Large-scale Hybrid Research Articles

Effect of internal recycling ratios on biomass parameters and simultaneous reduction of nitrogen and organic matter in a hybrid treatment system

A new large-scale pilot hybrid treatment system of 53m3/day was developed by combining 3 treatment methods: switched internal recycling flows to equalization tank (EQ); rotating hanging media bioreactor (RHMBR); and submerged flat sheet membrane bioreactor (SMBR). The system was operated for more than 16 months in a real-world municipal wastewater treatment plant, using different internal recycling ratios and observing/monitoring the results. This paper addresses not only the urgent problems of treating nutrient and organic pollutants in municipal wastewater, but also assesses characteristics of biomass production, sludge yield, and observed yield during the pilot operation. It also details design parameters used to achieve these assessed levels. Furthermore, the effects and correlations of the loading rates, activated sludge and biomass parameters, on different runs were also studied. The purpose of this was to identify the most suitable indicator for assessing the hybrid system's performance. Results strongly indicated that increasing the internal circulation rate greatly influenced the declining yield trend. The lowest biomass production (Px,bio) and sludge yields (PX,VSS or PX,TSS) were shown for conditions in run 3, and run 4, respectively. Overall the developed treatment system performed extremely well in biological terms for actual municipal wastewater treatment and resulted in high pollutant removal efficiencies, reduced sludge production at a reasonable cost. The hybrid system is a potential option for wastewater treatment, reuse and economy.

Behavior of Large-Scale Hybrid FRP–Concrete–Steel Double-Skin Tubular Beams with Shear Connectors

AbstractHybrid fiber-reinforced polymer (FRP)–concrete–steel double-skin tubular members (DSTMs) are a new form of hybrid members that consist of an outer tube made of FRP and an inner tube made of steel, with the space between them filled with concrete. The existing studies on hybrid DSTMs have been mainly focused on their use as compression members, with only a very limited number of studies on their use as flexural members [i.e., hybrid double-skin tubular beams (DSTBs)]. This paper presents the first ever experimental study on large-scale hybrid DSTBs with headed shear studs; the effect of an integrated deck is also examined. The main parameter examined in the experimental program was the section configuration. The test results show that both the DSTBs and the DSTB-deck unit possessed a very ductile response, and that the headed shear studs effectively reduced or eliminated slips between the steel tube and the concrete. This paper also presents a theoretical model based on conventional section analysi...

An Algorithm for Network Fluctuation Hopping Signal Suppression Based on Disturbance Characteristics Decomposition and Feed-Forward Modulation

In the data communication, a time-frequency hopping resonance signal will be created, and this network fluctuation hopping signal must be suppressed in order to improve the network stability. An algorithm for network fluctuation hopping signal suppression based on disturbance characteristics decomposition and feed-forward modulation is proposed, and the disturbance characteristics decomposition for a network fluctuation hopping signal is done in a Hilbert space. A feed-forward modulation filter is created to get the feed-forward modulation suppression of the network fluctuation hopping signal. The simulation results indicate that this algorithm has good real-time data transmission, which can effectively suppress the resonance signal in the network fluctuation hopping, low loss of information, and has the obvious function to resolve the startup hysteresis, server load, tremble and other problems in the large-scale hybrid networking.

Superconducting Computing in Large-Scale Hybrid Systems

Once focused solely on computation speed, superconducting computing is now proving useful in hybrid systems where its unique capabilities complement conventional computing technologies. Energy efficiency has become a strong motivation for developing large-scale superconducting systems.

HierHybNET: Capacity scaling of ad hoc networks with cost-effective infrastructure

In this paper, we introduce a large-scale hierarchical hybrid network (HierHybNET) consisting of both n wireless ad hocnodes and m base stations (BSs) equipped with l multiple antennas per BS, where the communication takes place from wireless nodes to a remote central processor (RCP) through BSs in a hierarchical way. To understand a relationship between capacity and cost, we deal with a general scenario where m, l, and the backhaul link rate can scale at arbitrary rates relative to n (i.e., we introduce three scaling parameters). In order to provide a cost-effective solution for the deployment of backhaul links connecting BSs and the RCP, we first derive the minimum backhaul link rate required to achieve the same capacity scaling law as in the infinite-capacity backhaul link case. Assuming an arbitrary rate scaling of each backhaul link, a generalized achievable throughput scaling law is then analyzed. Moreover, three-dimensional information-theoretic operating regimes are explicitly identified according to the three scaling parameters. We also characterize an infrastructure-limited regime where the throughput is limited by the backhaul link rate.

Transient Stability Augmentation of PV/DFIG/SG-Based Hybrid Power System by Nonlinear Control-Based Variable Resistive FCL

This paper proposes three nonlinear controllers such as fuzzy logic controller (FLC), static nonlinear controller (SNC), and adaptive-network-based fuzzy inference system (ANFIS)-based variable resistive-type fault current limiter (VR-FCL) to augment the transient stability of a large-scale hybrid power system consisting of a doubly fed induction generator (DFIG)-based wind farm, a photovoltaic (PV) plant, and a synchronous generator (SG). Appropriate resistance generation of the VR-FCL during a grid fault to provide better transient stability is the main contribution of the work. The effectiveness of the proposed control methods in improving the transient stability of the hybrid power network is verified by applying both balanced and unbalanced faults in one of the double circuit transmission lines connected to the system. Simulation results show that the proposed FLC-, SNC-, or ANFIS-based VR-FCL are effective in improving the transient stability of the studied hybrid system. Moreover, all the proposed methods exhibit almost similar performance. Therefore, any of the methods can be chosen for the transient stability enhancement of the hybrid power system.

Ab initio simulations on migration paths of interstitial oxygen in corundum

Ionizing radiation produces in Al2O3 (corundum) crystals primary Frenkel pairs of complementary defects (in oxygen sublattice these are oxygen vacancies and interstitial oxygen ions, VO−Oi). The interstitial Oi atoms begin to migrate above certain temperature and create the dumbbell pairs with regular oxygen atoms (Oreg−Oi). We have calculated the optimal dumbbell configurations and optimized further migration paths (i.e., Oi interstitial can break the bond with one Oreg atom and moves towards another, one of four next-neighbor Oreg atoms). To simulate all possible Oi migration trajectories, we have performed large-scale hybrid DFT-LCAO PBE0 calculations on 2×2×1 supercells of defective α-Al2O3 crystals using CRYSTAL14 computer code. The limiting barrier height for oxygen interstitial 3D migration is estimated as 1.3eV.

A Survey of Multi-Agent based Intelligent Decision Support System for Medical Classification Problems

has been growing on big data since last decade for discovering useful trends or patterns that are used in diagnosis and decision making. Intelligent decision support system an automated judgment that supports decision making is composed of human and computer interaction to help in decision making accuracy. Also multi-agent systems (MAS) are collections of independent intelligent entities that collaborate in the joint resolution of a complex problem. Multi-agent intelligent decision support systems can be used to solve large-scale convention problem. This paper is a survey of the recent research in multi- agent and intelligent decision support systems to support for classification problems. The purpose of the survey described in this paper is the development of a novel large-scale hybrid medical diagnosis system based on Multi-agent Intelligent Decision Support System (IDSS) for distributed database.

Robustness of spiking Deep Belief Networks to noise and reduced bit precision of neuro-inspired hardware platforms.

Increasingly large deep learning architectures, such as Deep Belief Networks (DBNs) are the focus of current machine learning research and achieve state-of-the-art results in different domains. However, both training and execution of large-scale Deep Networks require vast computing resources, leading to high power requirements and communication overheads. The on-going work on design and construction of spike-based hardware platforms offers an alternative for running deep neural networks with significantly lower power consumption, but has to overcome hardware limitations in terms of noise and limited weight precision, as well as noise inherent in the sensor signal. This article investigates how such hardware constraints impact the performance of spiking neural network implementations of DBNs. In particular, the influence of limited bit precision during execution and training, and the impact of silicon mismatch in the synaptic weight parameters of custom hybrid VLSI implementations is studied. Furthermore, the network performance of spiking DBNs is characterized with regard to noise in the spiking input signal. Our results demonstrate that spiking DBNs can tolerate very low levels of hardware bit precision down to almost two bits, and show that their performance can be improved by at least 30% through an adapted training mechanism that takes the bit precision of the target platform into account. Spiking DBNs thus present an important use-case for large-scale hybrid analog-digital or digital neuromorphic platforms such as SpiNNaker, which can execute large but precision-constrained deep networks in real time.

Large-Size CH3NH3PbBr3 Single Crystal: Growth and In Situ Characterization of the Photophysics Properties.

We reported a facile single-solution fabrication method to grow large-scale CH3NH3PbBr3 hybrid perovskite single crystal at room temperature. The obtained single crystal in this experiment was 14 × 14 mm. The sample's in situ photophysics properties under dark and illumination, including the surface morphology, work function, surface current distribution, microcosmic I-V curves, as well as the polarization behavior, were in situ characterized by integrated utilization of a scanning probe microscopy, respectively. Piezoresponse force microscopy (PFM) phase angles indicated the existence of "polarization" in CH3NH3PbBr3 lattice. Interestingly, the "polarization effect" was enhanced by the plus light source. Moreover, a surface potential shift as large as 200 mV was observed under the condition of the illumination on and off. This research is proposed to provide an opportunity to take a fresh look at the architectural design and photovoltaic performance origin of the hybrid perovskite solar cells.

Large-Scale Hybrid Simulation of a Steel Moment Frame Building Structure through Collapse

The implementation of two series of hybrid simulations that aim to trace the system-level seismic response of a four-story steel moment frame building structure through collapse is presented. In the first series of tests, a half-scale 1½-bay by 1½-story physical substructure of a special steel moment-resisting frame is considered, while in the second series the physical substructure corresponds to the gravity framing system with a similar-sized specimen. An objective of these tests is to demonstrate the potential of hybrid simulation with substructuring as a cost-effective alternative to earthquake simulators for large-scale system-level testing of structural frame subassemblies. The performance of a recently developed substructuring technique and time-stepping integration method for hybrid simulation are evaluated when employed with large and complex numerical substructures exhibiting large levels of nonlinear response. The substructuring technique simplifies the experimental setup by reducing the number of required actuators while adequately approximating the boundary conditions including lateral displacements and axial loads on columns. The test method was found to be reliable with capabilities to provide insight into experimental behavior of structural subassemblies under realistic seismic loading and boundary conditions.

SOLAR WIND TURBULENCE FROM MHD TO SUB-ION SCALES: HIGH-RESOLUTION HYBRID SIMULATIONS

We present results from a high-resolution and large-scale hybrid (fluid electrons and particle-in-cell protons) two-dimensional numerical simulation of decaying turbulence. Two distinct spectral regions (separated by a smooth break at proton scales) develop with clear power-law scaling, each one occupying about a decade in wave numbers. The simulation results exhibit simultaneously several properties of the observed solar wind fluctuations: spectral indices of the magnetic, kinetic, and residual energy spectra in the magneto-hydrodynamic (MHD) inertial range along with a flattening of the electric field spectrum, an increase in magnetic compressibility, and a strong coupling of the cascade with the density and the parallel component of the magnetic fluctuations at sub-proton scales. Our findings support the interpretation that in the solar wind large-scale MHD fluctuations naturally evolve beyond proton scales into a turbulent regime that is governed by the generalized Ohm's law.

Large-scale antenna systems with hybrid analog and digital beamforming for millimeter wave 5G

With the severe spectrum shortage in conventional cellular bands, large-scale antenna systems in the mmWave bands can potentially help to meet the anticipated demands of mobile traffic in the 5G era. There are many challenging issues, however, regarding the implementation of digital beamforming in large-scale antenna systems: complexity, energy consumption, and cost. In a practical large-scale antenna deployment, hybrid analog and digital beamforming structures can be important alternative choices. In this article, optimal designs of hybrid beamforming structures are investigated, with the focus on an N (the number of transceivers) by M (the number of active antennas per transceiver) hybrid beamforming structure. Optimal analog and digital beamforming designs in a multi-user beamforming scenario are discussed. Also, the energy efficiency and spectrum efficiency of the N × M beamforming structure are analyzed, including their relationship at the green point (i.e., the point with the highest energy efficiency) on the energy efficiency-spectrum efficiency curve, the impact of N on the energy efficiency performance at a given spectrum efficiency value, and the impact of N on the green point energy efficiency. These results can be conveniently utilized to guide practical LSAS design for optimal energy/ spectrum efficiency trade-off. Finally, a reference signal design for the hybrid beamform structure is presented, which achieves better channel estimation performance than the method solely based on analog beamforming. It is expected that large-scale antenna systems with hybrid beamforming structures in the mmWave band can play an important role in 5G.

Security and Privacy Dimensions in Next Generation DDDAS/Infosymbiotic Systems: A Position Paper

The omnipresent pervasiveness of personal devices will expand the applicability of the Dynamic Data Driven Application Systems (DDDAS) paradigm in innumerable ways. While every single smartphone or wearable device is potentially a sensor with powerful computing and data capabilities, privacy and security in the context of human participants must be addressed to leverage the infinite possibilities of dynamic data driven application systems. We propose a security and privacy preserving framework for next generation systems that harness the full power of the DDDAS paradigm while (1) ensuring provable privacy guarantees for sensitive data; (2) enabling field-level, intermediate, and central hierarchical feedback-driven analysis for both data volume mitigation and security; and (3) intrinsically addressing uncertainty caused either by measurement error or security-driven data perturbation. These thrusts will form the foundation for secure and private deployments of large scale hybrid participant-sensor DDDAS systems of the future.

Modeling and Coordinated Control Strategy of Large Scale Grid-Connected Wind/Photovoltaic/Energy Storage Hybrid Energy Conversion System

An AC-linked large scale wind/photovoltaic (PV)/energy storage (ES) hybrid energy conversion system for grid-connected application was proposed in this paper. Wind energy conversion system (WECS) and PV generation system are the primary power sources of the hybrid system. The ES system, including battery and fuel cell (FC), is used as a backup and a power regulation unit to ensure continuous power supply and to take care of the intermittent nature of wind and photovoltaic resources. Static synchronous compensator (STATCOM) is employed to support the AC-linked bus voltage and improve low voltage ride through (LVRT) capability of the proposed system. An overall power coordinated control strategy is designed to manage real-power and reactive-power flows among the different energy sources, the storage unit, and the STATCOM system in the hybrid system. A simulation case study carried out on Western System Coordinating Council (WSCC) 3-machine 9-bus test system for the large scale hybrid energy conversion system has been developed using the DIgSILENT/Power Factory software platform. The hybrid system performance under different scenarios has been verified by simulation studies using practical load demand profiles and real weather data.

Command and Control for Large-Scale Hybrid Warfare Systems

Emerging hybrid threats in large-scale warfare systems require networked teams to perform in a reliable manner under changing mission tactics and reconfiguration of mission tasks and force resources. In this paper, a formal Command and Control (C2) structure is presented that allows for computer-aided execution of the networked team decision-making process, real-time tactic selection, and reliable mission reconfiguration. A mathematically justified networked computing environment is provided called the Augmented Discrete Event Control (ADEC) framework. ADEC is portable and has the ability to provide logical connectivity among all team participants including mission commander, field commanders, war-fighters, and robotic platforms. The proposed C2 structure is developed and demonstrated on a simulation study involving Singapore Armed Forces team with three realistic symmetrical, asymmetrical, and hybrid attack missions. Extensive simulation results show that the tasks and resources of multiple missions are fairly sequenced, mission tactics are correctly selected, and missions and resources are reliably reconfigured in real time.

Phase transition–induced electrochemical performance enhancement of hierarchical CoCO3/CoO nanostructure for pseudocapacitor electrode

Phase transition of active electrode materials for pseudocapacitors always plays a pivotal role during the energy storage/release process. Here, large-scale hybrid CoCO3/CoO nanostructure arrays were obtained on carbon fiber paper substrate in a mild environment and tested as pseudo-capacitor electrode. After several cycles’ activity, the as-prepared electrodes exhibited good energy storage performance with maximum specific capacitance of 0.77F/cm2 in area and 510F/g in gram at a discharge current of 1A/g, and 82% of the capacity is retained when the discharge current increased to be 10A/g from 0.2A/g, indicating high power capability. Most interestingly, the electrode showed excellent cycling durability with gradually increased capacitance along with cyclic voltammetry at first 5,000 cycles and then maintained at least more than other 15,000 cycles. The initial phase transition of CoCO3/CoO to Co(OH)2/CoO induced by alkaline electrolyte was demonstrated to be the critical factor for the capacitance enhancement. The phase transition before and after long cycles was discussed through ex-situ X-ray diffraction, Raman and high resolution transmission electron microscope analysis.

Solving the large-scale hybrid flow shop scheduling problem with limited buffers by a hybrid artificial bee colony algorithm

This paper presents a novel hybrid algorithm (TABC) that combines the artificial bee colony (ABC) and tabu search (TS) to solve the hybrid flow shop (HFS) scheduling problem with limited buffers. The objective is to minimize the maximum completion time. Unlike the original ABC algorithm, in TABC, each food source is represented by a string of job numbers. A novel decoding method is embedded to tackle the limited buffer constraints in the schedules generated. Four neighborhood structures are embedded to balance the exploitation and exploration abilities of the algorithm. A TS-based self-adaptive neighborhood strategy is adopted to impart to the TABC algorithm a learning ability for producing neighboring solutions in different promising regions. Furthermore, a well-designed TS-based local search is developed to enhance the search ability of the employed bees and onlookers. Moreover, the effect of parameter setting is investigated by using the Taguchi method of design of experiment (DOE) to determine the suitable values for key parameters. The proposed TABC algorithm is tested on sets of instances with large scales that are generated based on realistic production. Through a detailed analysis of the experimental results, the highly effective and efficient performance of the proposed TABC algorithm is contrasted with the performance of several algorithms reported in the literature.

A phased approach to enable hybrid simulation of complex structures

Hybrid simulation has been shown to be a cost-effective approach for assessing the seismic performance of structures. In hybrid simulation, critical parts of a structure are physically tested, while the remaining portions of the system are concurrently simulated computationally, typically using a finite element model. This combination is realized through a numerical time-integration scheme, which allows for investigation of full system-level responses of a structure in a cost-effective manner. However, conducting hybrid simulation of complex structures within large-scale testing facilities presents significant challenges. For example, the chosen modeling scheme may create numerical inaccuracies or even result in unstable simulations; the displacement and force capacity of the experimental system can be exceeded; and a hybrid test may be terminated due to poor communication between modules (e.g., loading controllers, data acquisition systems, simulation coordinator). These problems can cause the simulation to stop suddenly, and in some cases can even result in damage to the experimental specimens; the end result can be failure of the entire experiment. This study proposes a phased approach to hybrid simulation that can validate all of the hybrid simulation components and ensure the integrity large-scale hybrid simulation. In this approach, a series of hybrid simulations employing numerical components and small-scale experimental components are examined to establish this preparedness for the large-scale experiment. This validation program is incorporated into an existing, mature hybrid simulation framework, which is currently utilized in the Multi-Axial Full-Scale Sub-Structuring Testing and Simulation (MUST-SIM) facility of the George E. Brown Network for Earthquake Engineering Simulation (NEES) equipment site at the University of Illinois at Urbana-Champaign. A hybrid simulation of a four-span curved bridge is presented as an example, in which three piers are experimentally controlled in a total of 18 degrees of freedom (DOFs). This simulation illustrates the effectiveness of the phased approach presented in this paper.

A large-scale hybrid simulated annealing algorithm for cyclic facility layout problems

The cyclic facility layout problem (CFLP) is a special case of the dynamic facility layout problem (DFLP) in which there are several production periods and the production cycle repeats itself by going to the first period after the last one because of the seasonal nature of products. In this article, a mixed integer programming formulation is developed for the CFLP. In the DFLP literature, department shapes are assumed to be given or fixed. However, this assumption does not hold in the case of the CFLP because the facility size is limited and the area requirements of the departments change significantly throughout the planning horizon. Therefore, department dimensions and sizes are considered as decision variables in the CFLP. A large-scale hybrid simulated annealing algorithm (LS-HSA) is proposed to solve the formulated problem and shown to be effective and versatile as it can be applied to various facility layout problems.