith beam-column connection and STR-1 beam connection. the value of monolithic cumulative energy dissipation is around 9333.07 kN-mm, STR-1 is 8336.76 kN-mm, and STR-2 is 10162.52 kN-mm. in principle, all three test specimens, monoliths, STR-1 and STR-2 provide satisfactory stability performance under lateral cyclic loads, because they still meet the minimum relative energy dissipation ratio at a deviation of 3.5% according to the ACI Committee 374.1 -05

Performance evaluation of hierarchical clustering protocols with fuzzy C-means

The longevity of the network and the lack of resources are the main problems within the WSN. Minimizing energy dissipation and optimizing the lifespan of the WSN network are real challenges in the design of WSN routing protocols. Load balanced clustering increases the reliability of the system and enhances coordination between different nodes within the network. WSN is one of the main technologies dedicated to the detection, sensing, and monitoring of physical phenomena of the environment. For illustration, detection, and measurement of vibration, pressure, temperature, and sound. The WSN can be integrated into many domains, like street parking systems, smart roads, and industrial. This paper examines the efficiency of our two proposed clustering algorithms: Fuzzy C-means based hierarchical routing approach for homogeneous WSN (F-LEACH) and fuzzy distributed energy efficient clustering algorithm (F-DEEC) through a detailed comparison of WSN performance parameters such as the instability and stability duration, lifetime of the network, number of cluster heads per round and the number of alive nodes. The fuzzy C-means based on hierarchical routing approach is based on fuzzy C-means and low-energy adaptive clustering hierarchy (LEACH) protocol. The fuzzy distributed energy efficient clustering algorithm is based on fuzzy C-means and design of a distributed energy efficient clustering (DEEC) protocol. The technical capability of each protocol is measured according to the studied parameters.

Quantum Foundations of Classical Reversible Computing.

The reversible computation paradigm aims to provide a new foundation for general classical digital computing that is capable of circumventing the thermodynamic limits to the energy efficiency of the conventional, non-reversible digital paradigm. However, to date, the essential rationale for, and analysis of, classical reversible computing (RC) has not yet been expressed in terms that leverage the modern formal methods of non-equilibrium quantum thermodynamics (NEQT). In this paper, we begin developing an NEQT-based foundation for the physics of reversible computing. We use the framework of Gorini-Kossakowski-Sudarshan-Lindblad dynamics (a.k.a. Lindbladians) with multiple asymptotic states, incorporating recent results from resource theory, full counting statistics and stochastic thermodynamics. Important conclusions include that, as expected: (1) Landauer’s Principle indeed sets a strict lower bound on entropy generation in traditional non-reversible architectures for deterministic computing machines when we account for the loss of correlations; and (2) implementations of the alternative reversible computation paradigm can potentially avoid such losses, and thereby circumvent the Landauer limit, potentially allowing the efficiency of future digital computing technologies to continue improving indefinitely. We also outline a research plan for identifying the fundamental minimum energy dissipation of reversible computing machines as a function of speed.

Investigation of PVT-Aware STT-MRAM Sensing Circuits for Low-VDD Scenario.

Spintronic based embedded magnetic random access memory (eMRAM) is becoming a foundry validated solution for the next-generation nonvolatile memory applications. The hybrid complementary metal-oxide-semiconductor (CMOS)/magnetic tunnel junction (MTJ) integration has been selected as a proper candidate for energy harvesting, area-constraint and energy-efficiency Internet of Things (IoT) systems-on-chips. Multi-VDD (low supply voltage) techniques were adopted to minimize energy dissipation in MRAM, at the cost of reduced writing/sensing speed and margin. Meanwhile, yield can be severely affected due to variations in process parameters. In this work, we conduct a thorough analysis of MRAM sensing margin and yield. We propose a current-mode sensing amplifier (CSA) named 1D high-sensing 1D margin, high 1D speed and 1D stability (HMSS-SA) with reconfigured reference path and pre-charge transistor. Process-voltage-temperature (PVT) aware analysis is performed based on an MTJ compact model and an industrial 28 nm CMOS technology, explicitly considering low-voltage (0.7 V), low tunneling magnetoresistance (TMR) (50%) and high temperature (85 °C) scenario as the worst sensing case. A case study takes a brief look at sensing circuits, which is applied to in-memory bit-wise computing. Simulation results indicate that the proposed high-sensing margin, high speed and stability sensing-sensing amplifier (HMSS-SA) achieves remarkable performance up to 2.5 GHz sensing frequency. At 0.65 V supply voltage, it can achieve 1 GHz operation frequency with only 0.3% failure rate.

Surface gravity wave scattering by multiple slatted screens placed near a caisson porous breakwater in the presence of seabed undulations

In the present study, the effectiveness of using multiple slatted screens placed in front of a caisson porous breakwater to dissipate the incident wave energy is analyzed. To model the water flow through the slatted screens, a quadratic (nonlinear) pressure drop condition which involves both the inertial and drag effects is considered. Further, for thick porous structure, the well known Sollitt and Cross (1972) model is used. To handle the nonlinear boundary conditions, an iterative multi-domain boundary element method (BEM) is used. The numerical convergence of the multi-domain BEM based solutions is presented. Energy identities for flow past a single slatted screen, multiple slatted screens and for the present problem are derived. The study shows that the minimum reflection coefficient (<1%) and maximum wave energy dissipation (>98%) can be obtained by using four slatted screens. Further, for moderate values of perforation-effect Keulegan-Carpenter number (KC), the reflection coefficient attains maximum for b1λ≈n2,n=1,2,3,⋯ (b1 is the distance between the rigid caisson and the front slatted screen, λ is the incident wavelength) irrespective of the variations in the number of slatted screens. Further, the transmission coefficient, horizontal and vertical wave forces acting on the rigid caisson attain maximum for b1/λ≈0.55n, and minimum occurs for 2n+14<b1λ<3n+26,n=0,1,2,3,⋯. The Bragg resonance in the reflection coefficient occurs at Bragg value ≈1.6 irrespective of the variations of KC number. Moreover, the reflection coefficient increases around the Bragg value for higher values of KC number without altering the peak value in the reflection coefficient.

Energy Aware Resource Utilization Technique for Workflow Scheduling in Cloud Computing Environment

Heterogeneous multicore computational environment are increasingly being used for executing scientific workload. Heterogeneous computational framework aid is reducing energy dissipation for executing real-time data intensive workload by employing Dynamic Power Management (DPM) and Dynamic Voltage and Frequency Scaling (DVFS). However, reducing energy and improving performance is becoming major constraint in modelling workload scheduling model in heterogeneous computational environment. Recently, number of multi-objective based workload scheduling aimed at minimizing power budget and meeting task deadline constraint. However, these model induce significant overhead when demand and number of processing core increases. For addressing research problem this work assume that different task will have different execution path, I/O access, memory, active processing, and cache requirement. Thus, this paper present Energy Aware Resource Utilization (EARU) model by minimizing energy dissipation and utilizing cache resource more efficiently. The EARU model achieves much lesser execution time, energy consumption, and power consumption when compared with existing multi-objective based and DVFS-based workload scheduling algorithm.

Web Service Composition for Executing Workflows: Open Issues, Challenges, Survey and Future Directions

Cloud computing has nowadays become a dominant technology to reduce the computation cost by elastically providing resources to users on a pay-per-use basis. More and more data intensive business and scientific web service applications represented by workflows have been moved or are in active transition to cloud platforms. Therefore, efficient web service compositing for executing workflow are in high demand. This paper conduct extensive survey of various existing web service composition technique for executing workflow. From survey it is identified very limited work is done for minimizing workflow execution processing time with minimal energy dissipation considering task deadline requirement under heterogeneous cloud computational environment. This paper identifies open issues and future challenges and presented possible solution in building efficient web service composition for executing workflows under heterogeneous cloud computational environment

Which Is the Motion State of a Droplet on an Inclined Hydrophilic Rough Surface in Gravity: Pinned or Sliding?

The motion state of a droplet on an inclined, hydrophilic rough surface in gravity, pinned or sliding, is governed by the balance between the driving and the pinned forces. It can be judged by the droplet’s shape on the inclined hydrophilic rough surface and the droplet’s contact angle hysteresis. In this paper, we used the minimum energy theory, the minimum energy dissipation theory, and the nonlinear numerical optimization algorithm to establish Models 1–3 to calculate out the advancing/receding contact angles (θa/θr), the initial front/rear contact angles (θ1−0/θ2−0) and the dynamic front/rear contact angles (θ1−*/θ2−*) for a droplet on a rough surface. Also, we predicted the motion state of the droplet on an inclined hydrophilic rough surface in gravity by comparing θ1−0(θ2−0) and θ1−*(θ2−*) with θa(θr). Experiments were done to verify the predictions. They showed that the predictions were in good agreement with the experimental results. These models are promising as novel design approaches of hydrophilic functional rough surfaces, which are frequently applied to manipulate droplets in microfluidic chips.

Mathematical analysis of laboratory microbial experiments demonstrating deterministic chaotic dynamics

Presented is a system of four ordinary differential equations and a mathematical analysis of microbiological experiments in a four-component chemostat—nutrient n, rods r, cocci c, and predators p. The analysis is consistent with the conclusion that previous experiments produced features of deterministic chaotic and classical dynamics depending on dilution rate. The surrogate model incorporates as much experimental detail as possible, but necessarily contains unmeasured parameters. The objective is to understand better the differences between model simulations and experimental results in complex microbial populations. The key methodology for simulation of chaotic dynamics, consistent with the measured dilution rate and microbial volume averages, was to cause the preference of p for r vs. c to vary with the r and c concentrations, to make r more competitive for nutrient than c, and to recycle some dying p biomass, leading to a modified version of the Monod kinetics model. Our mathematical model demonstrated that the occurrence of chaotic dynamics requires a predator, p, preference for r versus c to increase significantly with increases in r and c populations. Also included is a discussion of several generalizations of the existing model and a possible involvement of the minimum energy dissipation principle. This principle appears fundamental to thermodynamic systems including living systems. Several new experiments are suggested.

A hybridization strategy using equal and unequal clustering schemes to mitigate idle listening for lifetime maximization of wireless sensor network

The main focus in the designing of wireless sensor networks (WSNs) applications and protocols is minimizing energy dissipation while at the same time maximizing the network lifetime. In this paper, we investigate the idle listening and hotspot problems with respect to the clustering routing technique in WSNs. Some of the studies in clustering centered around equal clustering scheme while others were based on unequal clustering scheme. Equal clustering scheme avoids inter-cluster idle listening as the intra-cluster data collection can be completed at the same time across all clusters in the network but lead to hotspot problem due to additional traffic relay experienced by cluster heads near the base station. Similarly, unequal clustering addresses hotspot problem but lead to inter-cluster idle listening due to the use of global network-wide intra-cluster collection among clusters of unequal sizes and densities. In this paper we proposed a zone-based clustering scheme referred to as hybrid equal and unequal clustering (HEUC) that jointly address inter-cluster idle listening and hotspot problems to maximize the lifetime of WSNs. To achieve this, the network area is firstly partitioned into zones. The size of clusters in the same zone is designed to be equal and cluster size increases across zones as the distance from the BS increases. Secondly, the density of nodes deployed in each cluster per zone is obtained in such a way that the distribution of nodes in zones away from BS increases according to the radius increase in clusters across the zones. Thirdly, a deterministic deployment strategy is used to deploy nodes into various clusters. Fourthly, we implement a zone-wise intra-cluster data collection strategy that allows intra-cluster data collection to be completed at once to address inter-cluster idle listening. Lastly, a multihop routing is used for data forwarding to BS. The result shows that our proposed HEUC has 38% and 51% lifetime improvement against EBULRP and AECR respectively.

Energy Efficient Clustering and Routing Algorithm for WSN

: This paper presents a novel Energy Efficient Clustering and Routing Algorithm (EECRA) for WSN. It is a clustering-based algorithm that minimizes energy dissipation in wireless sensor networks. The proposed algorithm takes into consideration energy conservation of the nodes through its inherent architecture and load balancing technique. In the proposed algorithm the role of intercluster transmission is not performed by gateways instead a chosen member node of respective cluster is responsible for data forwarding to another cluster or directly to the sink. Our algorithm eases out the load of the gateways by distributing the transmission load among chosen sensor node which acts as a relay node for inter-cluster communication for that round. Grievous simulations show that EECRA is better than PBCA and other algorithms in terms of energy consumption per round and network lifetime. Objective: The objective of this research lies in its inherent architecture and load balancing technique. The sole purpose of this clustering-based algorithm is that it minimizes energy dissipation in wireless sensor networks. Methods: This algorithm is tested with 100 sensor nodes and 10 gateways deployed in the target area of 300m × 300m. The round assumed in this simulation is same as in LEACH. The performance metrics used for comparisons are (a) network lifetime of gateways and (b) energy consumption per round by gateways. Our algorithm gives superior result compared to LBC, EELBCA and PBCA. Results: The simulation was performed on MATLAB version R2012b. The performance of EECRA is compared with some existing algorithms like PBCA, EELBCA and LBCA. The comparative analysis shows that the proposed algorithm outperforms the other existing algorithms in terms of network lifetime and energy consumption. Conclusion: The novelty of this algorithm lies in the fact that the gateways are not responsible for inter-cluster forwarding, instead some sensor nodes are chosen in every cluster based on some cost function and they act as a relay node for data forwarding. Note the algorithm does not address the hot-spot problem. Our next endeavor will be to design an algorithm with consideration of hot-spot problem.

Refining Landauer\u2019s Stack: Balancing Error and Dissipation When Erasing Information

Nonequilibrium information thermodynamics determines the minimum energy dissipation to reliably erase memory under time-symmetric control protocols. We demonstrate that its bounds are tight and so show that the costs overwhelm those implied by Landauer’s energy bound on information erasure. Moreover, in the limit of perfect computation, the costs diverge. The conclusion is that time-asymmetric protocols should be developed for efficient, accurate thermodynamic computing. And, that Landauer’s Stack—the full suite of theoretically-predicted thermodynamic costs—is ready for experimental test and calibration.

An Analytical Evaluation of Performance Limit for PiN diodes and IGBTs

This paper reports analytical evaluation for minimum reverse recovery loss and turn‐off loss of PiN diodes and IGBTs, respectively. In this evaluation, we take account of structural parameters and current continuity at the both ends of the i‐layer, and we calculate switching losses (E) from energy dissipation on the i‐layer during switching action by using position integration instead of time integration. In the case of IGBT, we assume that depletion layer spreads from the i‐layer and n+ layer interface of the PiN diode that corresponds to bottom p type layer ‐ n− layer ‐ p type backgate region of IGBT cells. We evaluate optimum structure for minimum energy dissipation of these switching actions and conduction states by newly employed index RE consists of R calculated by voltage drop at the i‐layer and both ends of the i‐layer and E. We clarify that ideal carrier profile for minimum RE, and we also evaluate structural parameters for that condition. © 2021 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC.

Correlation between Buoyancy Flux, Dissipation and Potential Vorticity in Rotating Stratified Turbulence

We study in this paper the correlation between the buoyancy flux, the efficiency of energy dissipation and the linear and nonlinear components of potential vorticity, PV, a point-wise invariant of the Boussinesq equations, contrasting the three identified regimes of rotating stratified turbulence, namely wave-dominated, wave–eddy interactions and eddy-dominated. After recalling some of the main novel features of these flows compared to homogeneous isotropic turbulence, we specifically analyze three direct numerical simulations in the absence of forcing and performed on grids of 10243 points, one in each of these physical regimes. We focus in particular on the link between the point-wise buoyancy flux and the amount of kinetic energy dissipation and of linear and nonlinear PV. For flows dominated by waves, we find that the highest joint probability is for minimal kinetic energy dissipation (compared to the buoyancy flux), low dissipation efficiency and low nonlinear PV, whereas for flows dominated by nonlinear eddies, the highest correlation between dissipation and buoyancy flux occurs for weak flux and high localized nonlinear PV. We also show that the nonlinear potential vorticity is strongly correlated with high dissipation efficiency in the turbulent regime, corresponding to intermittent events, as observed in the atmosphere and oceans.

INERTIA PARTICLE SWARM OPTIMIZATION WITH DYNAMIC VELOCITY BASED CLUSTERING TECHNIQUE IN WIRELESS SENSOR NETWORKS

Wireless Sensor Networks (WSN) comprises a collection of nodes commonly employed to observe the physical environment. Different sensor nodes are linked to an inbuilt power unit to carry out necessary operations and data transmission between nearby nodes. The maximization of network lifetime and minimization of energy dissipation are considered as the major design issue of WSN. Clustering is a familiar energy efficient technique and the choice of optimal cluster heads (CHs) is considered as an NP hard problem. This paper presents an Inertia Particle Swarm Optimization algorithm with dynamic velocities (IPSO-DV) algorithm based clustering technique in WSN. The aim of the IPSO-DV technique is to select the CHs in such a way to maximize network lifetime. The IPSO-DV algorithm derives a fitness function (FF) to select CHs using distance to BS and remaining energy level. The application of dynamic velocities helps to improvise the effectiveness of the conventional PSO algorithm. To assure the performance of the presented IPSO-DV algorithm, a series of experiments were carried out and the results are investigated under several aspects. The experimentation outcome ensured the effective performance of the IPSO-DV algorithm over the compared clustering techniques.

Influence of Ni2+ doping in the structural, magnetic and optical properties of MnFe2O4 spinel ferrite synthesized by sol–gel facilitated microwave method

Transition of superparamagnetic behaviour to ferromagnetic behaviour is earned by incorporating a divalent transition metal ion Ni2+into the lattice of nanocrystalline MnFe2O4 and consequently evolves as a soft magnet. The present work exploits sol–gel facilitated microwave combustion method to synthesize the nickel doped manganese ferrite nanocrystals Mn1-xNixFe2O4(0.0 ≤ x ≥ 0.5). The resulting nanocrystals were characterised by X-ray diffraction (XRD), Scanning electron microscope with energy dispersive X-ray analysis (SEM-EDAX), UV–Visible Diffuse reflectance spectroscopy (UV-DRS) and Vibrating sample magnetometer (VSM) studies. Within the tested calcination temperature (700 °C/4hr) it was feasible to procure nanocrystalline magnetic ferrites with a single crystalline phase confirmed by XRD analysis leading to a cubic spinel structure with a prominent superparamagnetic regime. The VSM studies evidences a diminishing saturation magnetization (Ms) from 66.89 to 49.42 emu/g, a decrease in magnetic moment (µB) and an increase in coercivity (Hc) from 51.45 kOe to 66.36 kOe with the higher doping of Ni2+ions in the lattice. The crystalline size of the synthesized ferrites varied between 30 and 40 nm illustrated by XRD analysis and an average particle size of 70 nm evidenced by SEM results. An increase in band gap with an increase in Ni2+could be observed from the UV-DRS results. The analysed characteristics of these ferrites could be exploited in places of minimum energy dissipation such as transformer and motor cores.

Quasi Oppositional Glowworm Swarm Optimization Algorithm for Energy Efficient Clustering in Wireless Sensor Networks

Wireless sensor network (WSN) becomes popular due to its applicability in distinct application areas like healthcare, military, search and rescue operations, etc. In WSN, the sensor nodes undergo deployment in massive number which operates autonomously in harsh environment. Because of limited resources and battery operated sensor nodes, energy efficiency is considered as a main design issue. To achieve, clustering is one of the effective technique which organizes the set of nodes into clusters and cluster head (CH) selection takes place. This paper presents a new Quasi Oppositional Glowworm Swarm Optimization (QOGSO) algorithm for energy efficient clustering in WSN. The proposed QOGSO algorithm is intended to elect the CHs among the sensor nodes using a set of parameters namely residual energy, communication cost, link quality, node degree and node marginality. The QOGSO algorithm incorporates quasi oppositional based learning (QOBL) concept to improvise the convergence rate of GSO technique. The QOGSO algorithm effectively selects the CHs and organizes clusters for minimized energy dissipation and maximum network lifetime. The performance of the QOGSO algorithm has been evaluated and the results are assessed interms of distinct evaluation parameters.

Topology optimization of turbulent rotating flows using Spalart–Allmaras model

The design of rotating fluid devices, such as flow machines, mixers, and separators, with a focus on performance improvement is of high interest. They usually operate under high Reynolds numbers featuring turbulent flows. In this research, the topology optimization model of turbulent flows is expanded by adapting the Spalart–Allmaras (SA) model with the Rotation/Curvature Correction to consider a density-based material model. This correction improves the turbulence evaluation when rotating frames are considered. The SA model considers the distance to the nearest wall to calculate the turbulent viscosity. However, in the TO, it uses the distance to the nearest solid element, which is calculated by using a novel Eikonal equation with a penalization model. The algorithm is implemented by using a finite element model to solve the state equations. The pyadjoint libraries are used to perform the automatic sensitivity derivation. The objective function considered minimizes energy dissipation. The algorithm is evaluated by performing the optimization of rotating flows with high Reynolds numbers. Several optimized topologies for different domains and angular velocities are shown.

Multioperative reversible gate design with implementation of 1‐bit full adder and subtractor along with energy dissipation analysis

SummaryNanotechnology and very large‐scale integration (VLSI) fabrication have a reflective productivity. The growth of one demands the growth of the other. In nanotechnology, quantum‐dot cellular automata (QCA) secures as the best alternative for replacement of complementary metal‐oxide semiconductor (CMOS) technology for integrated circuit (IC) fabrication. This paper presents an integration of the two domains wherein a novel ultraefficient, multioperative 3 × 3 universal reversible gate, Sadat Farah Vijay (SFV)‐QCA, is proposed and implemented in QCA technology using majority voter approach. SFV‐QCA gate is redesigned and restructured using precise QCA cell interaction for optimization. The basic logic gates are implemented using the proposed SFV‐QCA gate to validate its universality. All the 13 standard Boolean functions are implemented using SFV‐QCA to demonstrate its multioperation nature. One‐bit full adder and subtractor circuits are designed using SFV‐QCA gate and compared with the previous works. The analysis of the SFV‐QCA gate shows that it is ultraefficient and more robust as compared to previous works. Energy dissipation analysis of the designs has also been presented, and the investigation establishes minimum energy dissipation of the designs that confirms ultrahigh efficient designs.