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AbstractIn this paper, a new model of transverse mixing in a rotating drum is derived from dynamic data collected from an experimental rig. Since the active layer has often been declared as the zone that is responsible for the mixing of solids in a rolling bed, the active layer was characterized so that its properties could be predicted for a wide range of experimental conditions. The mixing model consisted of two correlations, one to predict the mixing rate in the drum and the other to predict the final contact between the two materials. These correlations were linked back to the operational variables of the drum, such as the drumfs loading, size and rotational velocity. By combining these two correlations the time required to fully mix the material in the drum could be predicted. The mixing model was tested against independent data and good agreement was observed between the experimentally derived results and those predicted by the mixing model. Furthermore, this mixing model was designed such that it would be easily applicable to different sized drums. The extrapolation ability was tested on different smaller‐sized drums and found to agree considerably with experimental results.

Abstract The dissolution of carbon dioxide (CO 2 ) in deep saline aquifer water is recognized as one of the fundamental mechanisms in the subsurface for storing significant quantities of CO 2 . One fundamental physical effect of CO 2 dissolution is the slight increase in water density in the layer in contact with the buoyant free-phase CO 2 plume. Under specific conditions, this may lead to gravitational instability and the onset of free convection, significantly accelerating the dissolution of the free-phase CO 2 by bringing CO 2 in contact with a larger volume of aquifer water. It is also feasible to enhance CO 2 dissolution using engineering methodologies such as injecting water on top of the plume of CO 2 . The objective of this review is to provide a perspective on the progress in modeling and experimental observations of physical aspects of CO 2 dissolution in deep saline aquifers. We review the published research efforts concerning the physical effects of CO 2 dissolution in formation water, the conditions under which process can be accelerated either naturally, such as by free convection, or by use of engineering methodologies, and the effects of CO 2 dissolution on CO 2 storage. Finally, we discuss areas in need of further research.

Abstract Third zone of a distance relay is sensitive to system stressed conditions, such as stable and unstable power swing, voltage instability and load encroachment. Mal-operation of a distance relay under these conditions can cause power system blackout and should be prevented for power system security. An integrated approach based on two indices is introduced to improve the relay performance during system stressed conditions. The first index is based on estimated dc offset magnitude from the current signal using half cycle Discrete Fourier Transform and the second index is based on energy of first level detail coefficients obtained using discrete wavelet transform. It can be hard for a distance relay to discriminate between a three-phase fault in the third zone and stressed system events as both are balanced phenomena. Therefore, during the occurrence of a transient event if the conventional impedance calculation method detects it as a fault, it will be rightly detected as a three-phase fault only if both the indices lie above their respective thresholds. Using these two indices as a combined supervisory logic, three-phase fault in the third zone can be rapidly and reliably detected and discriminated from system stressed conditions, and thus avoid false operation of distance relay during stressed system conditions. Current based and wavelet techniques are, respectively, sensitive to noise and sampling frequency. However, with the proposition of adaptive threshold setting in the wavelet approach the robustness of this method against noise and sampling frequency is guaranteed. The proposed method is reliable during CT saturation condition as well. The proposed method is based on local end information so system condition can be rapidly scrutinized. Results for different power system events are analyzed using New England 39-bus, 10-machine test system modelled in EMTDC/PSCAD software. Comparative assessment with conventional approach confirms that this algorithm can meet the accuracy standards of the industrial relays due to better reliability.

The energy industry has been going through a significant modernization process over the last decade. Its infrastructure is being upgraded rapidly. The supply, demand and prices are becoming more volatile and less predictable than ever before. Even its business model is being challenged fundamentally. In this competitive and dynamic environment, many decision-making processes rely on probabilistic forecasts to quantify the uncertain future. Although most of the papers in the energy forecasting literature focus on point or single-valued forecasts, the research interest in probabilistic energy forecasting research has taken off rapidly in recent years. In this paper, we summarize the recent research progress on probabilistic energy forecasting. A major portion of the paper is devoted to introducing the Global Energy Forecasting Competition 2014 (GEFCom2014), a probabilistic energy forecasting competition with four tracks on load, price, wind and solar forecasting, which attracted 581 participants from 61 countries. We conclude the paper with 12 predictions for the next decade of energy forecasting.

AbstractAn active power filter (APF) is proposed which eliminates harmonics, compensates reactive power and neutral current in a three‐phase four‐wire electric system supplying non‐linear loads. An insulated‐gate‐bipolar‐transistor (IGBT)‐basedpulse‐width modulation (PWM) voltage source inverter (VSI) with a DC bus capacitor is employed as an APF. A hysteresis‐rule‐based carrierless PWM current control technique is used to generate switching signals to the devices of the APF. Three single‐phase diode rectifiers supplying resistive‐capacitive loads are considered as a three‐phase non‐linear load. A detailed dynamic model of the scheme is developed to study transient and steady‐state behaviour of the APF. The proposed APF is found capable to compensate reactive power, neutral currents and to reduce the harmonics below specific recommendations of IEEE‐519 standard.

Artificial neural networks can be used as intelligent controllers to control nonlinear, dynamic systems through learning, which can easily accommodate the nonlinearities and time dependencies. Taking advantage of the characteristics of a generalized neuron (GN), that requires much smaller training data and shorter training time, a GN-based adaptive power system stabilizer (GNAPSS) is proposed. It consists of a GN as an identifier, which predicts the plant dynamics one step ahead, and a GN as a controller to damp low frequency oscillations. Results of studies with a GN-based PSS on a five-machine power system show that it can provide good damping of both local and inter-area modes of oscillations over a wide operating range and significantly improve the dynamic performance of the system.

Gastric ulcer (GU) is the most common and chronic inflammatory condition mediated by multiple immune cells like neutrophils, macrophages, and lymphocytes with multiple pro-inflammatory cytokine interleukins such as IL-8, IL-10, IL-β, and interferon-γ (IFN-γ). Copper (Cu) is one of the essential micronutrients mainly found in the liver and brain. It plays a major role in metabolism, enzyme conversion, free radical scavenging, trafficking agents, and many others. Due to its various roles in the biological system, it can also be used as a therapeutic agent in many diseases like colon cancer, bone fracture healing, angiogenesis, as an antibacterial, wound-healing and radiotherapeutic agents. In this study, we used thiol-functionalized cellulose-conjugated copper-oxide nanoparticles (CuI/IIO NPs) synthesized under environmentally friendly conditions. We have evaluated the effects of cellulose-conjugated CuI/IIO NPs against ethanol-induced gastric ulcer in Wistar rats. The cellulose-conjugated CuI/IIO NPs were evaluated against different physical, histochemical, and inflammatory parameters. The NPs promoted mucosal healing by ameliorating ulcerative damage, restoring the histoarchitecture of gastric mucosa, and inhibiting pro-inflammatory cytokines such as tumor necrosis factor-α (TNF-α), interleukin-1 beta (IL-1β), and other inflammatory biomarkers such as myeloperoxidase (MPO) activity and nitric oxide (NO) levels. The current study's findings suggest that cellulose-conjugated CuI/IIO NPs exerted antiulcer effects on the preclinical rat model and have promising potential as a novel therapeutic agent for the treatment of gastric ulcers.

Abstract Artificial neural networks (ANN) can be used as intelligent controllers to control non-linear, dynamic systems through learning, which can easily accommodate the nonlinearities and time dependencies. However, they require large training time and large number of neurons to deal with complex problems, Taking benefit of the characteristics of a Generalized Neuron (GN), that requires much smaller training data and shorter training time, a generalized neuron based PSS (GNPSS) and adaptive PSS (GNAPSS) are developed and compared.