127 resultados para 259903 Industrial Chemistry
Resumo:
The concept of sustainable manufacturing is a form of pollution prevention that integrates environmental considerations in the production of goods while focusing on efficient resource use. Taking the industrial ecology perspective, this efficiency comes from improved resource flow management. The assessment of material, energy and waste resource flows, therefore, offers a route to viewing and analysing a manufacturing system as an ecosystem using industrial ecology biological analogy and can, in turn, support the identification of improvement opportunities in the material, energy and waste flows. This application of industrial ecology at factory level is absent from the literature. This article provides a prototype methodology to apply the concepts of industrial ecology using material, energy and waste process flows to address this gap in the literature. Various modelling techniques were reviewed and candidates selected to test the prototype methodology in an industrial case. The application of the prototype methodology showed the possibility of using the material, energy and waste resource flows through the factory to link manufacturing operations and supporting facilities, and to identify potential improvements in resource use. The outcomes of the work provide a basis to build the specifications for a modelling tool that can support those analysing their manufacturing system to improve their environmental performance and move towards sustainable manufacturing. © IMechE 2012.
Resumo:
In this paper, a synthetic mixture of ZrO2 and Fe 2O3 was prepared by coprecipitation for use in chemical looping and hydrogen production. Cycling experiments in a fluidized bed showed that a material composed of 30 mol % ZrO2 and 70 mol % Fe 2O3 was capable of producing hydrogen with a consistent yield of 90 mol % of the stoichiometric amount over 20 cycles of reduction and oxidation at 1123 K. Here, the iron oxide was subjected to cycles consisting of nearly 100% reduction to Fe followed by reoxidation (with steam or CO 2 and then air) to Fe2O3. There was no contamination by CO of the hydrogen produced, at a lower detection limit of 500 ppm, when the conversion of Fe3O4 to Fe was kept below 90 mol %. A preliminary investigation of the reaction kinetics confirmed that the ZrO2 support does not inhibit rates of reaction compared with those observed with iron oxide alone. © 2012 American Chemical Society.
Resumo:
Direct Numerical Simulations (DNS) of turbulent n-heptane sprays autoigniting at high pressure (P=24bar) and intermediate air temperature (Tair=1000K) have been performed to investigate the physical mechanisms present under conditions where low-temperature chemistry is expected to be important. The initial turbulence in the carrier gas, the global equivalence ratio in the spray region, and the initial droplet size distribution of the spray were varied. Results show that spray ignition exhibits a spotty nature, with several kernels developing independently in those regions where the mixture fraction is close to its most reactive value ξMR (as determined from homogeneous reactor calculations) and the scalar dissipation rate is low. Turbulence reduces the ignition delay time as it promotes mixing between air and the fuel vapor, eventually resulting in lower values of scalar dissipation. High values of the global equivalence ratio are responsible for a larger number of ignition kernels, due to the higher probability of finding regions where ξ=ξMR. Spray polydispersity results in the occurrence of ignition over a wider range of mixture fraction values. This is a consequence of the inhomogeneities in the mixing field that characterize these sprays, where poorly mixed rich spots are seen to alternate with leaner ones which are well-mixed. The DNS simulations presented in this work have also been used to assess the applicability of the Conditional Moment Closure (CMC) method to the simulation of spray combustion. CMC is found to be a valid method for capturing spray autoignition, although care should be taken in the modelling of the unclosed terms appearing in the CMC equations. © 2013 The Combustion Institute.
Resumo:
An established Stochastic Reactor Model (SRM) is used to simulate the transition from Spark Ignition (SI) to Homogeneous Charge Compression Ignition (HCCI) combustion mode in a four cylinder in-line four-stroke naturally aspirated direct injection SI engine with cam profile switching. The SRM is coupled with GT-Power, a one-dimensional engine simulation tool used for modelling engine breathing during the open valve portion of the engine cycle, enabling multi-cycle simulations. The mode change is achieved by switching the cam profiles and phasing, resulting in a Negative Valve Overlap (NVO), opening the throttle, advancing the spark timing and reducing the fuel mass as well as using a pilot injection. A proven technique for tabulating the model is used to create look-up tables in both SI and HCCI modes. In HCCI mode several tables are required, including tables for the first NVO, transient valve timing NVO, transient valve timing HCCI and steady valve timing HCCI and NVO. This results in the ability to simulate the transition with detailed chemistry in very short computation times. The tables are then used to optimise the transition with the goal of reducing NO x emissions and fluctuations in IMEP. Copyright © 2010 SAE International.
Resumo:
A Stochastic Reactor Model (SRM) has been used to simulate the transition from Spark Ignition (SI) mode to Homogeneous Charge Compression Ignition (HCCI) mode in a four cylinder in-line four-stroke naturally aspirated direct injection SI engine with cam profile switching. The SRM is coupled with GT-Power, a one-dimensional engine simulation tool used for modelling engine breathing during the open valve portion of the engine cycle, enabling multi-cycle simulations. The model is initially calibrated in both modes using steady state data from SI and HCCI operation. The mode change is achieved by switching the cam profiles and phasing, resulting in a Negative Valve Overlap (NVO), opening the throttle, advancing the spark timing and reducing the fuel mass as well as utilising a pilot injection. Experimental data is presented along with the simulation results. The model is used to investigate key control parameters and their effects on parameters that are difficult to measure experimentally. The effect of the spark in the first HCCI cycles is found to have a major impact on the stability of the transition. Copyright © 2010 SAE International.
Resumo:
This paper explores the evolving industrial control paradigm of product intelligence. The approach seeks to give a customer greater control over the processing of an order - by integrating technologies which allow for greater tracking of the order and methodologies which allow the customer [via the order] to dynamically influence the way the order is produced, stored or transported. The paper examines developments from four distinct perspectives: conceptual developments, theoretical issues, practical deployment and business opportunities. In each area, existing work is reviewed and open challenges for research are identified. The paper concludes by identifying four key obstacles to be overcome in order to successfully deploy product intelligence in an industrial application. © 2013 Elsevier Ltd. All rights reserved.
Resumo:
The standard design process for the Siemens Industrial Turbomachinery, Lincoln, Dry Low Emissions combustion systems has adopted the Eddy Dissipation Model with Finite Rate Chemistry for reacting computational fluid dynamics simulations. The major drawbacks of this model have been the over-prediction of temperature and lack of species data limiting the applicability of the model. A novel combustion model referred to as the Scalar Dissipation Rate Model has been developed recently based on a flamelet type assumption. Previous attempts to adopt the flamelet philosophy with alternative closure models have failed, with the prediction of unphysical phenomenon. The Scalar Dissipation Rate Model (SDRM) was developed from a physical understanding of scalar dissipation rate, signifying the rate of mixing of hot and cold fluids at scales relevant to sustain combustion, in flames and was validated using direct numerical simulations data and experimental measurements. This paper reports on the first industrial application of the SDRM to SITL DLE combustion system. Previous applications have considered ideally premixed laboratory scale flames. The industrial application differs significantly in the complexity of the geometry, unmixedness and operating pressures. The model was implemented into ANSYS-CFX using their inbuilt command language. Simulations were run transiently using Scale Adaptive Simulation turbulence model, which switches between Large Eddy Simulation and Unsteady Reynolds Averaged Navier Stokes using a blending function. The model was validated in a research SITL DLE combustion system prior to being applied to the actual industrial geometry at real operating conditions. This system consists of the SGT-100 burner with a glass square-sectioned combustor allowing for detailed diagnostics. This paper shows the successful validation of the SDRM against time averaged temperature and velocity within measurement errors. The successful validation allowed application of the SDRM to the SGT-100 twin shaft at the relevant full load conditions. Limited validation data was available due to the complexity of measurement in the real geometry. Comparison of surface temperatures and combustor exit temperature profiles showed an improvement compared to EDM/FRC model. Furthermore, no unphysical phenomena were predicted. This paper presents the successful application of the SDRM to the industrial combustion system. The model shows a marked improvement in the prediction of temperature over the EDM/FRC model previously used. This is of significant importance in the future applications of combustion CFD for understanding of hardware mechanical integrity, combustion emissions and dynamics of the flame. Copyright © 2012 by ASME.