176 resultados para Enzymes - Industrial applications


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The ability to understand and predict how thermal, hydrological,mechanical and chemical (THMC) processes interact is fundamental to many research initiatives and industrial applications. We present (1) a new Thermal– Hydrological–Mechanical–Chemical (THMC) coupling formulation, based on non-equilibrium thermodynamics; (2) show how THMC feedback is incorporated in the thermodynamic approach; (3) suggest a unifying thermodynamic framework for multi-scaling; and (4) formulate a new rationale for assessing upper and lower bounds of dissipation for THMC processes. The technique is based on deducing time and length scales suitable for separating processes using a macroscopic finite time thermodynamic approach. We show that if the time and length scales are suitably chosen, the calculation of entropic bounds can be used to describe three different types of material and process uncertainties: geometric uncertainties,stemming from the microstructure; process uncertainty, stemming from the correct derivation of the constitutive behavior; and uncertainties in time evolution, stemming from the path dependence of the time integration of the irreversible entropy production. Although the approach is specifically formulated here for THMC coupling we suggest that it has a much broader applicability. In a general sense it consists of finding the entropic bounds of the dissipation defined by the product of thermodynamic force times thermodynamic flux which in material sciences corresponds to generalized stress and generalized strain rates, respectively.

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By combining gene design and heterologous over-expression of Rhodotorula gracilis D-amino acid oxidase (RgDAO) in Pichia pastoris, enzyme production was enhanced by one order of magnitude compared to literature benchmarks, giving 350 kUnits/l of fed-batch bioreactor culture with a productivity of 3.1 kUnits/l h. P. pastoris cells permeabilized by freeze-drying and incubation in 2-propanol (10% v/v) produce a highly active (1.6 kUnits/g dry matter) and stable oxidase preparation. Critical bottlenecks in the development of an RgDAO catalyst for industrial applications have been eliminated.

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Effective machine fault prognostic technologies can lead to elimination of unscheduled downtime and increase machine useful life and consequently lead to reduction of maintenance costs as well as prevention of human casualties in real engineering asset management. This paper presents a technique for accurate assessment of the remnant life of machines based on health state probability estimation technique and historical failure knowledge embedded in the closed loop diagnostic and prognostic system. To estimate a discrete machine degradation state which can represent the complex nature of machine degradation effectively, the proposed prognostic model employed a classification algorithm which can use a number of damage sensitive features compared to conventional time series analysis techniques for accurate long-term prediction. To validate the feasibility of the proposed model, the five different level data of typical four faults from High Pressure Liquefied Natural Gas (HP-LNG) pumps were used for the comparison of intelligent diagnostic test using five different classification algorithms. In addition, two sets of impeller-rub data were analysed and employed to predict the remnant life of pump based on estimation of health state probability using the Support Vector Machine (SVM) classifier. The results obtained were very encouraging and showed that the proposed prognostics system has the potential to be used as an estimation tool for machine remnant life prediction in real life industrial applications.

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Cold-active lipases are of significant interest as biocatalysts in industrial processes. We have identified a lipase that displayed activity towards long carbon-chain-p-nitrophenyl substrates (C12–C18) at 25 °C from the culture supernatant of an Antarctic Penicillium expansum strain assigned P. expansum SM3. Zymography revealed a protein band of around 30 kDa with activity towards olive oil. DNA fragments of a lipase gene designated as lipPE were isolated from the genomic DNA of P. expansum SM3 by genomic walking PCR. Subsequently, the complete genomic lipPE gene was amplified using gene-specific primers designed from the 5′- and 3′-regions. Reverse transcription PCR was used to amplify the lipPE cDNA. The deduced amino acid sequence consisted of 285 residues that included a predicted signal peptide. Three peptides identified by LC/MS/MS analysis of the proteins in the culture supernatant of P. expansum were also present in the deduced amino acid sequence of the lipPE gene suggesting that this gene encoded the lipase identified by initial zymogram activity analysis. Full analysis of the nucleotide and the deduced amino acid sequences indicated that the lipPE gene encodes a novel P. expansum lipase. The lipPE gene was expressed in E. coli for further characterization of the enzyme with a view of assessing its suitability for industrial applications.

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Interior permanent-magnet synchronous motors (IPMSMs) become attractive candidates in modern hybrid electric vehicles and industrial applications. Usually, to obtain good control performance, the electric drives of this kind of motor require one position, one dc link, and at least two current sensors. Failure of any of these sensors might lead to degraded system performance or even instability. As such, sensor fault resilient control becomes a very important issue in modern drive systems. This paper proposes a novel sensor fault detection and isolation algorithm based on an extended Kalman filter. It is robust to system random noise and efficient in real-time implementation. Moreover, the proposed algorithm is compact and can detect and isolate all the sensor faults for IPMSM drives. Thorough theoretical analysis is provided, and the effectiveness of the proposed approach is proven by extensive experimental results.

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The mineral pectolite NaCa2Si3O8(OH) is a crystalline sodium calcium silicate which has the potential to be used in plaster boards and in other industrial applications. Raman bands at 974 and 1026 cm−1 are assigned to the SiO stretching vibrations of linked units of Si3O8 units. Raman bands at 974 and 998 cm−1 serve to identify Si3O8 units. The broad Raman band at around 936 cm−1 is attributed to hydroxyl deformation modes. Intense Raman band at 653 cm−1 is assigned to OSiO bending vibration. Intense Raman bands in the 2700–3000 cm−1 spectral range are assigned to OH stretching vibrations of the OH units in pectolite. Infrared spectra are in harmony with the Raman spectra. Raman spectroscopy with complimentary infrared spectroscopy enables the characterisation of the silicate mineral pectolite.

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The effects of various discharge parameters and ambient gas on the length of He atmospheric plasma jet plumes expanding into the open air are studied. It is found that the voltage and width of the discharge-sustaining pulses exert significantly stronger effects on the plume length than the pulse frequency, gas flow rate, and nozzle diameter. This result is explained through detailed analysis of the I-V characteristics of the primary and secondary discharges which reveals the major role of the integrated total charges of the primary discharge in the plasma dynamics. The length of the jet plume can be significantly increased by guiding the propagating plume into a glass tube attached to the nozzle. This increase is attributed to elimination of the diffusion of surrounding air into the plasma plume, an absence which facilitates the propagation of the ionization front. These results are important for establishing a good level of understanding of the expansion dynamics and for enabling a high degree of control of atmospheric pressure plasmas in biomedical, materials synthesis and processing, environmental and other existing and emerging industrial applications. © 2009 American Institute of Physics.

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An overview of dynamic self-organization phenomena in complex ionized gas systems, associated physical phenomena, and industrial applications is presented. The most recent experimental, theoretical, and modeling efforts to understand the growth mechanisms and dynamics of nano- and micron-sized particles, as well as the unique properties of the plasma-particle systems (colloidal, or complex plasmas) and the associated physical phenomena are reviewed and the major technological applications of micro- and nanoparticles are discussed. Until recently, such particles were considered mostly as a potential hazard for the microelectronic manufacturing and significant efforts were applied to remove them from the processing volume or suppress the gas-phase coagulation. Nowadays, fine clusters and particulates find numerous challenging applications in fundamental science as well as in nanotechnology and other leading high-tech industries.

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Self-organization and dynamic processes of nano/micron-sized solid particles grown in low-temperature chemically active plasmas as well as the associated physico-chemical processes are reviewed. Three specific reactive plasma chemistries, namely, of silane (SiH4), acetylene (C 2H2), and octafluorocyclobutane (c-C4F 8) RF plasma discharges for plasma enhanced chemical vapor deposition of amorphous hydrogenated silicon, hydrogenated and fluorinated carbon films, are considered. It is shown that the particle growth mechanisms and specific self-organization processes in the complex reactive plasma systems are related to the chemical organization and size of the nanoparticles. Correlation between the nanoparticle origin and self-organization in the ionized gas phase and improved thin film properties is reported. Self-organization and dynamic phenomena in relevant reactive plasma environments are studied for equivalent model systems comprising inert buffer gas and mono-dispersed organic particulate powders. Growth kinetics and dynamic properties of the plasma-assembled nanoparticles can be critical for the process quality in microelectronics as well as a number of other industrial applications including production of fine metal or ceramic powders, nanoparticle-unit thin film deposition, nanostructuring of substrates, nucleating agents in polymer and plastics synthesis, drug delivery systems, inorganic additives for sunscreens and UV-absorbers, and several others. Several unique properties of the chemically active plasma-nanoparticle systems are discussed as well.

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The performance of the 500 KHz planar-coil inductively coupled plasma source was studied. The global electrical characteristics of the discharge, distributions of the induced electromagnetic fields, plasma density, potential, and electron temperature were investigated. Achieved high plasma density and low electron temperature implied that the studied plasma source was promising for industrial applications.

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Detection of faults in roller element bearing is a topic widely discussed in the scientific field. Bearings diagnostics is usually performed by analyzing experimental signals, almost always vibration signals, measured during operation. A number of signal processing techniques have been proposed and applied to measured vibrations. The diagnostic effectiveness of the techniques depends on their capacities and on the environmental conditions (i.e. environmental noise). The current trend, especially from an industrial point of view, is to couple the prognostics to the diagnostics. The realization of a prognostic procedure require the definition of parameters able to describe the bearing condition during its operation. Monitoring the values of these parameters during time allows to define their trends depending on the progress of the wear. In this way, a relation between the variation of the selected parameters and the wear progress, useful for diagnostics and prognostics of bearings in real industrial applications, can be established. In this paper, a laboratory test-rig designed to perform endurance tests on roller element bearing is presented. Since the test-rig has operated for a short time, only some preliminary available results are discussed.

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Monitoring of the integrity of rolling element bearings in the traction system of high speed trains is a fundamental operation in order to avoid catastrophic failures and to implement effective condition-based maintenance strategies. Diagnostics of rolling element bearings is usually based on vibration signal analysis by means of suitable signal processing techniques. The experimental validation of such techniques has been traditionally performed by means of laboratory tests on artificially damaged bearings, while their actual effectiveness in industrial applications, particularly in the field of rail transport, remains scarcely investigated. This paper will address the diagnostics of bearings taken from the service after a long term operation on a high speed train. These worn bearings have been installed on a test-rig, consisting of a complete full-scale traction system of a high speed train, able to reproduce the effects of wheel-track interaction and bogie-wheelset dynamics. The results of the experimental campaign show that suitable signal processing techniques are able to diagnose bearing failures even in this harsh and noisy application. Moreover, the most suitable location of the sensors on the traction system is also proposed.

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Rolling element bearings are the most critical components in the traction system of high speed trains. Monitoring their integrity is a fundamental operation in order to avoid catastrophic failures and to implement effective condition based maintenance strategies. Generally, diagnostics of rolling element bearings is usually performed by analyzing vibration signals measured by accelerometers placed in the proximity of the bearing under investigation. Several papers have been published on this subject in the last two decades, mainly devoted to the development and assessment of signal processing techniques for diagnostics. The experimental validation of such techniques has been traditionally performed by means of laboratory tests on artificially damaged bearings, while their actual effectiveness in specific industrial applications, particularly in rail industry, remains scarcely investigated. This paper is aimed at filling this knowledge gap, by addressing the diagnostics of bearings taken from the service after a long term operation on the traction system of a high speed train. Moreover, in order to test the effectiveness of the diagnostic procedures in the environmental conditions peculiar to the rail application, a specific test-rig has been built, consisting of a complete full-scale train traction system, able to reproduce the effects of wheeltrack interaction and bogie-wheelset dynamics. The results of the experimental campaign show that suitable signal processing techniques are able to diagnose bearing failures even in this harsh and noisy application. Moreover, the most suitable location of the sensors on the traction system is proposed, in order to limit their number.

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The mineral harmotome (Ba,Na,K)1-2(Si,Al)8O16⋅6H2O is a crystalline sodium calcium silicate which has the potential to be used in plaster boards and other industrial applications. It is a natural zeolite with catalytic potential. Raman bands at 1020 and 1102 cm−1 are assigned to the SiO stretching vibrations of three dimensional siloxane units. Raman bands at 428, 470 and 491 cm−1 are assigned to OSiO bending modes. The broad Raman bands at around 699, 728, 768 cm−1 are attributed to water librational modes. Intense Raman bands in the 3100 to 3800 cm−1 spectral range are assigned to OH stretching vibrations of water in harmotome. Infrared spectra are in harmony with the Raman spectra. A sharp infrared band at 3731 cm−1 is assigned to the OH stretching vibration of SiOH units. Raman spectroscopy with complimentary infrared spectroscopy enables the characterization of the silicate mineral harmotome.

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The Energy Efficiency (EE) Graduate Attributes Project focuses on engineering as a priority profession that has a significant role to play in addressing energy demand and supply issues in Australia. Specifically, this project aims to support embedding EE knowledge and skills throughout the engineering undergraduate curriculum, to help build capacity within the Australian workforce across major sectors of the economy, from mining, manufacturing and industrial applications to design, construction, maintenance and retrofitting built environments. The resultant report is intended to assist in future consultation with key groups such as Engineers Australia (EA), the Australian Council of Engineering Deans (ACED) and the eight EA colleges, to support systemic curriculum renewal and promote the design and development of high quality EE engineering education resources. The project is based on a whole-of-program outcomes-based approach to curriculum renewal, creating a transparent framework for integrating EE. This comprises collaborative consideration by academics and professional engineers who have experience in teaching and practising EE, to identify what students should learn to be equipped with relevant competencies by the time they graduate.