Footstep Power Generation

Piezoelectric energy harvesting is the new upcoming green and clean energy which works on piezoelectric principle. The lost energies are being captured and restored by the transducer and piezoelectric sensor in to a battery. The vibrations and motions caused by humans and machines will be used and stored in battery are being used by the small and low power electronic component and wireless technology, starts being to develop recently and so, necessary steps are taken to develop and find a new power source from harvesting technique. The power and energy from different sources are commonly used and simple power harvesting circuits will replace the power supplies which is currently used. These materials harvest small amount of energy which are ignored and wasted in the surrounding but this energy can be useful for powering the small electrical components in a system. The research made to accumulate the power through this method and sources so an estimate amount of energy can be produced and stored. At the end of this project, the outcomes should be a stable power source to charge a battery and light a bulb of small watt and further can be used for multiple tasks and applications. Keywords: Energy harvesting, Piezoelectric sensors, Solid works Analysis

Smart Sensors for Augmented Electrical Experiments

With the recent increase in the use of augmented reality (AR) in educational laboratory settings, there is a need for new intelligent sensor systems capturing all aspects of the real environment. We present a smart sensor system meeting these requirements for STEM (science, technology, engineering, and mathematics) experiments in electrical circuits. The system consists of custom experiment boxes and cables combined with an application for the Microsoft HoloLens 2, which creates an AR experiment environment. The boxes combine sensors for measuring the electrical voltage and current at the integrated electrical components as well as a reconstruction of the currently constructed electrical circuit and the position of the sensor box on a table. Combing these data, the AR application visualizes the measurement data spatially and temporally coherent to the real experiment boxes, thus fulfilling demands derived from traditional multimedia learning theory. Following an evaluation of the accuracy and precision of the presented sensors, the usability of the system was evaluated with n=20 pupils in a German high school. In this evaluation, the usability of the system was rated with a system usability score of 94 out of 100.

Hydrothermal Unit-Commitment Problem of a Large-Scale System with Representation of Forbidden Zones

As we move towards electrical networks with a growing presence of renewable generation, the representation of the electrical components becomes more important. In hydro-dominated power systems, modelling the forbidden zones of hydro plants becomes increasingly challenging as the number of plants increases. Such zones are ranges of generation that either should be avoided or are altogether unreachable. However, because representing the forbidden zones introduces a substantial computational burden, hydrothermal unit-commitment problems (HTUC) for large systems are usually formulated ignoring the forbidden zones. Nonetheless, this simplification may demand adjustments to the solution of the HTUC, because the generation of the hydro stations may fall in forbidden zones. In practice, the adjustments are usually performed based on the experience of system operators and, then, can be far from an optimal correction. In this paper, we study the impact of explicitly representing the hydro-generation forbidden zones in a large-scale system with more than 7000 buses, 10,000 lines, and 700 hydro units. Our findings show that the simplified model that is current used can deviate significantly from the model with forbidden zones, both in terms of the generation of hydro plants, as well as the generation of thermal plants and the system marginal costs.

Electrochemical Impedance Spectroscopy and Its Applications

Electrochemistry has become an important and recognized field for the future since many of its approaches contemplate the establishment of stable energy supplies and the minimization of our impact on the environment. In this regard, electrochemistry can face both objectives by studying the electrode/solution interface. As a result, different electrochemical techniques can be used to study the interface to understand the electron transfer phenomena in different reactions. Considering this, one of the most useful techniques to understand the electrode/solution interface is electrochemical impedance spectroscopy. This technique allows us to describe the electrode behavior in the presence of a certain electrolyte in terms of electrical parameters such as resistances and capacitances, among others. With this information, we can infer the electrochemical behavior toward a specific reaction and the capacity of the electrode to carry on the electron transfer depending on its resistance (impedance) values. The aim of this chapter is to go from the theory, based on Ohm’s Law and its derivations, to actual applications. This will lead us to characterize the solution, electrode, and the interface between these two phases based on their electrical components by using an equivalent electrical circuit, such as the Randles equivalent circuit.

Evaluation of the Explosion Pressure Parameters in Flameproof Enclosures under the Pressure Piling Condition

Explosion resistance is one of the most important performances for all flameproof enclosures. Pressure piling requires the flameproof enclosures to withstand explosion pressure higher than the design pressure. In order to study the explosion parameters in a flameproof enclosure under pressure piling, two experimental setups were prepared based on the theoretical analysis of the mechanism of pressure piling. One setup simulated the condition that the interior of a flameproof box is isolated by a baffle with a small hole. Another setup simulated the condition that a large number of electrical components were installed inside an explosion-proof box. The experimental result showed that the explosion pressure increased significantly in a very short time under pressure piling. When an explosion occurred in a cavity, the pressure wave of the explosion propagated faster than the flame propagation, and the pressure wave was transmitted to another cavity through a gas channel between the two cavities. This resulted in the pre-pressurization of the combustible gas in another cavity. It was observed that the ignition time in the cavity with an ignition source, is the key factor for pressure piling.

Self-Similar Functional Circuit Models of Arteries and Deterministic Fractal Operators: Theoretical Revelation for Biomimetic Materials

In this paper, the self-similar functional circuit models of arteries are proposed for bioinspired hemodynamic materials design. Based on the mechanical-electrical analogous method, the circuit model can be utilized to mimic the blood flow of arteries. The theoretical mechanism to quantitatively simulate realistic blood flow is developed by establishing a fractal circuit network with an infinite number of electrical components. We have found that the fractal admittance operator obtained from the minimum repeating unit of the fractal circuit can simply and directly determine the blood-flow regulation mechanism. Furthermore, according to the operator algebra, the fractal admittance operator on the aorta can be represented by Gaussian-type convolution kernel function. Similarly, the arteriolar operator can be described by Bessel-type function. Moreover, by the self-similar assembly pattern of the proposed model, biomimetic materials which contain self-similar circuits can be designed to mimic physiological or pathological states of blood flow. Studies show that the self-similar functional circuit model can efficiently describe the blood flow and provide an available and convenient structural theoretical revelation for the preparation of in vitro hemodynamic bionic materials.

AS-Solar, a Tool for Predictive Maintenance of Solar Groundwater Pumping Systems

Energy for water abstraction limits the viability of some irrigable areas. Increasing efficiency and introducing renewable energy can reduce energy cost. Solar pumping is a widely recognized renewable energy solution. These pumping systems suffer special wear out due to sudden changes and for having working conditions far from the nominal points. Thus, monitoring systems are becoming more frequent for maintenance issues. A new decision support system, named AS-Solar, was developed to perform predictive maintenance. This model permits detecting if the source of the anomaly in the pump performance is the pump, the electrical components (motor, variable frequency drive (VFD) or cables) or the pumping pipe. It demands real-time data from the monitoring system and an accurate simulation model, together with an optimization process that helps in the decision making in predictive maintenance. To validate the developed model, it was applied to a complex case study of a solar pumping system of 40 kWp that abstracts groundwater from nearly 200 m deep. This pumping system has a VFD, two lines of cables up to the pump and aggressive water with slimes, which causes different problems in the pumping system. In this case study, the AS-Solar model shows an acceptable accuracy, with a relative error (RE) of the 2.9% in simulated power and 7.9% in simulated discharge.

Deterministic & Probabilistic Evaluations of Structures & Components Credited for Seismic Design Extension Conditions

There is "high confidence" in the ability of structures, systems and components (SSCs) of Nuclear Power Plants (NPPs) to perform as designed during Design Basis Accidents. For Design Extension Conditions (DECs), the SSCs are required to perform as designed with "reasonably high confidence." A deterministic design method is proposed to address DECs' higher demands in new and existing CANDU NPPs. The deterministic method builds on the current requirements of applicable codes and standards and recommends more relaxed acceptance criteria. Nevertheless, a means to probabilistically evaluate built-in margins exceeding demand induced by a DEC would provide a measure of the confidence in a DEC-assigned structure or component performing its function. Therefore, a probabilistic method that estimates the probability of survivability for a structure or component when subjected to the demand induced by a DEC is proposed. The probabilistic method could be used to indicate whether there is a need for applying design modification to existing design features to address demands of seismic DEC. The mean, 5-percentile, and 95-percentile fragility functions of these SSCs are used. These fragility functions are typically developed to determine the High-Confidence-Low-Probability-of-Failure value associated with the contribution of a structure or component to the overall plant seismic risk. Sample cases for design features that were implemented in existing CANDU NPPs to address DECs are presented. Both the deterministic and probabilistic methods are applied to cases of Civil structures, passive Mechanical & Electrical components as well as active Control & Instrumentation components.

Inrush Current Based on Fast Fourier Transform

Advances in technology have caused the use of electricity to increase rapidly. With advances in technology, this is followed by the use of increasingly efficient electrical components or equipment. This more efficient electrical equipment causes the impedance of the component to be smaller, causing a surge in current when it is turned on. This current surge, if not followed by appropriate safety precautions, will be damage other components. Each load has different waveform characteristics and current transient peaks. For this reason, it is necessary to analyze the transient condition of a load to overcome this. This paper will explain the characteristics of the inrush current of the load due to ignition. There are three loads used in this study, namely resistive, capacitive and inductive loads. Then the use of this load is simulated by giving different ignition angle values, namely 0, 60, and 90 degrees. The analysis used is the Fast Fourier Transform (FFT) method which is a derivative of the Discrete Fourier Transform. The inrush current spectrum in this simulation is simulated using Simulink MATLAB with switching system modeling using TRIAC. This inrush current simulation data collection uses a sampling frequency of 100 Khz and will be analyzed in the first of 5 cycles. For each load in this paper, the harmonic values for each ignition angle will be presented. The simulation results show that the inrush current is caused by the ignition angle value used and because of components that can deviate energy such as inductors and capacitors as well as components which at the time of starting have a low impedance value such as incandescent lamps. The simulation also shows that the use of switching components for setting the ignition angle causes an increase in the value of Total Harmonic Distortion (THD) but the peak current in the first cycle when the ignition angle is set decreases.

Artificial Neurons Based on Ag/V2C/W Threshold Switching Memristors

Artificial synapses and neurons are two critical, fundamental bricks for constructing hardware neural networks. Owing to its high-density integration, outstanding nonlinearity, and modulated plasticity, memristors have attracted emerging attention on emulating biological synapses and neurons. However, fabricating a low-power and robust memristor-based artificial neuron without extra electrical components is still a challenge for brain-inspired systems. In this work, we demonstrate a single two-dimensional (2D) MXene(V2C)-based threshold switching (TS) memristor to emulate a leaky integrate-and-fire (LIF) neuron without auxiliary circuits, originating from the Ag diffusion-based filamentary mechanism. Moreover, our V2C-based artificial neurons faithfully achieve multiple neural functions including leaky integration, threshold-driven fire, self-relaxation, and linear strength-modulated spike frequency characteristics. This work demonstrates that three-atom-type MXene (e.g., V2C) memristors may provide an efficient method to construct the hardware neuromorphic computing systems.