911 resultados para Process system value


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Scientific research revolves around the production, analysis, storage, management, and re-use of data. Data sharing offers important benefits for scientific progress and advancement of knowledge. However, several limitations and barriers in the general adoption of data sharing are still in place. Probably the most important challenge is that data sharing is not yet very common among scholars and is not yet seen as a regular activity among scientists, although important efforts are being invested in promoting data sharing. In addition, there is a relatively low commitment of scholars to cite data. The most important problems and challenges regarding data metrics are closely tied to the more general problems related to data sharing. The development of data metrics is dependent on the growth of data sharing practices, after all it is nothing more than the registration of researchers’ behaviour. At the same time, the availability of proper metrics can help researchers to make their data work more visible. This may subsequently act as an incentive for more data sharing and in this way a virtuous circle may be set in motion. This report seeks to further explore the possibilities of metrics for datasets (i.e. the creation of reliable data metrics) and an effective reward system that aligns the main interests of the main stakeholders involved in the process. The report reviews the current literature on data sharing and data metrics. It presents interviews with the main stakeholders on data sharing and data metrics. It also analyses the existing repositories and tools in the field of data sharing that have special relevance for the promotion and development of data metrics. On the basis of these three pillars, the report presents a number of solutions and necessary developments, as well as a set of recommendations regarding data metrics. The most important recommendations include the general adoption of data sharing and data publication among scholars; the development of a reward system for scientists that includes data metrics; reducing the costs of data publication; reducing existing negative cultural perceptions of researchers regarding data publication; developing standards for preservation, publication, identification and citation of datasets; more coordination of data repository initiatives; and further development of interoperability protocols across different actors.

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Experimental demonstrations and theoretical analyses of a new electromechanical energy conversion process which is made feasible only by the unique properties of superconductors are presented in this dissertation. This energy conversion process is characterized by a highly efficient direct energy transformation from microwave energy into mechanical energy or vice versa and can be achieved at high power level. It is an application of a well established physical principle known as the adiabatic theorem (Boltzmann-Ehrenfest theorem) and in this case time dependent superconducting boundaries provide the necessary interface between the microwave energy on one hand and the mechanical work on the other. The mechanism which brings about the conversion is another known phenomenon - the Doppler effect. The resonant frequency of a superconducting resonator undergoes continuous infinitesimal shifts when the resonator boundaries are adiabatically changed in time by an external mechanical mechanism. These small frequency shifts can accumulate coherently over an extended period of time to produce a macroscopic shift when the resonator remains resonantly excited throughout this process. In addition, the electromagnetic energy in s ide the resonator which is proportional to the oscillation frequency is al so accordingly changed so that a direct conversion between electromagnetic and mechanical energies takes place. The intrinsically high efficiency of this process is due to the electromechanical interactions involved in the conversion rather than a process of thermodynamic nature and therefore is not limited by the thermodynamic value.

A highly reentrant superconducting resonator resonating in the range of 90 to 160 MHz was used for demonstrating this new conversion technique. The resonant frequency was mechanically modulated at a rate of two kilohertz. Experimental results showed that the time evolution of the electromagnetic energy inside this frequency modulated (FM) superconducting resonator indeed behaved as predicted and thus demonstrated the unique features of this process. A proposed usage of FM superconducting resonators as electromechanical energy conversion devices is given along with some practical design considerations. This device seems to be very promising in producing high power (~10W/cm^3) microwave energy at 10 - 30 GHz.

Weakly coupled FM resonator system is also analytically studied for its potential applications. This system shows an interesting switching characteristic with which the spatial distribution of microwave energies can be manipulated by external means. It was found that if the modulation was properly applied, a high degree (>95%) of unidirectional energy transfer from one resonator to the other could be accomplished. Applications of this characteristic to fabricate high efficiency energy switching devices and high power microwave pulse generators are also found feasible with present superconducting technology.

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Grinding is an advanced machining process for the manufacturing of valuable complex and accurate parts for high added value sectors such as aerospace, wind generation, etc. Due to the extremely severe conditions inside grinding machines, critical process variables such as part surface finish or grinding wheel wear cannot be easily and cheaply measured on-line. In this paper a virtual sensor for on-line monitoring of those variables is presented. The sensor is based on the modelling ability of Artificial Neural Networks (ANNs) for stochastic and non-linear processes such as grinding; the selected architecture is the Layer-Recurrent neural network. The sensor makes use of the relation between the variables to be measured and power consumption in the wheel spindle, which can be easily measured. A sensor calibration methodology is presented, and the levels of error that can be expected are discussed. Validation of the new sensor is carried out by comparing the sensor's results with actual measurements carried out in an industrial grinding machine. Results show excellent estimation performance for both wheel wear and surface roughness. In the case of wheel wear, the absolute error is within the range of microns (average value 32 mu m). In the case of surface finish, the absolute error is well below R-a 1 mu m (average value 0.32 mu m). The present approach can be easily generalized to other grinding operations.

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Technological investment is an important driver of innovation and the evaluation of technology potential is becoming increasingly important in this context. Although there is a range of possible approaches and tools for understanding and communicating the value of technology to potential customers, not all are useful or accessible in practice, where the situation is often complex and constantly evolving. Although many companies have their own customised processes in place for securing approval for technology development, often combining several techniques, very few empirical studies have been performed to learn from these practices and provide an overall view of the process of ";selling"; technologies internally or externally. In this paper, the current literature and practice related to technology valuation is reviewed and summarised in a five step process for building a business case for technology investment that gives guidance on where and when to use specific valuation tools. The seller or proposer's perspective is taken and consultative sales techniques incorporated. This provides a flexible reference for R&D managers and adds to the body of literature on the selection and use of valuation tools. A user friendly guide has been published detailing the five step approach. © 2011 IEEE.