Developing A Sensing System for the Measurement of Oxygen Concentration in Liquid Pb-Bi Eutectic: Quarterly Progress Report (Aug. 01 – Oct. 31, 2003)

The experimental setup designed and manufactured in UNLV was shipped to LANL in early Aug. One student has been working in LANL to conduct the experiment since then. In the meantime, one new Ph. D. student has started to run the simulation for transport in oxygen mixing. In Oct., a professional has been hired to work in both experimental and the theoretical studies pertaining to the proposed work

Thermal Transient Flow Rate Sensor for High Temperature Liquid Metal Cooled Nuclear Reactor

In nuclear power plants and accelerator driven system (ADS) for nuclear waste treatment, it is important to monitor the coolant flow rate in the reactor core and pipe-line. In such a strong irradiation, high pressure and temperature environment, no accurate local flow measurement technique is readily available. Electromagnetic (EM) flow meter is popular in low temperature application as it is a non-intrusive technology. However, additional voltage will be produced due to temperature, flow, pressure, the chemical properties of the liquid metal and surface condition of the steel walls. In addition, the non-definite wetting behavior of liquid lead-bismuth to the electrically conducting structure material can lead to incorrect readings even during one measurement day. As the temperature measurement technique is well developed for high temperature applications, one alternative flow rate measurement technique is proposed here based on correlation velocity measurement using temperature sensors. The impulse response function (IRF) will be used instead of the cross-correlation function in the time delay estimation. The IRF method shows a more accurate estimation of the transit time, which allows extremely low velocities (down to 2 cm/sec) to be detected. In this research work, 2 the faster thermal diffusion effect in low Prandtl number liquid metal will be considered for the better delay time estimation. The proposed research will be completed in two years, and in specific, the PIs plan to fulfill the research missions by performing the following activities: 1. Review the related literature on correlation velocity measurement technique using temperature noise in the flow field; 2. Design and construct a correlation velocity measurement device with a possibility of changing the distances between the two temperature sensors; 3. Develop a signal processing and data reduction scheme and implement it to a LabVIEW data acquisition system; 4. Perform experiments with different sensor distances and various Reynolds numbers in several different water temperatures in single-phase water flows. Experimental results will be compared to a Pitot tube or hot-wire anemometry; 5. Evaluate the measurement device in the by-pass system of TC-1. 6. Design a circuit board for sensor integration

Wind Power Forecasting Methods Based on Deep Learning: A Survey

Accurate wind power forecasting in wind farm can effectively reduce the enormous impact on grid operation safety when high permeability intermittent power supply is connected to the power grid. Aiming to provide reference strategies for relevant researchers as well as practical applications, this paper attempts to provide the literature investigation and methods analysis of deep learning, enforcement learning and transfer learning in wind speed and wind power forecasting modeling. Usually, wind speed and wind power forecasting around a wind farm requires the calculation of the next moment of the definite state, which is usually achieved based on the state of the atmosphere that encompasses nearby atmospheric pressure, temperature, roughness, and obstacles. As an effective method of high-dimensional feature extraction, deep neural network can theoretically deal with arbitrary nonlinear transformation through proper structural design, such as adding noise to outputs, evolutionary learning used to optimize hidden layer weights, optimize the objective function so as to save information that can improve the output accuracy while filter out the irrelevant or less affected information for forecasting. The establishment of high-precision wind speed and wind power forecasting models is always a challenge due to the randomness, instantaneity and seasonal characteristics

A Graph-Based Reinforcement Learning Method with Converged State Exploration and Exploitation

In any classical value-based reinforcement learning method, an agent, despite of its continuous interactions with the environment, is yet unable to quickly generate a complete and independent description of the entire environment, leaving the learning method to struggle with a difficult dilemma of choosing between the two tasks, namely exploration and exploitation. This problem becomes more pronounced when the agent has to deal with a dynamic environment, of which the configuration and/or parameters are constantly changing. In this paper, this problem is approached by first mapping a reinforcement learning scheme to a directed graph, and the set that contains all the states already explored shall continue to be exploited in the context of such a graph. We have proved that the two tasks of exploration and exploitation eventually converge in the decision-making process, and thus, there is no need to face the exploration vs. exploitation tradeoff as all the existing reinforcement learning methods do. Rather this observation indicates that a reinforcement learning scheme is essentially the same as searching for the shortest path in a dynamic environment, which is readily tackled by a modified Floyd-Warshall algorithm as proposed in the paper. The experimental results have confirmed that the proposed graph-based reinforcement learning algorithm has significantly higher performance than both standard Q-learning algorithm and improved Q-learning algorithm in solving mazes, rendering it an algorithm of choice in applications involving dynamic environments

Thermal Transient Flow Rate Sensor for High Temperature Liquid Metal Cooled Nuclear Reactor

In nuclear power plants and accelerator driven systems (ADS) for nuclear waste treatment, it is important to monitor the coolant flow rate in the reactor core and pipe-line. In such a strong irradiation, high pressure, and temperature environment, the existing flow measurement techniques (such as Electromagnetic flow meters, Ultrasonic flow meters, Turbine flow meters, etc.) are not accurate and reliable. The measurement of flow rates (mass flow rates or volume flow rate) plays a notable role in monitoring and controlling the experimental conditions. The bulk flow rates can be obtained through direct methods, which measure the amount of discharged fluids over a period of time. Alternatively, flow rates can also be obtained using indirect methods. For example, they can be derived through the measurement of fluid velocities. So far, the velocities have been found in strong correlation with signals of pressure, temperature, optical wave, ultrasonic wave, etc. based on diverse physical principles. Note that with some exceptions, the flow rate measurement systems require calibration or empirical corrections, especially after long term operation. In the application of liquid metal coolant flow rate measurement, the high temperature, pressure, and corrosion environment limit most flow meter devices from being used in long term and maintenance-free operation. As the temperature measurement technique is well developed for high temperature applications, one flow rate measurement technique is proposed based on the correlated thermal signals. This way, the measurement errors due to long term corrosion will be easily counteracted using this proposed method. Correlated thermal signals are measured to deduce the flow velocity

Developing a Sensing System for the Measurement of Oxygen Concentration in Liquid Pb-Bi Eutectic

The research objectives of this project were as follows: To generate calibration curves of voltage versus oxygen concentration for the YSZ oxygen sensor system under various temperatures in liquid LBE. To determine the sensor characteristics of the YSZ sensor system. To determine oxygen dissolving rates in LBE under different temperatures in vitro. To study the effects of unwanted electrical conductivity, contributed by the mobility of the electrons at high temperatures, for more accurate oxygen measurement. To study alternative and promising oxygen measuring methods

Wireless Sensor networks and the Internet of Things

It is estimated that mobile internet devices that can act as sensors will outnumber humans this year (2013), and by 2015, there will be about 15 billion internet-connected devices. Related applications are thriving in commercial, civic, and scientific operations that involve sensors, web, and services, leading by both academic societies and industry companies. It is commonly accepted that the next generation of internet is becoming the “Internet of Things (IoT)” which is a worldwide network of interconnected objects and their virtual representations uniquely addressable based on standard communication protocols. Identified by a unique address, any object including computers, mobile phones, RFID tagged devices, and especially Wireless Sensor Networks (WSN) will be able to dynamically join the network, collaborate, and cooperate efficiently to achieve different tasks. With all these objects in the world equipped with tiny identifying devices, daily life on earth would undergo a big transformation

A bulk-driven CMOS voltage-to-current transconductor and its applications

Techniques that can provide non-degraded performance at low power supply voltages and consuming less power are demanded and will continue to evolute. In this thesis a novel bulk-driven CMOS voltage to current transconductor (VCT) is introduced. In contrast with the conventional gate-driven transconductors, this new transconductor (called bulk-driven VCT) has great potential to be used in low power low voltage supply system. Characteristics (DC, AC, etc.) related to this VCT circuit have been investigated. Noise performance of the circuit has been studied as well. Simulation and test results on several prototype chips fabricated in a 1.5 micron CMOS process show close agreements between the theoretical and test results. The functional parameters versus power consumption of the new VCT is very impressive compared with similar gate-driven VCTs that have been reported in the literature. This bulk-driven VCT can be further used to synthesize many components (like resistors and inductors). Using VCT-based inductors, a large system (filter) has been built. Advantage and disadvantage of the synthesized filter system have been shown through simulation and test results respectively. This VCT circuit may find its applications in audio devices and biomedical equipment, in which a modest working frequency band and efficient power consumption are required

A Computation Model for Nanoantenna-based Solar Cell with High Conversion Efficiency

Build a model of spiral nanoantenna and an antennaarray based solar cell collector. Using Rao-Wilton-Glisson (RWG) basis functions tosimulate the spiral nanoantennas. We calculate the frequency response of the radiationgain as the indicator of receiving bandwidth which is akey factor in conversion efficiency