Effect of Silver Loading on the Lean NOx Reduction with Methanol Over Ag–Al2O3

The influence of silver loading on the lean NO_x reduction activity using methanol as reductant has been studied for alumina supported silver catalysts. In general, increasing the silver loading (0–3 wt%), in Ag–Al₂O₃, shifts or extends the activity window, for lean NO_x reduction towards lower temperatures. In particular Ag–Al₂O₃ with 3 wt% silver is active for NO_x reduction under methanol-SCR conditions in a broad temperature interval (200–500 °C), with high activity in the low temperature range (maximum around 300 °C) typical for exhaust gases from diesel and other lean burn engines. Furthermore, increasing the C/N molar ratio enhances the reduction of NO_x. However, too high C/N ratios results in poor selectivity to N₂.     

STEAM DRYLNG OF WOOD FUELS

ABSTRACT

The objective of this work is to investigate some of the important aspects in the design of a steam band dryer for wood fuels. For this purpose the drying of the material in a bench-scale fixed bed dryer has been studied.

Drying times and thermal efficiencies for experiments conducted under different conditions are compared. The investigated materials are soft-and hardwood chips and softwood bark.

The thermal efficiency, the part of the sensible heat which is used during one passage of the steam through the bed, increases with increasing mass load (mass of dry matter per unit area) and with decreasing steam mass flux. At a mass load of 30 kg/m the thermal efficiency is about 0.85 even at steam mass fluxes as high as 0.6 kg/m² s (1.2 m/s). The thermal efficiency proves to be almost independent of pressure and temperature of the steam.

Due to the very inhomogeneous materials the steam mass flow distribution was uneven. This causes a decreased thermal efficiency. When bark     

Multivariable data analysis of a cold rolling control system to minimise defects

This paper focuses on the application of principal component analysis (PCA) to thoroughly analyse and interpret multidimensional data from a cold rolling process. The analysis includes the effects of variables on the final properties of strips in a cold rolling mill. Unscrambler software was used to analyse and identify hidden variables. Variable correlations were also used to derive correlations between the control parameters. The results of this research will be used to improve the selection of material in order to reduce the occurrence of defects in the cold rolling process and to improve the adjustment of the set points that are performed in every pass or section of the cold rolling process. The hot rolled strips that enter the cold rolling mill are made of different materials and are produced by different strip manufacturers. Some strips break during the thickness reduction process in the cold rolling mill. This paper focuses on two possible causes of breakage: non-uniform strip material properties and failures in the rolling mill process. Two types of rolled strips (those that break and those that do not break) were compared to identify causes of breakage. The results indicate that breakages are caused by material or process failures. PCA was applied to the dataset in order to identify and analyse the relationships between the variables in the process. This information was used to interpret and diagnose the process behaviour. Swarm analysis and relating observations to process behaviour were able to distinguish between different start-up conditions, and between desirable and undesirable process conditions.     

Ambient oxygen ingress rate method—an alternative method to Ox‐Tran for measuring oxygen transmission rate of whole packages

The ambient oxygen ingress rate method (AOIR) is an alternative method to Ox‐Tran for measuring the oxygen transmission rates (OTR) of whole packages. The objective of the present work was (a) to compare OTR values obtained by the two methods, and (b) to evaluate the use of the AOIR method for measuring OTR at realistic food storage temperatures and humidity levels. The AOIR method gave equal OTR values compared to the Ox‐Tran method for the five different types of whole packages used in the experiment, with OTR values in the range 0.06–1.48 ml O₂/day. The repeatability of the AOIR method measured on an HDPE bottle was ±2.6% of the measured value in this experiment. This is slightly higher than the general specifications of the Ox‐Tran method (1% of reading for packages). However, the AOIR method can be considered to be a reliable, precise and cheap alternative method to the Ox‐Tran method for measuring OTR of whole packages. The capacity of the method is also high. The AOIR method showed satisfactory results when comparing OTR for packages tested under realistic food storage conditions covering 23°C/50% relative humidity (RH) and at 4°C/60% RH on the outside, combined with water (100% RH) or dry air inside the packages. Copyright © 2000 John Wiley & Sons, Ltd.     

The power of gifts: organizing social relationships in open source communities

Abstract. In writings on the open source software development model, it is often argued that it is successful as a result of the gift economy that embraces activities in online communities. However, the theoretical foundations for this argument are seldom discussed and empirically tested. Starting with the 'classic' theories of gift giving, we discuss how they need to be developed in order to explain gift-giving practices in digital domains. In this paper, we argue that the gift economy is important, not only because it creates openness, but also because it organizes relationships between people in a certain way. Open source software development relies on gift giving as a way of getting new ideas and prototypes out into circulation. This also implies that the giver gets power from giving away. This power is used as a way of guaranteeing the quality of the code. We relate this practice to how gifts, in the form of new scientific knowledge, are given to the research community, and how this is done through peer review processes.     

Accuracy analysis of a covariance matching approach for identifying errors-in-variables systems

A system identification method for errors-in-variables problems based on covariance matching was recently proposed. In the first step, a small amount of covariances of noisy input–output data are computed, and then a parametric model is fitted to these covariances. In this paper, the method is further analyzed and the asymptotic accuracy of the parameter estimates is derived. An explicit algorithm for computing the asymptotic covariance matrix of the parameter estimates is given, and the identification method is shown to be asymptotically statistically efficient assuming that the given information is the computed covariances. As an important byproduct, an efficient algorithm is presented for computing the covariance matrix of the computed input–output covariances.     

Improving yield and shape in a crushing plant

There is increasing demand to optimise yield and increase capacity of crushing plants. Research in this area has resulted in the development of numerous optimisation tools, and resent research has shown that the economic aspects of production have great influence on the optimisation results. The profitability of a product is influenced by several parameters, and control of all these parameters is necessary to use some sort of optimisation software.In this paper, we present a case study of a typical crushing plant, with the goal of reducing the number of crusher while keeping the plant capacity and quality. By reducing the number of crusher the plant will need less maintenance which will decrease the operating costs. The article presents a method to combine crushing plant simulation and optimisation with quality and economic considerations in order to successfully study alternative configurations of the plant.     

Algorithm for dynamic cone crusher control

Cone crushers are used in the mineral, mining, and aggregate industry for fragmentation of rock materials. Control systems for cone crusher settings are widely used for compensating for wear and protecting the machines from high pressure. However, these systems focus on the crusher and not the crushed products.By applying measurement devices on the process the crusher can be run optimally from the saleable products point of view (unlike most existing systems which only protect the machine) in each time. The measurement devices can be mass flow meters, e.g. conveyor belt scales. To analyze data from the process and convert them to a desired CSS value, an algorithm was developed.The developed algorithm is tested and evolved at a real crushing plant for aggregates. The algorithm was loaded into a computer which could communicate with the crusher control system, read data from three mass flow meters, and also interact with the operators. The computer was reachable over the Internet by the researchers at Chalmers and the algorithm was tuned and improved on-line.The result is an algorithm which was capable of providing CSS set-points to the automatic setting regulation system. The amount of saleable product from the crushing stage improved 3.5%, when not limited by the hydraulic pressure, compared to when a fixed closed side setting is used. The use of the algorithm automatically compensates for changes in the feed material and it also decreases the need for calibration of the underlying system.     

Automatic Generation of Persistent Formations for Multi-agent Networks Under Range Constraints

In this paper we present a collection of graph-based methods for determining if a team of mobile robots, subjected to sensor and communication range constraints, can persistently achieve a specified formation. What we mean by this is that the formation, once achieved, will be preserved by the direct maintenance of the smallest subset of all possible pairwise inter-agent distances. In this context, formations are defined by sets of points separated by distances corresponding to desired inter-agent distances. Further, we provide graph operations to describe agent interactions that implement a given formation, as well as an algorithm that, given a persistent formation, automatically generates a sequence of such operations. Experimental results are presented that illustrate the operation of the proposed methods on real robot platforms.     

On the calculation of the quasi-bound-state energies and lifetimes in inverted MOS structures with ultrathin oxides and its application to the direct tunneling current

We discuss the inverted MOS structure with extremely thin oxides as a quasi-bound-state system. Its energy subbands can be regarded as resonances of a quantum mechanical system with a continuum of eigenstates. We derive an analytical calculation to extract the defining parameters of the Lorentzian peaks associated with the relative probability of localizing an electron in the confining potential region at the Si/dielectric interface and propose an algorithm that allows to estimate the energy levels and the lifetimes of these states, provided the solution of the approximate bound state system is known. This new method has the advantage of not being affected by computational errors, avoiding the time consuming scanning procedure usually employed in previously reported works. Furthermore, a comparison with semiclassical calculation of the lifetimes is performed and direct tunneling current is calculated, which allows it to fit experimental gate-leakage curves with high accuracy.