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AbstractIn this paper a complete vehicle system simulation tool chain which applies a Multi Objective Optimization (MOO) methodology for designing the Electric Powertrain (ePT) of Battery Electric Vehicles (BEV) is presented. Optimization scope includes all relevant electric powertrain components from battery, inverter, electric machine to gear box. In addition to cost, vehicle dynamics, energy consumption and range are further optimization targets. For an overall minimal system cost design a multiplicity of interactions between all powertrain components has to be taken into account. High system complexity prevents an expert to consider all relevant correlations without the support of numeric simulation tools. The presented simulation tool chain enables fast identification of the best cost/benefit trade off regarding system cost while considering all defined system performance requirements. The approach enables experts to find unconventional solutions which would have been overlooked applying a classical straight forward approach and, thus, helps to sharpen the expert's knowledge in cause-effect relationships on the system level. Typical use cases are given and illustrated by several practical examples.

Recent laboratory studies of droplet combustion indicate the potential for substantial gas phase particulate formation even with single component hydrocarbon fuels. Formation of large particles has been observed in the neighborhood of burning droplet arrays, particularly when the droplets are closely spaced. To provide insight into the potential for particulate formation during the combustion of fuel droplet sprays in gas turbine combustors, a mathematical framework is developed for examining the formation of soot nuclei in droplet combustion. A simplified model of the chemistry of fuel pyrolysis and nuclei formation is used and a series of calculations is made to explore the sensitivity of soot nuclei formation to conditions typical of gas turbine combustion systems.

In this paper, a numerical method coupling moment method with circuit theory is used to analyze the influence of the grounding material's property on the performance of grounding grids. It can be seen that for a large grounding grid, when the soil resistivity is small, the influence of both resistivity and permeability of grounding material on the performance of grounding grids is great. If the frequency is not very high, the grounding material's resistivity can affect the performance of the grounding grid obviously. If the frequency is very low or very high, the effect of the grounding material's permeability on the performance of the grounding grid is small, while the effect is obvious at other frequency.

Interest in the highly efficient energy hub (EH) model has been growing despite the high computational requirements of planning for a multi-energy, multi-device operation. To address both the device size limitation and the multi-scenario issue, we propose a new solution methodology for solving the EH planning problem. In the method, the decision variables are device sizes. First, a dimension reduction technique is proposed to address the curse of dimensionality based on the correlation of unknown variables such as the capacities of different devices in an EH. Second, to avoid local convergence, a solution method called the variable-sized unimodal searching (VUS) approach is proposed to assure a global optimal planning scheme for the one-dimensional non-convex optimization model obtained from the preceding dimension reduction process. The case study indicates that the proposed approach has a higher computing efficiency than the Benders decomposition (BD) algorithm to deal with a scenario-based stochastic planning problem with a large number of scenarios. Thus, the effectiveness of the EH planning approach is verified.

Abstract This study sought to quantify and characterize cassava waste as fuel. The wastes from three cultivars were collected to study and were divided into three distinct parts of the cassava plant: seed stem, thick stalks, and thin stalks. Physical and chemical analyzes were carried out to determine the elemental composition of the waste: volatile matter; fixed carbon; ash; moisture; lignin; cellulose; hemicellulose; ash composition and higher heating value were determined. We conducted a thermogravimetric analysis in oxidizing and inert atmospheres to study the behavior of the waste as fuel. The root productivity obtained ranged from 7.7 to 13.0 t ha−1 yr−1 on a dry basis (db), and the ratio between waste and roots varied from 0.36 to 0.91. The physical and chemical properties of cassava waste are analogous to those of woody biomass regarding the elemental composition, the higher heating value, and thermogravimetric analysis. Ash content varied from 2.5% to 3.5%, reaching around 6.0% in samples unwashed. Approximately 60% of the ashes are alkali oxides, especially P2O5, K2O, and CaO, which have low melting points. The alkali index calculated suggests that there is a strong tendency that the combustion process leads to ash fouling and the formation of ash deposits.

Abstract Concerns about power quality (PQ) in distribution networks have necessitated the use of PQ measuring/monitoring equipment to detect and analyse PQ problems. As the installation of such equipment at all locations is not economically feasible, minimum number and optimum locations of PQ monitors have been sought in recent researches to meet both economical efficiency and monitoring capability. Focusing on voltage sags, this paper attempts to further reduce the number of PQ monitors obtained by optimum allocation approaches while keeping the desired monitoring capability. Growing number of electric equipment with high sensitivity to voltage sags have raised more concerns about financial losses associated with voltage sags in comparison to other PQ problems. Here, a neural estimator placed at a monitored location is proposed to estimate instantaneous voltage-sag waveforms of a non-monitored sensitive load using local measurements. Echo state network (ESN) is used as the voltage-sag waveform estimator (VSWE). Because of increasing penetration of distributed generations (DGs) and their impacts on voltage-sag performance, they are considered to challenge the estimation task. The proposed ESN-based VSWE is examined on the IEEE 37-bus network. Tests for extensive unseen cases with different fault resistances, fault inception-angles, fault locations and fault types under different load demands and network conditions show acceptable high accuracy of estimations during fault and fault clearing sequences. Furthermore, the performance of the VSWE is investigated during transients due to switching capacitors, DGs, loads and lines.

Abstract The integrity of PWR pressure vessels is assured by keeping the crack tip stress intensity factor below the toughness of the material under monotonic isothermal loading. To study the effects of sudden cooling associated with a thermal gradient, a specially modified compact specimen has been developed. This has been used to carry out tests in the transition zone with different loading-temperature sequences liable to call the conventional criteria into question. The test is described in detail in Part I of this article [Chapuliot S, et al. Thermomechanical analysis of thermal shock fracture in the brittle/ductile transition zone. Part I: Description of the tests. Engng Fract Mech, 72, 2005, 661–73]. The second part describes numerical investigations to estimate the local mechanical fields at the crack tip and the overall parameters of the fracture mechanics. Finite element thermomechanical calculations are used to interpret the results of these new thermal shock tests using the master curve concept [ASTM E 1921–1997. Standard test method for determination of reference temperature To for ferritic steels in the transition range, 1997] and the Beremin statistical model [Beremin FM. A local criterion for cleavage fracture of a nuclear pressure vessel steel. Metall Trans A, 14A, November 1983, 2287–777].

Abstract Microorganisms used in syngas fermentation require nutrients to grow and convert syngas (CO, H2 and CO2) into various products. Many of the essential nutrients can be provided by biochar. Poultry litter biochar (PLBC) contains minerals and trace metals and has a high pH buffering capacity, making it suitable as a nutrient supplement. The effects of PLBC loadings from 1 to 20 g L−1 on syngas fermentation were determined in 250 ml bottle assays. Results showed that 10 and 20 g L−1 PLBC significantly increased ethanol production compared to standard yeast extract (YE) medium. Fermentations in a 3L continuous stirred tank reactor (CSTR) with 10 g L−1 PLBC with and without 4-morpholineethanesulfonic acid (MES) showed 64% and 36% more ethanol production, respectively, than standard medium. The acetic acid accumulated at the beginning of fermentation was completely converted to ethanol in all media tested in the CSTR. These results demonstrate the feasibility of using PLBC medium without costly MES in the CSTR to enhance ethanol production from syngas for potential use at commercial scale.