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Abstract This paper presents a novel multi-time-stage input–output-based modeling framework for simulating the dynamics of bioenergy supply chains. One of the key assumptions used in the model is that the production level at the next time-stage of each segment of the energy supply chain adjusts to the output surplus or deficit relative to targets at the current time period. Furthermore, unlike conventional input–output models, the technology matrix in this approach need not be square, and thus can include coefficients denoting flows of environmental goods, such as natural resources or pollutants. Introducing a feedback control term enables the system to regulate the dynamics, thus extending the model further. This is an important feature since the uncontrolled dynamic model exhibits oscillatory or unstable behavior under some conditions; in principle, the control term allows such undesirable characteristics to be suppressed. Numerical simulations of a simple, two-sector case study are given to illustrate dynamic behavior under different scenarios. Although the case study uses only a hypothetical system, preliminary comparisons are made between the simulation results and some broad trends seen in real bioenergy systems. Finally, some of the main policy implications of the model are discussed based on the general dynamic characteristics seen in the case study. In particular, insights from control theory can be used to develop policy interventions to impart desirable dynamic characteristics to nascent or emerging biofuel supply chains. These interventions can be used to guide the growth of bioenergy supplies along final demand trajectories with minimal fluctuation and no instability.

Conventionally assessing of turbine performance was done by conducting model experiments which at times become costly and time consuming for several design alternatives in design optimization. Recently, computational fluid dynamics (CFD) has become a more cost effective tool for predicting detailed flow information in turbine space to enable the selection of the best design. With the growth of computational mechanics, the virtual hydraulic machines are becoming more and more realistic to get minor details of the flow, which are not possible in model testing. The inverse design technique and fully 3-dimensional flow simulations were performed early to manufacture the newly developed runner. It allows a quick and efficient improvement and optimization of turbine components. The system has been applied to the optimization of a Francis turbine runner for a turbine replacement project. In present work, 3D turbulent real flow analyses in hydraulic Francis turbine have been carried out at four guide vane opening at constant rotational speed using Ansys CFX computational fluid dynamics (CFD) software. The newly developed runner from reverse engineering and CFD results show an enhanced performance. The average values of flow parameters like velocities and flow angles at the inlet and outlet of runner, guide vane and stay vane of turbine are computed to derive flow characteristics. The aim was to analyze the flow behavior and pressure distribution to further fine-tune the whole numerical experiment to achieve the level of accuracy necessary for the concept design of a revitalized turbine. The obtained results are in good agreement with the in site experiments, especially for the characteristic curve.

Abstract In this communication, a mathematical model is presented to predict the thermal performance of a spherical solar still. The analysis is based on the heat and mass transfer relationships by Dunkle (1961) which have been modified empirically so as to validate the experimental results of Menguy et al. (1980). Numerical calculations have also been made to study the effect of the absorptivity of the basin liner on the distillate yield of the still

Nowadays, a large part of energy is provided by steam turbines; thus, increasing the efficiency and improving the steam turbines performance are of special importance. The presence of the liquid phase in the low-pressure stage of the steam turbine can cause energy loss, efficiency drop, and erosion/corrosion problems; therefore, one of the essential issues is to identify wet steam flow and try to reduce condensation loss. In order to decrease the liquid fraction, the drainage groove technique can be applied. The drainage groove sucks the water droplets from the turbine blade surface and drains them into the condenser. In this study, the effect of the drainage groove location on the surface of steam turbine blades has been investigated on the condensation, droplet radius, inlet mass flow, erosion rate, liquid drainage ratio, condensation losses, and total drainage ratio. For modeling the condensing flow, the Eulerian–Eulerian approach has been applied. The results show that the location of the drainage groove affects the groove performance and flow pattern in the turbine blade. In the selected drainage, the liquid drainage ratio, condensation losses, and erosion rate are reduced by 7.6%, 12%, and 88%, respectively, compared with the no-drainage groove case. Also, the total drainage ratio is 7.2% in the selected drainage. The outcomes of the present work have been a major step forward in the techniques having a great influence on the lifetime, repair and maintenance, and the output power of steam power generation facilities.

A new concept, called synchronized Lissajous curve , is proposed to study synchro-waveform measurements that are obtained from waveform measurement units (WMUs) in power distribution systems. Two types of synchronized Lissajous curves are discussed. The first one is created by plotting the difference of two synchronized voltage waveforms versus the difference of two synchronized current waveforms. The second one is created by plotting the difference of two synchronized voltage waveforms versus the difference of the derivatives of two synchronized current waveforms. These two curves carry valuable and complementary information about the state of the power system and the root cause of events and disturbances. We characterize the area , rotational angle , and shape of the introduced synchronized Lissajous curves to study events and disturbances in power distribution feeders.

The use of deep UV resist hardening for high temperature resist-masked processes is becoming more widespread throughout the semiconductor industry. In this report we present data on the wavelength and thermal dependence of the deep UV crosslinking process in novolak resin obtained through dissolution studies and SEM micrographs. An excimer laser was used to provide light of differing wavelengths. The results indicate that longer wavelengths near 308 nm promote crosslinking throughout the 1.5 micron thick resin, while shorter wavelengths induce crosslinking to limited depths. Heating of the wafer during the deep UV exposure is shown to greatly accelerate the crosslinking process, compared to a sequential expose and bake process. SEM micrographs of various stages of hardening in resist are shown. The resist hardening process employed by one commercial system is discussed in terms of the findings of this study.

Electricity price forecasting is critical to numerous tasks in the power system such as strategic bidding, generation scheduling, optimal scheduling of storage reserves and system analysis. Most existing price forecasting models focus on hourly prediction for the day ahead market. This work focuses on the real-time, 5-minute market, with the goal of developing a model able to capture both the long- and short-term temporal distribution of the data. Extending the recent advances in deep learning models of time series forecasting, the proposed model - named HFnet - is a novel multi-branch Gated Recurrent Unit (GRU) architecture for electricity price forecasting. Extensive empirical analyses using real-time data from the New York Independent System Operator (NYISO) illustrate the value of the proposed model when compared to state-of-art prediction models, with an average reduction in error of 10%.

Abstract A novel multi-scale domain overlapping coupling methodology designed to couple a computational fluid dynamics (CFD) code with a system thermal hydraulic (STH) code was developed and its performance was investigated. The methodology has been implemented in the coupling infrastructure code Janus, developed at the University of Michigan, providing methods for the on-the-fly data transfer through memory between the commercial CFD code STAR-CCM+ and the US NRC best-estimate thermal hydraulic system code TRACE. Coupling between these two software packages is motivated by the desire to extend the range of applicability of TRACE to scenarios in which local momentum and energy transfer are important, such as three-dimensional mixing of localized slugs of deborated or cold water in the downcomer and lower plenum of a reactor pressure vessel. The intra-fluid shear forces necessary to correctly capture these effects are neglected in the TRACE equations of motion, but are readily calculated from CFD solutions. CFD/STH coupling implementations therefore have applications in reactor transients such as boron dilution scenarios, Anticipated Transient Without SCRAM (ATWS) and Main Steam Line Break (MSLB). The proposed method is based on aliasing all spatial sources and sinks of momentum in the CFD domain as frictional losses in the system code domain. The internal velocity fields and, consequently, the inertial component of the pressure field are maintained consistent between the CFD and STH domains through a complementary velocity-matching interface. In this paper, coupled simulations are performed on Cartesian and cylindrical geometry with emphasis on consistency, convergence, and stability during transient scenarios. Results show that the presented domain overlapping coupling method is capable of adjusting pressure and velocity profiles of multi-dimensional system code solutions to match CFD solutions accurately. Important characteristics of transient simulations were found to include the background flow rate, specifically the stabilizing effect of viscous forces, as well as the time derivative of the flow rate. Under certain adverse conditions, the basic coupling method is found to produce unstable behavior. A stabilization method for adjusting CFD data is laid out and found to significantly improve the method’s performance under the most challenging conditions. Recommendations are laid out for further improving the coupling via advanced time stepping methods.