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The homogenization design method has been expanded to obtain the optimal topology of a structure in magnetic fields to maximize the magnetic energy. In this study, the homogenization design method (HDM) is applied to a structure in magnetic fields to reduce the vibration level of a structure excited by the magnetic forces, especially by the magnetic harmonic forces. This is accomplished by obtaining the optimal material distribution of the structure to minimize the frequency response. The Maxwell stress method is used to compute the magnetic force and the HDM is applied for the optimization. It is verified that the HDM is useful to minimize the frequency response by some actual applications. The effects of mesh density of the design domain and the rotor-stator position are also examined.

In het kort meetresultaten van de vergisting van Beukergist tezamen met varkensmest en van de vergisting van aardappelzetmeel met varkensmest in de biogasinstallatie van Praktijkcentrum Sterksel. Beukergist ontstaat bij de winning van alcohol uit vloeibaar tarwezetmeel en werd geleverd door Beuker Vochtrijke Diervoeders; primair aardappelzetmeel is ingedikt snijzetmeel uit proceswater, dat ontstaat bij de verwerking van aardappelen tot frites.

Abstract An important objective of the Optimal Power Flow (OPF) problem is to minimize the generation cost and keep the power outputs of generators, bus voltages, bus shunt reactors/capacitors and transformer tap settings in their secure limits. Solving this OPF problem using classical methods suffer from the disadvantages of highly limited capability to solve the practical large scale power system problems. To overcome the inherent limitations of conventional optimization techniques, Swarm Intelligence (SI) methods have been developed. However, the environmental concern, dictate the minimization of emissions of the thermal plants. Individually, if one objective is optimized, other objective is compromised. Hence, Multi-Objective Optimal Power Flow (MO-OPF) problem has been formulated in this paper. Swarm Intelligence methods, such as Particle Swarm Optimization (PSO) and Glowworm Swarm Optimization (GSO) have been used to solve the OPF problem with generation cost and emission minimizations as objective functions. The effectiveness of the proposed algorithms are tested on IEEE 30 bus and practical Indian 75 bus systems for cost minimization as objective function, and IEEE 30 bus test system for minimization of cost and emission as objectives. The results obtained from both the networks, the PSO and GSO are compared with each other based on different parameters.

In many-body physics, renormalization techniques are used to extract aspects of a statistical or quantum state that are relevant at large scale, or for low energy experiments. Recent works have proposed that these features can be formally identified as those perturbations of the states whose distinguishability most resist coarse-graining. Here, we examine whether this same strategy can be used to identify important features of an unlabeled dataset. This approach indeed results in a technique very similar to kernel PCA (principal component analysis), but with a kernel function that is automatically adapted to the data, or “learned”. We test this approach on handwritten digits, and find that the most relevant features are significantly better for classification than those obtained from a simple Gaussian kernel.

The meshed network may become a standard for future distribution systems owing to its various benefits regarding voltage profile, reliability, losses, and the distributed generation (DG). Therefore, in Korea, there is a plan to introduce an advanced form of meshed network called a networked distribution system (NDS). This refers to a system with permanent linkages between four distribution lines (DLs) and N×N communication-based protection. To properly introduce NDS to an actual grid, this study proposes a strategy for optimal grid planning and system evaluation. Four different topologies and four practical indicators are explained. First, load imbalance is used to find the optimal grid that maximizes the load capacity. Second, line overload, fault current, and temporary overvoltage (TOV) were used to evaluate the necessity of load transfer, availability of circuit breakers, relay settings, and system stability. PSCAD/EMTDC were employed for the simulation. This study establishes the construction and evaluation guidelines of NDS for distribution system operators (DSOs).

We consider energy efficient base station (BS) sleeping and clustering problems in cooperative cellular networks, where clusters of base stations jointly transmit to users. Our key idea of energy saving is to exploit spatio-temporal fluctuation of traffic demand, and use minimal energy to provide achievable data rate only slightly greater than varying traffic demand. However, it is highly challenging to design traffic-aware algorithms without the future traffic demand information. To overcome this difficulty, we develop joint BS sleeping and clustering algorithms using queue instead of the future traffic information. The queue length information captures spatio-temporal mismatch between traffic demand and offered data rate. For BS clustering problem, we propose an optimal algorithm under given BS sleep mode state that has polynomial complexity. We integrate the optimal clustering solution into the sleeping problem, which is a complex combinatorial problem, and develop a joint optimal clustering and sleeping algorithm with reduced complexity compared to the exhaustive search. We also develop a greedy algorithm that finds a near-optimal clustering and sleeping solution with polynomial complexity. Through extensive simulations, we show that the proposed algorithms can save significant energy when traffic load is low.

Electrochemical CO2 reduction (ECO2R) is considered as one of the economically viable means to convert CO2 into useful products, for achieving carbon neutrality in the future. Many studies have been conducted on developing and evaluating electrochemical cells that provide high energy efficiency and conversion of CO2 for CO production via ECO2R. However, commercially feasible technologies are yet to be developed and demonstrated due to various technical limitations as well as the lack of a systematic evaluation framework. In this study, CO production performance is examined by catholyte-free electrochemical CO2 reduction (CF-ECO2R), which eliminates a large ohmic drop by removing the catholyte compartment, thus lowering the energy requirement. The CF-ECO2R shows 0.6 V lower cell voltage and 17.4% higher electrical energy conversion efficiency than a typical GDE-catholyte method using 1 M KOH as the catholyte at a current density of 240 mA cm−2. The obtained results are used to demonstrate its technical feasibility and to provide basic data for the evaluation of a scale-up process. A mathematical model is developed based on the obtained experimental data and the model is simulated along with three different options of downstream separation to provide basic mass and energy balance data. Then, techno-economic and CO2 life cycle analyses are conducted to suggest the best configuration of the overall CO production system in terms of the economics and net CO2 reduction. It is estimated that the best configuration provides a reduction in CO2 emission by 48% compared to the conventional CO production via steam methane reforming. This configuration is also assessed to be economically feasible, giving a production cost (584 USD per ton CO) that is competitive with the current market price of CO. It is also demonstrated that the operating voltage of the CF-ECO2R and regional influences such as CO2 emission intensity and cost of the mixed electricity strongly affect the cost and CO2 emission of the system.

This study investigates the effect of reaction temperature (298–353 K) on photocatalytic H2 production in bare and platinized TiO2 (Pt/TiO2) suspensions containing various organic hole scavengers (EDTA, methanol, and formic acid) under UV (λ > 320 nm) and visible light (λ > 420 nm for ligand-to-metal charge transfer). H2 production rates are enhanced ∼7.8- and ∼2.5-fold in TiO2 and Pt/TiO2 suspensions, respectively, with EDTA under UV by simply elevating the reaction temperature from 298 K to 323 K (ΔT = 25 °C). Such a temperature-boosted increase in H2 production is always observed, regardless of the TiO2 crystalline structure (anatase, rutile, and an anatase/rutile mixture), type of hole scavenger, and irradiation wavelength range. It is estimated that approximately 90% of incident photons are utilized in H2 production, for which the activation energy is 25.5 kJ mol−1. Detailed photoelectrochemical analyses show the positive relationship between reaction temperature and photocurrent generation, with charge carrier mobility and interfacial charge transfer improving at higher temperatures. Other possible factors, such as H2 solubility and mass transport, play a limited role.

We examined the relationship between management characteristics and corporate social responsibility (CSR) and this relationship was differentiated by the level of corporate governance. Our analysis was undertaken in firms listed on the Korean Stock Exchange (KSE) from 2006 to 2015. We employed Ordinary Least Square (OLS) regression after clustering the standard errors at the firm level in order to examine these relationships. The KEJI (Korea Economic Justice Institute) index was used as a proxy for CSR and a big data-based proxy estimated from multimedia was used as the level of advertising. We showed that there is a positive relationship between overconfident management and CSR activities. We then categorized the CSR activities as primary and social activities and found that overconfident management is more aggressive in primary CSR activities. In addition, overconfident management makes fewer CSR expenditures when the management is in a chaebol firm but promotes more CSR advertisement. This finding indicates that chaebol affiliation controls overinvestment in CSR activities but promotes CSR advertisements by overconfident managers. Similarly, we found consistent results with overconfident owner-managers. Prior literature on CSR activities focuses on the impact of CSR activities on firm performance. In this paper, we elucidated the determinants of CSR activities, so that this research contributes to firms&rsquo decision-making about sustainable management. Our estimation of CSR variables with big data approaches will also guide future research on this issue. We expect our study to be used as a reference for decision-making by relevant authorities and stakeholders.