Logistics cost analysis of rice straw pellets for feasible production capacity and spatial scale in heat utilization systems: A case study in Nanporo town,Hokkaido, Japan

Rice straw is a promising renewable energy source because it is abundantly available in Asia. This study conducted a case study of logistics cost analysis for rice straw pellets by considering all stages in the supply chain to define the main factors affecting the selling price of rice straw pellets: collection (job-commission or employment of part-time workers), transportation, storage (vinyl greenhouses or storage buildings with larger capacity), pelletizing, and delivery to users with biomass boilers. The selling price was found to be strongly dependent on the production capacity because the investment cost for the pellet production facility had a significant effect of economies of scale. A production capacity of larger than 1500 t y⁻¹ is required for rice straw pellets to compete with wood pellets and fossil fuels in the studied Japanese context if the subsidy rate for the investment is 50%, part-time workers conduct the collection, and rice straw is stored in the storage buildings. Our sensitivity analysis also showed an economically feasible spatial scale: for example, rice straw should be collected within a 20 km radius and the users should be within a 38 km radius when the production capacity is 1500 t y⁻¹. In addition, other critical factors related to the collection of rice straw from the paddy fields and transportation of rice straw rolls to storage were identified as planning factors to further reduce the total logistics cost of rice straw pellets.     

Sensorless Vector Control of Induction Motors Using Minimum Dimensional Flux D‐State Observer with Instantaneous Speed Estimation

This paper proposes a new sensorless vector control method for induction motors using a minimum dimensional flux D‐state observer with instantaneous speed estimation. First, the D‐state observer with a new design rule of constant observer gains is established in a different way. Second, a new speed estimator using flux estimates produced by the observer is established on the basis of the fundamental relationship between the rotor flux and the slip frequency. Speed estimates are reused in the observer as feedback. Characteristic analyses and the usefulness of the proposed vector control method are verified by simulations.     

Zircaloy-U02 and -Water Reactions and Cladding Temperature Estimation for Rapidly-Heated Fuel Rods under an RIA Condition

Zircaloy cladding chemical reactions with coolant water and UO₂ fuel at elevated temperatures under a reactivity initiated accident (RIA) condition were studied from a metallurgical point of view on the basis of the nuclear safety research reactor (NSRR) experiments. The cladding-fuel chemical reaction was extensively analyzed and found to be explainable from equilibrium phase diagrams. The systematic estimation methods of maximum cladding temperature were proposed and examined from metallographies. Maximum cladding temperature can be estimated from measured oxidation thicknesses in the temperature range of 1,000~1,600°C, from melting microstructures in the range of 1,600~1,950°C and also from the volume fraction of the precipitates, (U, Zr)0_2-x, in once-molten oxygen-stabilized α-zircaloy in 1,950~2,400°C. The estimation by the method proposed in the paper is more valid than thermocouple indications at high temperatures, since thermocouples perturb the temperatures they are measuring or fail at the extremely high temperatures. The results are thought to be applicable also to understand general fuel rod behavior under hypothetical accident conditions which cause severe fuel damage.     

Einfluss der Versuchsunterstützung auf die Abschätzungsgenauigkeit mittels künstlich neuronaler Netze

Suitable methods and transferability criteria and knowledge of the cyclic material behaviour is essential for a durable design of a component. For this reason, the cyclic material parameters are determined as a function of the product's properties (level of deformation, microstructure, surface finish, residual stresses) and different loading parameters. However, since the determination of the cyclic parameters is associated with considerable experimental effort and costs, a cost‐effective and easy method is sought to determine these parameters. A very promising approach for this is the application of artificial neural networks (ANN) since they have the ability to generate the influences on the fatigue strength from the manufacturing and environmental parameters using sensibly selected input parameters. They offer the possibility to access acquired knowledge and to thus construct a multidimensional map based on a few tests. By combining a few experimental tests with the ANN, the result of the estimation can be improved and the experimental effort can be reduced.     

Novel Transmitting Power Control Method without Signal Communication for Wireless Power Transfer via Magnetic Resonance Coupling

Wireless power transfer (WPT) via magnetic resonance coupling has been widely studied for vehicle applications, particularly the stationary and dynamic charging of electric vehicles. Our research group previously proposed a wireless in‐wheel motor to improve the reliability and safety of in‐wheel motors. Transmit power control is necessary to achieve stable WPT. We proposed a control method that uses a feedforward controller on the primary side and a feedback controller on the secondary side. However, the control method may cause shortfalls in the transmission power owing to modeling error, coupling coefficient variation, and signal communication delay. In this paper, we propose a novel feedback control method for the primary side based on conversion ratio estimation. The effectiveness of the proposed method was verified by simulations and experiments on the load current control of a constant voltage load and load voltage control of a constant power load.     

Probabilistic cost prediction for submarine power cable projects

It is estimated that Europe alone will need to add over 250,000 km of transmission capacity by 2050, if it is to meet renewable energy production goals while maintaining security of supply. Estimating the cost of new transmission infrastructure is difficult, but it is crucial to predict these costs as accurately as possible, given their importance to the energy transition. Transmission capacity expansion plans are often founded on optimistic projections of expansion costs. We present probabilistic predictive models of the cost of submarine power cables, which can be used by policymakers, industry, and academia to better approximate the true cost of transmission expansion plans. The models are both generalizable and well-specified for a variety of submarine applications, across a variety of regions. The best performing statistical learning model has slightly more predictive power than a simpler, linear econometric model. The specific decision context will determine whether the extra data gathering effort for the statistical learning model is worth the additional precision. A case study illustrates that incorporating the uncertainty associated with the cost prediction to calculate risk metrics - value-at-risk and conditional-value-at-risk - provides useful information to the decision-maker about cost variability and extremes.     

Modeling 3D heat flow interaction with defects in composite materials for infrared thermography

Estimation of defect depth and size is an important problem in the domain of Nondestructive Testing in order to perform corrective repairs. The problem of defect depth estimation using Infrared Thermography has been previously studied using 1D heat conduction models. Unfortunately, 1D heat conduction based models are generally inadequate in predicting heat flow around finite-sized defects, especially in composite structures. In this study, a novel approach based on 3D heat conduction is proposed to model the heat flow interaction with the defect in quasi-isotropic composite materials. The modeling process involved coordinate transformations to reduce the anisotropic heat conduction problem to the isotropic domain, followed by separation of variables to solve the partial differential equation of the heat conduction. The validity of the model is established using Pulsed Thermography experiments performed on a composite panel containing rectangular flat-bottom holes of different sizes, present at different depths.     

Analyzing the relationship between car generation and severity of motor-vehicle crashes in Denmark

While the number of fatalities on Danish roads has decreased in the last 40 years, research has not investigated the contribution of legislation changes, enforcement measures, technological enhancements, infrastructural improvements and human factors to this reduction. In the context of a Danish car market with remarkably high registration tax that causes potential buyers to hold longer onto old cars, the relationship between technological enhancements of vehicles and severity of crashes requires particular attention.     

An Estimation Method to Determine Equivalent Circuit Parameters for Harmonic Analysis

This paper proposes a new estimation method to determine arbitrary circuit parameters for the harmonic analysis of a distribution network. Harmonic analysis is important in maintaining electric power quality. An interesting phenomenon, a temporary cut‐down of the harmonic voltage level at dawn, even if demand is slightly increasing at this time, is often observed in actual power systems. This paper proposes to utilize observations of this phenomenon to estimate circuit parameters. In addition, it is claimed that a detailed equivalent circuit is preferable to a conventional simplified equivalent circuit for explaining the phenomenon. This paper also discusses the usefulness of the Harmonic Characteristics Curve, which is proposed in this paper as a new concept, at the secondary winding of the distribution transformer, and the correlation of PQ, the monitored values of the active and reactive power at the secondary winding of distribution transformer. This correlation should determine the equivalent fundamental frequency admittance of the shunt capacitors installed for distribution lines. © 2014 Wiley Periodicals, Inc. Electr Eng Jpn, 187(1): 16–23, 2014; Published online in Wiley Online Library ( wileyonlinelibrary.com ). DOI 10.1002/eej.22451     

Distance Estimation and Material Classification of a Compliant Tactile Sensor Using Vibration Modes and Support Vector Machine

Many animals possess actively movable tactile sensors in their heads, to explore the near-range space. During locomotion, an antenna is used in near range orientation, for example, in detecting, localizing, probing, and negotiating obstacles. A bionic tactile sensor used in the present work was inspired by the antenna of the stick insects. The sensor is able to detect an obstacle and its location in 3D (Three dimensional) space. The vibration signals are analyzed in the frequency domain using Fast Fourier Transform (FFT) to estimate the distances. Signal processing algorithms, Artificial Neural Network (ANN) and Support Vector Machine (SVM) are used for the analysis and prediction processes. These three prediction techniques are compared for both distance estimation and material classification processes. When estimating the distances, the accuracy of estimation is deteriorated towards the tip of the probe due to the change in the vibration modes. Since the vibration data within that region have high a variance, the accuracy in distance estimation and material classification are lower towards the tip. The change in vibration mode is mathematically analyzed and a solution is proposed to estimate the distance along the full range of the probe.