Self-fluxing coatings for stationary gas turbines

Self-fluxing alloys are becoming more and more interesting for hardware applications in stationary gas turbines. This is due to their ease of application which involves plasma spraying and sintering. These coatings are basically Cr₂O₃ formers which provide protection against sulphidation.As a result of the demand for greater efficiency in gas turbines and the consequent increase in operating temperature oxidation has become the basic form of corrosion attack and therefore oxides other than Cr₂O₃, i.e.Al₂O₃, are required.In this paper we shall describe an attempt that was made to modify a self-fluxing alloy (Ni-Cr-Fe-Si-B) with aluminium in order to produce protective Al₂O₃ scales. The coating is applied using air plasma spraying. The variation in the sinter temperature and the oxidation and corrosion resistance properties due to aluminium are given. The effect of aluminium on the tensile properties is illustrated using data from a ductile-brittle transition temperature test.     

Deterministic global optimization approach to steady-state distribution gas pipeline networks

Natural gas is normally transported through a vast network of pipelines. A pipeline network is generally established either to transmit gas at high pressure from coastal supplies to regional demand points (transmission network) or to distribute gas to consumers at low pressure from the regional demand points (distribution network). In this study, the distribution network is considered. The distribution network differs from the transmission one in a number of ways. Pipes involved in a distribution network are often much smaller and the network is simpler, having no valves, compressors or nozzles. In this paper, we propose the problem of minimizing the cost of pipelines incurred by driving the gas in a distribute non-linear network under steady-state assumptions. In particular, the decision variables include the length of the pipes’ diameter, pressure drops at each node of the network, and mass flow rate at each pipeline leg. We establish a mathematical optimization model of this problem, and then present a global approach, which is based on the GOP primal-relaxed dual decomposition method presented by Visweswaran and Floudas (Global optimization in engineering design. Kluwer book series in nonconvex optimization and its applications. Kluwer, Netherlands, 1996), to the optimization model. Finally, results from application of the approach to data from gas company are presented.     

Transformed Gaussian stationary models for ocean waves

Transformed Gaussian processes using Hermite expansions are revisited. An exact solution for the moment method is proposed with a Matlab program. The Central Limit Theorem is established for the coefficients of the expansion and the extreme behavior of such models is given. Eventually a numerical application to ocean waves is presented.     

Stochastic networks for constraint satisfaction and optimization

Stochastic algorithms for solving constraint satisfaction problems with soft constraints that can be implemented on a parallel distributed network are discussed in a unified framework. The algorithms considered are: the Boltzmann machine, a Learning Automata network for Relaxation Labelling and a formulation of optimization problems based on Markov random field (mrf) models. It is shown that the automata network and themrf formulation can be regarded as generalisations of the Boltzmann machine in different directions.     

Existence and construction of translation models for stationary non-Gaussian processes

Translation models are memoryless transformations of Gaussian processes specified by their marginal distribution F and covariance function ξ. Iteration schemes are commonly used to find probability laws of Gaussian images of translation models, although these schemes may not converge since translation models do not exist for arbitrary functions F and ξ. Pairs (F,ξ) for which translation models exist are said to be consistent. Optimization algorithms are developed for constructing translation models that, for consistent pairs (F,ξ), match F and ξ, and, for inconsistent pairs (F,ξ), match F or ξ and approximate ξ or F. The resulting translation models can be used in Monte Carlo simulation studies.     

Monitoring and simulating non‐stationary vibrations for package optimization

This paper introduces a new method to analyse and simulate vibrations of transport vehicles. The method pays particular attention to the non‐stationary nature of vibrations, especially during road transport. The limitations of current methods used for analysing and simulating vehicle vibrations are demonstrated. The paper shows how the Hilbert transform can be used to compute the vibration intensity and offers substantial data reduction advantages. It is shown how statistical characteristics of the vibration intensity can be combined with spectral characteristics to enable more realistic simulations of transport vibrations. Finally, it is shown how the processed data is well suited for use with modern telemetry techniques integrated with web browser technologies. Copyright © 2000 John Wiley & Sons, Ltd.     

Quantized hopfield networks for reliability optimization

The use of neural networks in the reliability optimization field is rare. This paper presents an application of a recent kind of neural networks in a reliability optimization problem for a series system with multiple-choice constraints incorporated at each subsystem, to maximize the system reliability subject to the system budget. The problem is formulated as a nonlinear binary integer programming problem and characterized as an NP-hard problem. Our design of neural network to solve efficiently this problem is based on a quantized Hopfield network. This network allows us to obtain optimal design solutions very frequently and much more quickly than others Hopfield networks.     

Refurbishing procedures for blades of large stationary gas turbines

Abstract

The design life for blades of large stationary gas turbines is at least 100000 h in creep terms. Typical damage occurring within the lifetime of gas-turbine blading may be hot corrosion and/or erosion, foreign-object damage, tip rubbing, and cracking caused by low-cycle fatigue, thermocycle fatigue, high-cycle fatigue, and creep crack growth. When applying refurbishing procedures both technical and economic aspects should be considered. The repair procedures available are welding, brazing, plasma spraying, recoating, combined with special heat treatment cycles, and occasionally intermediate hot isostatic pressing. The limiting factors for repair procedures are the mechanical properties and the hot corrosion behaviour of the refurbished parts. Examples are given of results from metallographic and laboratory tests on refurbished Kraftwerk Union (KWU) test specimens and blades in relation to the material, design, and stressing of the components. Typical examples of the refurbished parts are also presented. Service experience with refurbished blades in stationary gas turbines is limited at present. Therefore, KWU can only consider these procedures in the light of the growing knowledge of refurbishing processes and the operating experience of refurbished parts as well as the economic aspects.

MST/102     

Heavy gas dispersion: integral models and shallow layer models

Integral models for heavy gas dispersion approximate a dispersing cloud in terms of a small number of variables; each of these is ultimately a function of an independent variable which is usually time (instantaneous releases) or downwind distance (continuous releases). This type of model is used almost exclusively in risk assessment [HSE's risk assessment tool, RISKAT, in: Major Hazards: Onshore and Offshore, October 1992, pp. 607-638; Ann. Rev. Fluid Mech. 21 (1989) 317], but many distinct integral models exist. The code comparison exercise of Mercer et al. [CEA/AEA exchange agreement on external event. Comparison of heavy gas dispersion models for instantaneous releases: final report, Technical Report IR/L/HA/91/6, Health and Safety Laboratory, Sheffield, June 1991; J. Hazard. Mater. 36 (1994) 193] presented the results from a number of integral models in a common format; Mercer found that the range of predictions for some scenarios exceeded three orders of magnitude. Here, the TWODEE shallow layer model [J. Hazard. Mater. 66 (3) (1999) 211; J. Hazard. Mater. 66 (3) (1999) 227; J. Hazard. Mater. 66 (3) (1999) 239] is added to Mercer's code comparison exercise. The physical assumptions used in shallow layer models differ profoundly from those used in integral models and the implications of these differences for risk assessment are discussed. TWODEE was used to simulate four representative cases considered by Mercer. In terms of cloud averaged concentration (CAC) vs. centroid position, the present model gave predictions that were consistent with the integral models used by Mercer. As the model neglects horizontal diffusion for passive clouds, overprediction at large downwind distances was expected, but not generally observed.     

Operational planning models for distribution networks

The design and optimisation of a logistic network deals with a wide set of decisions, e.g. the determination of the best location and capacity of the different logistic facilities (production plants, distribution centres, transit points, wholesalers, etc.), the allocation of the product demand coming from customers in presence (or absence) of fractionable flows of material, the determination of the best transportation mode (truck, rail, etc.) as well as loading and routing of vehicles. These decisions involve multiple stages of a distribution network: customers-regional distribution centres (RDC), RDCs-central distribution centres (CDC) and CDCs-production plants and sources, in presence of multiple products and the variable time (i.e. time-dependent product demand and flows of material). This paper presents a top-down methodology that joins the strategic planning, the tactical planning and the operational planning of distribution networks with a special focus on the development of effective heuristic methods to face the vehicle routing problem. Original models and heuristic algorithms for the operational planning are illustrated. The impact of the strategic and tactical decisions on the performance of the operational planning is evaluated by the application of the proposed hierarchical approach to two realistic case studies. Obtained results are illustrated in a what-if experimental analysis conducted on multiple problem settings and realistic scenarios.     

Developing optimization models for cross-functional decision-making: integrating marketing and production planning

Although the lately evolved enterprise resource planning systems provide a unified platform for managing and integrating core business processes within a firm, the decision-making between marketing and production planning still remains rather independent. It is due in large part to the inherent weaknesses of ERP such as fixed and static parameter settings and uncapacitated assumption. To remedy these drawbacks, we propose decision model that solves optimally the production lot-size/scheduling problem taking into account the dynamic aspect of customer's demand and the restriction of finite capacity in a plant. The joint decision model is developed based on the inventory followed by shortages (IFS) inventory policy. The model is practical and can possibly be used as an add-on optimizer like an advanced planning system in ERP framework that coordinates distinct functions with an aim at maximizing the total profit of a firm. In this study, two versions of the model, i.e., the decentralized and the coordinated decision-making policies, were derived. They were solved by using dynamic programming technique combined with iterative search. In addition, numerical study was carried out, comparative experiment was conducted, and sensitivity was analyzed with respect to major parameters. This research was partially supported by the National Science Council (Taiwan) under Grant NSC93- 2416-H-008-007.     

Hot gas defrost model development and validation

This paper describes the development, validation, and application of a transient model for predicting the heat and mass transfer effects associated with an industrial air-cooling evaporator during a hot gas defrost cycle. The inputs to the model include the space dry bulb temperature, space humidity, coil geometry, frost thickness, frost density, and hot gas inlet temperature. The model predicts the time required for a complete frost melt as well as the sensible and latent loads transferred back to the conditioned space during the defrost period. The model is validated by comparing predicted results to actual defrost cycle field measurements and to results presented in previously published studies.A unique contribution of the present model is its ability to estimate parasitic space loads generated during a defrost cycle. The parasitic energy associated with the defrost process includes thermal convection, moisture re-evaporation, and extraction of the stored energy in the coil mass following a defrost cycle. Each of these factors contribute to the parasitic load on compressors connected to the defrost return. The results from the model provide quantitative information on evaporator operation during a defrost cycle which forms the basis to improve the energy efficiency of the defrost process.     

Picosecond pump-probe absorption spectroscopy in gases: models and experimental validation

Picosecond pump-probe absorption spectroscopy is a spatially resolved technique that is capable of measuring species concentrations in an absolute sense without the need for calibrations. When laser pulses are used that are shorter than the collision time in a sample, this pump-probe technique exhibits reduced sensitivity to collisional effects such as electronic quenching. We describe modeling and experimental characterization of this technique. The model is developed from rate equations that describe the interactions of the pump and probe pulses with the sample. Calculations based on the density-matrix equations are used to identify limits of applicability for the model. Excellent agreement between the model and the experimental data is observed when both 1.3- and 65-ps pulses are used to detect potassium in a flame and in an atomic vapor cell.     

Instrument development tools and activities for measure validation using Rasch models: part II--validation activities

Accumulation of validity evidence is an important part of the instrument development process. In Part I of a two-part series, we provided an overview of validity concepts and described how instrument development efforts can be conducted to facilitate the development of validity arguments. In this, Part II of the series, we identify how analyses, especially those conducted within a Rasch measurement framework, can be used to provide evidence to support validity arguments that are founded during the instrument development process.     

Aerodynamics of moving and stationary beds at high gas velocities

Some features of the operation of a dense bed at high gas velocities are examined, together with the conditions of suspension of the charge in a furnace. The maximum permissible gas velocities in the bed are obtained. The flow friction is determined for loose material in the moving and stationary beds.     

R-744 gas cooler model development and validation

A first principles-based model was developed for a transcritical CO₂ gas cooler, using a finite element method. The model uses published correlations for refrigerant and airside heat transfer and pressure drop. Experimental results are presented at 48 operating conditions. The model predicted the gas cooler capacity within ±2% and pressure drop on the R-744 side well within the range of experimental error. The model's usefulness is demonstrated by analyzing alternative circuiting and multi-slab designs.     

Monolayer-protected gold nanoparticles as a stationary phase for open tubular gas chromatography

The use of a thin film of monolayer-protected gold nanoparticles (MPNs) as a stationary phase for gas chromatography (GC) is reported. Deposition of a MPN film was obtained in a 2-m, 530-microm-i.d. deactivated silica capillary using gravity to force the solution containing the MPN material through the capillary. By SEM analysis, the average film thickness was determined to be 60.7 nm. The retention behavior for the dodecanethiol MPN column was studied using four compound classes (alkanes, alcohols, aromatics, ketones), and retention orders were objectively compared to a commercially available column (AT-1, 100-nm film thickness). Separation of an eight-component mixture was performed using both isothermal and temperature-programming methods with the dodecanethiol MPN phase and compared to an isothermal separation with the AT-1 phase. The AT-1 phase separation had an efficiency, N, of 6200 (k' = 0.33) while the dodecanethiol MPN phase separation had an efficiency, N, of 5700 (k' = 0.21) for the same analyte, octane. The reduced plate height, h, for octane was found to be less than 1 at the optimum linear flow velocity, indicating the MPN column operated near the optimum possible performance level. Robustness of the MPN phase is also discussed with consistent performance observed over several months. Overall, MPNs appear promising as a stationary-phase material for GC and as an experimental platform to study their thermodynamic and mass-transfer properties.