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Wang, Hong

Publications and source records attributed to Wang, Hong.

At least 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Globalized Modeling and Signal Timing Control for Large-scale Networked Intersections

Traffic intersections are often the bottlenecks of traffic systems. Given a traffic network, an optimal traffic signal control strategy can result in smooth traffic flow and thus reduce energy consumption and environmental impact at intersections. This study aims to develop a new multi input and multi output (MIMO) traffic signal control method that can improve network wide traffic operations in terms of delay and energy consumption. In this context, a 35 intersection network of Bellevue, WA is used as the basis for the development of the algorithm, where modeling and intersection controls in a globalized setting are established using MIMO linear control theory and high matrix formulation. The proposed control method is evaluated in a microscopic traffic simulation environment, VISSIM. Simulation results show that the proposed method has much shorter average travel delays in the network when compared with the delays of conventional pretimed and actuated controls.

Wang, Hong↗
DOE OSTI2019

Acceleration and Stabilization of Electron Transfer Products with Improved Quantum Yields upon Cation Binding to a Fused Bis-Zinc Porphyrin-Quinone Donor–Acceptor Conjugate

The role of metal ions in promoting electron transfer processes in biological coenzymes is of great significance not only to understand their mechanistic details but also due to their direct utilization in a number of chemical and biochemical processes. Here, we demonstrate an increased rate of forward electron transfer with improved reaction quantum yield, and an enhanced lifetime of electron transfer products upon cation binding to the acceptor entity in a donor-acceptor conjugate. Selective binding of cations such as Mg 2+ or Sc 3+ to the electron acceptor, quinone, in a fused, bis-zinc porphyrin-quinone donor-acceptor conjugate leads to facile reduction of the quinone making the electron transfer process thermodynamically highly feasible. Furthermore, the binding of metal ions to the electron transfer product, quinone anion, decelerates the reverse electron transfer process due to ion-pairing interactions, resulting in improving both the lifetime and quantum yields of the electron transfer products. Furthermore, systematic studies including spectral, electrochemical, computational, spectroelectrochemical, and transient absorption techniques, coupled with data analysis by Global Target Analysis (GloTarAn), are performed to demonstrate these novel findings that are relevant to further our understanding of electron transfer processes occurring in biological coenzymes and pertinent energy harvesting schemes.

Charge transfer↗
DOE OSTI2019

WSBP/NWBP small-world neural network and its performance for wind power forecasting

A small-world neural network has stronger generalization ability with high transfer efficiency than that of the regular neural networks. This paper presents two novel small-world neural networks, the Watts-Strogatz small-world based on a BP neural network (WSBP) and a Newman-Watts small-world neural network based on a BP neural network (NWBP), related to previous research of complex networks. The algorithms are developed separately by adopting WS and NW small-world networks as their topological structures, and their derivation and convergence criterion are progressively discussed. After that, the proposed models are subsequently tested by two typical nonlinear functions which confirm their significant improvement over the regular BP networks and other algorithms. Finally, a wind power prediction system is advanced to verify their generalization abilities, and show that the models are practically feasible and effective with improved accuracy and acceptable forecasting errors caused by wind fluctuation and randomness with a time scale up to 24 h.

17 WIND ENERGY↗
DOE OSTI2019

Parameter Co-optimization for Hybrid Electric Vehicles Powertrain System Leveraging V2V/V2I Information

A parameter tuning based co-optimization scheme for the hybrid electric vehicles (HEV) powertrain system is designed to maximize the fuel efficiency. The optimization controlled input parameters are chosen based on sensitivity study of powertrain control parameters. The vehicle to vehicle (V2V) and vehicle to infrastructure information is another optimization input, to have the driving conditions taking in to considerations for maximizing fuel efficiency. The catalyst temperature is considered as an additional constraint as the speed to reach lightoff temperature should not decrease during optimized operation. Neural network is used to develop a simplified yet equivalent model for the optimization problem model. We have achieved an average of 9.22% fuel savings for a random driving cycle on a Toyota Prius test model.

Hong, Wanshi↗
DOE OSTI2019

Investigating the Impact of Connected Vehicle Market Share on the Performance of Reinforcement-Learning Based Traffic Signal Control

We aim to understand and explore the performance of reinforcement learning based signal control algorithms in a mixed environment with less than 100% market share of connected and automated vehicles (CAVs). Within a simulation environment, we have considered partial connectivity—less than 100% market share of CAVs—in the network and investigated the impact on the performance of the signal control algorithm. Two test networks including a four-intersection arterial in Lankershim Boulevard, CA, and a portion of downtown Springfield, IL, with 20 intersections. The first network is calibrated in the micro-simulator PTV Vissim with the US DOT provided NGSIM datasets. The results provide insights regarding the impact of the connectivity and sensing technologies on the practical implementation of traffic signal control algorithms that leverage the data sharing capability of a connected environment. For scenarios with 40% or more market share of CAVs, we observed improvement in the performance metrics—travel time, queue time, and energy consumption—with the increase in market share. Results from our experiments do not indicate any clear trend when the networks have low (less than 40%) market share of CAVs. The higher standard deviations as obtained from the statistical analyses of the performance metrics at low market share may indicate the instability of the RL controller arising from the partial (if not zero) observability of the traffic states. Further, we have conducted simplified scenario analyses to explore the impact of the market share of battery electric vehicles (BEVs) on energy consumption due to the regenerative braking feature. Our results and findings will be the foundation for the future reinforcement learning based control algorithm development that accounts for partial connectivity—less than 100% CAV market share, and the presence of BEVs in a network of connected and automated signalized intersections.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2019

A Survey of Distributed Optimization

In distributed optimization of multi-agent systems, agents cooperate to minimize a global function which is a sum of local objective functions. Motivated by applications including power systems, sensor networks, smart buildings, and smart manufacturing, various distributed optimization algorithms have been developed. In these algorithms, each agent performs local computation based on its own information and information received from its neighboring agents through the underlying communication network, so that the optimization problem can be solved in a distributed manner. This survey paper aims to offer a detailed overview of existing distributed optimization algorithms and their applications in power systems. More specifically, we first review discrete-time and continuous-time distributed optimization algorithms for undirected graphs. We then discuss how to extend these algorithms in various directions to handle more realistic scenarios. Finally, we focus on the application of distributed optimization in the optimal coordination of distributed energy resources.

Yang, Tao↗
DOE OSTI2019

A2 and A2B2 Benzoporphyrins as sensitizers for dye-sensitized solar cells

The first example of A2B2 tetrabenzoporphyrin (KW-4) was synthesized, characterized and evaluated as a sensitizer for dye-sensitized solar cells. UV-vis and fluorescence spectroscopy revealed red-shifted and broadened absorption spectra of A2B2 tetrabenzoporphyrin as compared with its A2 dibenzo- and A2B2 dibenzoporphyrin analogues, which is a desired feature of dyes for dye-sensitized solar cells. DFT calculations also indicate favorable electron density distribution on the HOMO and LUMO of KW-4. However, the power conversion efficiency of the solar cell based on tetrabenzoporphyrin KW-4 displayed inferior performance than that of the solar cell based on A2 dibenzoporphyrin KW-2. The lower performance of the KW-4 cell was ascribed to two factors: the low lying LUMO energy level leading to less efficient electron injection and the “flat geometry” of the dye on TiO 2 surface facilitating charge recombination and decreasing dye loading. The investigation of anchoring group effect suggests that the acrylic acid group is a better anchoring group than pentadienyl carboxylic acid.

A2B2↗
DOE OSTI2019

β-Functionalized push–pull opp-dibenzoporphyrins as sensitizers for dye-sensitized solar cells: the role of the phenylethynyl bridge

A novel class of β-functionalized push–pull zinc opp-dibenzoporphyrins was designed and synthesized as sensitizers for dye-sensitized solar cells. Dibenzoporphyrin YH7 displayed strong push–pull characteristics, which included clearly segregated HOMO/LUMO and fast charge injection from the singlet excited state of zinc porphyrin to the conduction band of TiO 2 . The incorporation of both the phenylethynyl bridge and amino group was critical to achieve the enhanced push–pull effect. The highest PCE value in this series obtained with the YH6 cell was 6.7%, which is comparable to that of the best ruthenium dye, N719 (η = 7.4%), under similar conditions. The high PCE of the YH6 cell is ascribed to its high light harvesting ability and favorable cell kinetics, which is supported by electrochemical impedance spectroscopy studies and femtosecond transient absorption studies. An unusual illumination-induced photodegradation was observed for YH7, which was attributed as the major reason for the unexpected lower PCE of the YH7 cell (η = 5.7%). Furthermore, this work demonstrates the applicability of π-extended porphyrins as a new generation of sensitizers for high performance dye-sensitized solar cells.

Hu, Yi↗
DOE OSTI2019

Technical Gap Assessment for Materials and Component Integrity Issues for Molten Salt Reactors

Material selection and qualification is an important consideration for the deployment of molten salt reactors (MSRs). This report summarizes the most important materials issues that must be considered for licensing MSRs. Because of the variety of MSR designs under consideration, this report considers materials for both fluoride and chloride applications, with both fast and thermal neutron spectra.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2019

Research Considerations for Foam Fracturing in Stimulation Development for Enhanced Geothermal Systems

In regions where hydraulic fracturing is being considered for enhanced geothermal systems (EGS), and use of water is an issue, foam fracturing is an attractive option as a reduced water or waterless stimulation method. Although it has been shown to be an effective alternative in oil & gas production, foam fracturing has not yet been demonstrated in geothermal energy development. There are many challenges encountered in EGS. The reservoir may be located at great depth where earth stresses will be large and rock strength may be high. In addition, the viscosity of foam is higher than that of a pure single-phase fluid. Thus, the fracturing pressure will be increased substantially if a conventional fracturing routine is used. Moreover, fracturing in EGS systems may have more potential for induced seismicity. A proactive approach is proposed to address this technical challenge by using pulsed injection in a current project, sponsored by the U.S. DOE GTO Waterless Stimulation Initiative. This approach enables the dynamic responses of rock structure to be utilized and a new cavitation-based material-removal mechanism to be explored for enhanced fracturing efficiency. It also offers an approach to mitigate fracturing-induced seismicity and the potential to control dynamic behavior of foamed fluids. Research considerations will be described for investigation of the above phenomena in foam fracturing for EGS stimulation development.

Wang, Hong↗
DOE OSTI2019

Piezoresistive Characteristics of Silicon Carbide for Integrated Sensor Applications

Successful ubiquitous deployment of advanced reactors will depend to a large extent on the development of high-performance materials and sensors. Recently, there has been increasing interest in advanced reactors operating at very high temperatures (greater than 700 °C) and using molten salts as the primary coolant. In such reactor systems, temperature and pressure measurements are conducted using standard legacy thermocouples and pressure measurement technologies, both of which suffer from resolution issues, inaccuracies, and drift under harsh operating temperature and radiation conditions. We report on the structural, electrical, and mechanical characteristics of SiC materials and devices for the development of an integrated monolithic sensor unit capable of simultaneously monitoring temperature, pressure and flow in molten salt reactors, while at the same time exhibiting significant improvements in resolution, accuracy and signal-to-noise ratio.Wide bandgap and chemical inertness of SiC make it suitable for harsh environment sensor applications. We report on the development of a SiC pressure sensor exploiting its piezoresistive properties. Attempts have been made to fabricate thermally stable pressure sensor through doping induced high gauge factor. Both implanted and in-situ doped SiC wafers are being investigated to analyze the impact of dopant type and concentration on the piezoresistive characteristics. The microstructure, composition, and electrical conductivity of SiC samples have been analyzed to find optimum dopant incorporation and activation conditions. The mechanical measurements are being conducted on SiC beams with photolithographically defined surface piezoresistors to establish gauge factor for high performance sensors that can operate at temperatures beyond the limits of conventional silicon CMOS materials and devices.

Joshi, Pooran↗
DOE OSTI2019

RBFNN-based Minimum Entropy Filtering for a Class of Stochastic Nonlinear Systems

This paper presents a novel minimum entropy filter design for a class of stochastic nonlinear systems which are subjected to non-Gaussian noises. Motivated by stochastic distribution control, an output entropy model is developed using RBF neural network while the parameters of the model can be identified by the collected data. Based upon the presented model, the filtering problem has been investigated while the system dynamics have been represented. As the model output is the entropy of the estimation error, the optimal nonlinear filter is obtained based on the Lyapunov design which makes the model output minimum. Moreover, the entropy assignment problem has been discussed as an extension of the presented approach. To verify the presented design procedure, a numerical example is given which illustrates the effectiveness of the presented algorithm. The contributions of this paper can be included as 1) an output entropy model is presented using neural network; 2) a nonlinear filter design algorithm is developed as the main result and 3) a solution of entropy assignment problem is obtained which is an extension of the presented framework.

42 ENGINEERING↗
DOE OSTI2018

β-Functionalized trans -A2B2 push–pull tetrabenzoporphyrins

A series of β-functionalized trans-A2B2 tetrabenzoporphyrins have been successfully designed and synthesized through newly developed regioselective bromination chemistry of porphyrins and a Pd(0) catalyzed three-step-one pot reaction. These benzoporphyrins exhibit unique patterns of UV-Vis absorptions and emissions. Tetrabenzoporphyrins possess a unique combination of photophysical, optoelectronic, and physicochemical properties due to their largely extended π-conjugation and associated dynamics of ring deformation which make them distinctive from their parent porphyrins. As compared with their parent porphyrins, tetrabenzoporphyrins often display significantly red-shifted absorption bands, a much-desired feature for various applications ranging from biomedicine to organic electronics. However, due to limited synthetic methods, only a small number of simple symmetrical tetrabenzoporphyrins have been available for study. Unsymmetrical tetrabenzoporphyrins, in particular those functionalized at the porphyrin β-positions, are very difficult to access. A2B2 porphyrins, on the other hand, represent an attractive class of materials for non-linear optical applications as well as for other applications such as those involving dye-sensitized solar cells. meso-Functionalized push–pull trans-A2B2 porphyrins have previously been made available through the Suzuki coupling reaction, the Heck reaction and the Sonogashira coupling reaction of 5,10-dibromoporphyrin with the corresponding alkyl boronic acids, olefins and alkynes, respectively and have demonstrated interesting non-linear optical properties. In contrast, β-functionalized push–pull A2B2 porphyrins of the type shown in Fig. 1 have until now remained unknown. Furthermore, we present the synthesis and characterization for the first examples of β-functionalized A2B2 push–pull tetrabenzoporphyrins.

Kumar, Siddhartha↗
DOE OSTI2018

Minimizing Energy Consumption from Connected Signalized Intersections by Reinforcement Learning

Explicit energy minimization objectives are often discouraged in signal optimization algorithms due to its negative impact on mobility performance. One potential direction to solve this problem is to provide a balanced objective function to achieve desired mobility with minimized energy consumption. This research developed a reinforcement learning (RL) based control with reward functions considering energy and mobility in a joint manner-a penalty function is introduced for number of stops. Further, we proposed a clustering-based technique to make the state-space finite which is critical for a tractable implementation of the RL algorithm. We implemented the algorithm in a calibrated NG-SIM network within a traffic micro-simulator-PTV VISSIM. With sole focus on energy, we report 47% reduction in energy consumption when compared with existing signal control schemes, however causing a 65.6% increase in system travel time. In contrast, the control strategy focusing on energy minimization with penalty for stops yields 6.7% reduction in energy consumption with 27% increase in system travel time. The developed RL algorithm with a flexible penalty function in the reward will achieve desired energy goals for a network of signalized intersections without compromising on the mobility performance.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2018

Collaborative operational fault tolerant control for stochastic distribution control system

Based on a class of industry processes, a distributed fault diagnosis and a collaborative operational fault tolerant control algorithms are presented for an irreversible interconnected stochastic distribution control system with boundary conditions. Different from the existed collaborative fault tolerant controllers, the controller does not need to change after fault occurs, the system tracking performance can be maintained by adjusting the setpoint of the whole system. Simulations are also included to show the effectiveness of the proposed algorithm and encouraging results have been obtained.

Stochastic distribution control, Fault diagnosis, ↗