Abstract Combined Sewer Overflows (CSOs) are a major source of pollution and urban flooding, spilling untreated wastewater directly into water bodies and the surrounding environment. If overflows can be predicted sufficiently in advance, then techniques are available for mitigation. This paper presents a novel bi-model committee evolutionary artificial neural network (CEANN) designed to forecast water level in a CSO chamber from 15 min to 6 h ahead using inputs of past/current CSO level data, radar rainfall data and forecast forecasted rainfall data. The model is composed of two evolutionary artificial neural network (EANN) models. The two models are trained and optimised for wet and dry weather conditions respectively and their results combined into a single response using a non-linear weighted averaging approach. An evolutionary strategy algorithm is employed to automatically select the optimal artificial neural network (ANN) structure and parameter set, allowing the network to be tailored specifically for different CSO locations and forecast horizons without significant human input. The CEANN model was tested and evaluated on real level data from 4 CSOs located in Northern England and the results compared to three other ANN models. The results demonstrate that the CEANN model is superior in terms of accuracy for almost all forecast horizons considered. It is able to accurately forecast the dry weather and wet weather level, predicting the timing and magnitude of upcoming spill events, thus providing information that is of clear use to a wastewater utility.

Abstract Conventional physics-based or experimental-based approaches for gas turbine combustion tuning are time consuming and cost intensive. Recent advances in data analytics provide an alternative method. In this paper, we present a cross-disciplinary study on the combustion tuning of an F-class gas turbine that combines machine learning with physics understanding. An artificial-neural-network-based (ANN) model is developed to predict the combustion performance (outputs), including NOx emissions, combustion dynamics, combustor vibrational acceleration, and turbine exhaust temperature. The inputs of the ANN model are identified by analyzing the key operating variables that impact the combustion performance, such as the pilot and the premixed fuel flow, and the inlet guide vane angle. The ANN model is trained by field data from an F-class gas turbine power plant. The trained model is able to describe the combustion performance at an acceptable accuracy in a wide range of operating conditions. In combination with the genetic algorithm, the model is applied to optimize the combustion performance of the gas turbine. Results demonstrate that the data-driven method offers a promising alternative for combustion tuning at a low cost and fast turn-around.

Abstract This paper investigates the near-resonance response to exogenous excitation of a class of networks of coupled linear and nonlinear oscillators with emphasis on the dependence on network topology, distribution of nonlinearities, and damping ratios. The analysis shows a qualitative transition between the behaviors associated with the extreme cases of all linear and all nonlinear oscillators, respectively, even allowing for such a transition under continuous variations in the damping ratios but for fixed topology. Theoretical predictions for arbitrary members of the network class using the multiple-scales perturbation method are validated against numerical results obtained using parameter continuation techniques. The latter include the tracking of families of quasi-periodic invariant tori emanating from saddle-node and Hopf bifurcations of periodic orbits. In networks in the class of interest with special topology, 1:1 and 1:3 internal resonances couple modes of oscillation, and the conditions to suppress the influence of these resonances are explored.

Abstract Land-based power units have to fulfill even more high levels of production and reliability. In harsh environments (desert and tropical installations, typically), the power unit ingests high amounts of dust that might deposit inside the compressor. In this paper, the analysis of a multistage compressor performance that operates under sandy and humid conditions has been assessed. The compressor units, which equips the Allison 250 C18 compressor, has been subjected to multiple runs under severe conditions of soil dust ingestion. The compressor has been operated according to subsequent runs, and at the end of each run, the performance curve was recorded; the performance losses, in terms of pressure ratio, have been measured during the operations. The characteristic curve of each run is representative of the level of contamination of the unit. Finally, the compressor has been washed, and the performance curve, in the recovered conditions, has been recorded. The results show the modification and the downward shift of the characteristic curves which lead to a gradual loss of the compressor performance. The curves realized after dust ingestion have been compared with the recovered curve after online washing. The measurement shows a promising recovery of the performances, even if the compressor flow path appears affected by localized deposits able to resist to the droplet removal action. Detailed photographic reports of the inlet guide vane (IGV) and the first compressor stages have been included in this analysis. After each run, the IGV, the rotor blade and stator vane of the first stage, and the hub and the shroud surfaces have been photographed. The pictures show the deposition patterns on the blades and the compressor surfaces. The comparison of the pictures of the internal surfaces, before and after the washing, highlights the parts that are more critical to clean and needy of attention during offline washing and overhaul.

Abstract While turbocharging is a key technology for improving the performance and efficiency of internal combustion engines, the operating behavior of the turbocharger is highly dependent on the rotor temperature distribution as it directly modifies viscosity and clearances of the fluid film bearings. Since a direct experimental identification of the rotor temperature of an automotive turbocharger is not feasible at an acceptable expense, a combination of numerical analysis and experimental identification is applied to investigate its temperature characteristic and level. On the one hand, a numerical conjugate heat transfer (CHT) model of the automotive turbocharger investigated is developed using a commercial CFD-tool and a bidirectional, thermal coupling of the CFD-model with thermohydrodynamic lubrication simulation codes is implemented. On the other hand, experimental investigations of the numerically modeled turbocharger are conducted on a hot gas turbocharger test rig for selected operating points. Here, rotor speeds range from 64.000 to 168.000 rpm. The turbine inlet temperature is set to 600 °C and the lubricant is supplied at a pressure of 300 kPa with 90 °C to ensure practically relevant boundary conditions. Comparisons of measured and numerically predicted local temperatures of the turbocharger components indicate a good agreement between the analyses. The calorimetrically determined frictional power loss of the bearings as well as the floating ring speed are used as additional validation parameters. Evaluation of heat flow of diabatic simulations indicates a high sensitivity of local temperatures to rotor speed and load. A cooling effect of the fluid film bearings is present. Consequently, results confirm the necessity of the diabatic approach to the heat flow analysis of turbocharger rotors.

Abstract In order to increase the exploitation of the renewable energy sources, the diffusion of the distributed generation systems is grown, leading to an increase in the complexity of the electrical, thermal, cooling, and fuel energy distribution networks. With the main purpose of improving the overall energy conversion efficiency and reducing the greenhouse gas emissions associated with fossil fuel based production systems, the design and the management of these complex energy grids play a key role. In this context, an in-house developed software, called COMBO, presented and validated in Part I of this study, has been applied to a case study in order to define the optimal scheduling of each generation system connected to a complex energy network. The software is based on a nonheuristic technique, which considers all the possible combination of solutions, elaborating the optimal scheduling for each energy system by minimizing an objective function based on the evaluation of the total energy production cost and energy systems' environmental impact. In particular, the software COMBO is applied to a case study represented by an existing small-scale complex energy network, with the main objective of optimizing the energy production mix and the complex energy networks yearly operation depending on the energy demand of the users. The electrical, thermal, and cooling needs of the users are satisfied with a centralized energy production, by means of internal combustion engines, natural gas boilers, heat pumps, compression, and absorption chillers. The optimal energy systems' operation evaluated by the software COMBO will be compared to a reference case, representative of the current energy systems setup, in order to highlight the environmental and economic benefits achievable with the proposed strategy.

Abstract Closed Joule–Brayton cycles operating with carbon dioxide in supercritical conditions (sCO2) are nowadays collecting a significant scientific interest, due to their high potential efficiency, the compactness of their components, and the flexibility that makes them suitable to exploit diverse energy sources. However, the technical implementation of sCO2 power systems introduces new challenges related to the design and operation of the components. The compressor, in particular, operates in a thermodynamic condition close to the critical point, whereby the fluid exhibits significant non-ideal gas effects and is prone to phase change in the intake region of the machine. These new challenges require novel design concepts and strategies, as well as proper tools to achieve reliable predictions. In this study, we consider an exemplary sCO2 power cycle with the main compressor operating in proximity to the critical point, with an intake entropy level of the fluid lower than the critical value. In this condition, the phase change occurs as evaporation/flashing, thus resembling cavitation phenomena observed in liquid pumps, even though with specific issues associated with compressibility effects occurring in both the phases. The flow configuration is therefore highly nonconventional and demands the development of proper tools for fluid and flow modeling, which are instrumental for the compressor design. The paper discusses the modeling issues from the thermodynamic perspective, then highlighting their implications on compressor aerodynamics. We propose tailored models to account for the effect of the phase change in 0D mean-line design tools as well as in fully three-dimensional (3D) computational fluid-dynamic (CFD) simulations: the former was previously validated for sCO2 compressors, the latter is validated in this paper against experiments of compressible flows of supercritical sCO2 in nozzles. In this way, a strategy of investigation is built-up as a combination of mean-line tools, industrial design experience, and CFD for detailed flow analysis. The investigation reveals that the potential onset of the phase change might alter significantly the performance and operation of the compressor, both in design and in off-design conditions, according to three main mechanisms: incidence effect, front-loading, and channel blockage.

Nowadays a mobile computing and multimedia applications are need for high-performance reduced size and low-power devices. The multiplication is major operation in any signal processing applications. In any multiplier architecture, adder is one of the major processing elements. In which XOR is the basic block of an adder and multiplier. In this paper, a various design styles of XOR Gate have been surveyed and simulated using Microwind tool. In that XOR gate was analyzed the power using the different styles. They are conventional XOR gate, Pass transistor logic based EX-OR gate, Static inverter based EX-OR gate, Transmission Gate based EX-OR Gate, EX-OR Gate based on 8 & 6 Transistor & and Modified version of EX-OR Gate The CMOS circuit layout was created and simulated in Microwind software. In that the proposed XOR-based circuit has 40.17% of power consumption has improved &14.28 % of area in-terms of number of transistor improved as compare to modified version of EX-OR Gate design.