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Abstract When a lithium ion polymer battery (LiPB) is being cycled, one major cause for degradations is the irreversible side reactions between ions and solvent of electrolyte taking place at the surface of anode particles. SEM analysis of cycled battery cells has revealed that the deposits from the side reactions are dispersed not only on particles, but also between the composite anode and the separator. Thus, the solid electrolyte interface (SEI) becomes thicker and extra deposit layers are formed between composite anode and separator. Also, XPS analysis showed that the deposits are composed of Li 2 CO 3 , which is ionic conductive and electronic nonconductive. Based on the mechanisms and findings, we identified four degradation parameters, including volume fraction of accessible active anode, SEI resistance, resistance of deposit layer and diffusion coefficient of electrolyte, to describe capacity and power fade caused by the side reactions. These degradation parameters have been incorporated into an electrochemical thermal model that has been previously developed. The terminal voltage and capacity of the integrated model are compared with experimental data obtained for up to 300 cycles. Finally, the resistance of the deposit layer calculated by the model is validated against the thickness of the deposit layer measured by SEM.

Condition monitoring of power transformers is of great importance for the timely detection of incipient faults to avoid potential malfunctioning. Transformer insulating oil contains about 70% of diagnostic information, and a dramatic rise in oil temperature may drastically reduce the lifetime of power transformers, and thus the temperature of the oil is considered the most crucial parameter that has to be monitored continuously in real-time. Compared to traditional temperature measurement methods used in transformer condition monitoring, distributed optical fiber sensors have inherent advantages of immunity to electromagnetic interference and insulation at high-voltage levels, and they offer spatially resolved temperature monitoring with high accuracy and sensitivity. In this study, optical fiber-based distributed temperature measurement of a fully energized 100 kVA distribution transformer is demonstrated by using two different techniques: Optical Frequency Domain Reflectometry (OFDR) and Fiber Bragg Grating (FBG) sensor array. The fiber sensors are robust for a safe long-term installation into oil-filled distribution transformers during manufacturing, and they can withstand heat runs, long-term hot oil immersion, and transformer vibration. The internal transformer temperature is monitored during standard thermal tests prior to installation on the distribution system. The test results show very good agreement between the standard thermocouple and proposed distributed fiber temperature sensors, providing transformer manufacturers with new insights into the distribution of temperatures internal to their commercial products.

We consider planning and design of an extended supply chain for bioenergy networks (i.e., networks for multibiomass as well as biofuel logistics) in an integrated fashion while simultaneously addressing strategic and tactical decisions pertaining to location, production, inventory, and distribution in a multiperiod planning horizon setting. In our modeling, we also explicitly incorporate realistic operational parameters, including biomass deterioration rates and transportation economies of scale. For an efficient solution of our model, we suggest a Benders decomposition–based algorithm that can handle realistic size problems for design and analysis purposes. We implement the approach in a particular way using callback functions, in which the master problem is solved only once; we also develop surrogate constraints for enhanced lower bounds to obtain improved convergence especially for large instances. We provide computational results that demonstrate the efficiency of the solution approach on a wide-ranging set of problem instances. Furthermore, we develop a realistic case using data pertaining to the state of Texas and conduct an extensive analysis on the effects of varying input parameters on the design outcomes for a bioenergy supply chain network.

Abstract The dynamics of isolated-photon plus two-jet production in pp collisions at a centre-of-mass energy of 13 TeV are studied with the ATLAS detector at the LHC using a dataset corresponding to an integrated luminosity of 36.1 fb−1. Cross sections are measured as functions of a variety of observables, including angular correlations and invariant masses of the objects in the final state, γ + jet + jet. Measurements are also performed in phase-space regions enriched in each of the two underlying physical mechanisms, namely direct and fragmentation processes. The measurements cover the range of photon (jet) transverse momenta from 150 GeV (100 GeV) to 2 TeV. The tree-level plus parton-shower predictions from Sherpa and Pythia as well as the next-to-leading-order QCD predictions from Sherpa are compared with the measurements. The next-to-leading-order QCD predictions describe the data adequately in shape and normalisation except for regions of phase space such as those with high values of the invariant mass or rapidity separation of the two jets, where the predictions overestimate the data.