947 resultados para Operational conditions


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Pilot and industrial scale dilute acid pretreatment data can be difficult to obtain due to the significant infrastructure investment required. Consequently, models of dilute acid pretreatment by necessity use laboratory scale data to determine kinetic parameters and make predictions about optimal pretreatment conditions at larger scales. In order for these recommendations to be meaningful, the ability of laboratory scale models to predict pilot and industrial scale yields must be investigated. A mathematical model of the dilute acid pretreatment of sugarcane bagasse has previously been developed by the authors. This model was able to successfully reproduce the experimental yields of xylose and short chain xylooligomers obtained at the laboratory scale. In this paper, the ability of the model to reproduce pilot scale yield and composition data is examined. It was found that in general the model over predicted the pilot scale reactor yields by a significant margin. Models that appear very promising at the laboratory scale may have limitations when predicting yields on a pilot or industrial scale. It is difficult to comment whether there are any consistent trends in optimal operating conditions between reactor scale and laboratory scale hydrolysis due to the limited reactor datasets available. Further investigation is needed to determine whether the model has some efficacy when the kinetic parameters are re-evaluated by parameter fitting to reactor scale data, however, this requires the compilation of larger datasets. Alternatively, laboratory scale mathematical models may have enhanced utility for predicting larger scale reactor performance if bulk mass transport and fluid flow considerations are incorporated into the fibre scale equations. This work reinforces the need for appropriate attention to be paid to pilot scale experimental development when moving from laboratory to pilot and industrial scales for new technologies.

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Traditionally, it is not easy to carry out tests to identify modal parameters from existing railway bridges because of the testing conditions and complicated nature of civil structures. A six year (2007-2012) research program was conducted to monitor a group of 25 railway bridges. One of the tasks was to devise guidelines for identifying their modal parameters. This paper presents the experience acquired from such identification. The modal analysis of four representative bridges of this group is reported, which include B5, B15, B20 and B58A, crossing the Carajás railway in northern Brazil using three different excitations sources: drop weight, free vibration after train passage, and ambient conditions. To extract the dynamic parameters from the recorded data, Stochastic Subspace Identification and Frequency Domain Decomposition methods were used. Finite-element models were constructed to facilitate the dynamic measurements. The results show good agreement between the measured and computed natural frequencies and mode shapes. The findings provide some guidelines on methods of excitation, record length of time, methods of modal analysis including the use of projected channel and harmonic detection, helping researchers and maintenance teams obtain good dynamic characteristics from measurement data.

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Drying of food materials offers a significant increase in the shelf life of food materials, along with the modification of quality attributes due to simultaneous heat and mass transfer. Shrinkage and variations in porosity are the common micro and microstructural changes that take place during the drying of mostly the food materials. Although extensive research has been carried out on the prediction of shrinkage and porosity over the time of drying, no single model exists which consider both material properties and process condition in the same model. In this study, an attempt has been made to develop and validate shrinkage and porosity models of food materials during drying considering both process parameters and sample properties. The stored energy within the sample, elastic potential energy, glass transition temperature and physical properties of the sample such as initial porosity, particle density, bulk density and moisture content have been taken into consideration. Physical properties and validation have been made by using a universal testing machine ( Instron 2kN), a profilometer (Nanovea) and a pycnometer. Apart from these, COMSOL Multiphysics 4.4 has been used to solve heat and mass transfer physics. Results obtained from models of shrinkage and porosity is quite consistent with the experimental data. Successful implementation of these models would ensure the use of optimum energy in the course of drying and better quality retention of dried foods.

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This paper proposes the addition of a weighted median Fisher discriminator (WMFD) projection prior to length-normalised Gaussian probabilistic linear discriminant analysis (GPLDA) modelling in order to compensate the additional session variation. In limited microphone data conditions, a linear-weighted approach is introduced to increase the influence of microphone speech dataset. The linear-weighted WMFD-projected GPLDA system shows improvements in EER and DCF values over the pooled LDA- and WMFD-projected GPLDA systems in inter-view-interview condition as WMFD projection extracts more speaker discriminant information with limited number of sessions/ speaker data, and linear-weighted GPLDA approach estimates reliable model parameters with limited microphone data.

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Extensive research conducted in the occupational stress literature has failed to provide convincing support for the stress-buffering effects of work control on employee adjustment. Drawing on research conducted in the laboratory context, it was proposed that the stress-buffering effects of work control on employee adjustment would be more marked at high, rather than low, levels of self-efficacy. In a sample of 100 customer service representatives, a significant three-way interaction among role conflict, work control and self-efficacy (measured at Time 1) was observed on (low) depersonalization (measured at Time 2). Consistent with expectations, work control reduced the negative effects of work stress on this outcome measure only for employees who perceived high levels of self-efficacy at work. In addition, there was evidence to suggest that self-efficacy moderated the main effects of work control on job satisfaction and somatic health. These findings are discussed in terms of their theoretical contribution to the job strain model, and also in relation to workplace interventions designed to improve levels of employee adjustment.

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This paper presents the details of experimental studies on the effect of real support conditions on the shear strength of hollow flange channel beams, known as LiteSteel beams (LSB). The LSB has a unique shape of a channel beam with two rectangular hollow flanges, made using a unique manufacturing process. In many applications in the building industry LSBs are used with only one web side plate (WSP) at their supports. The WSPs are also often not full height plates. Past research studies showed that these real support connections did not provide the required simply supported conditions. Many studies have been carried out to evaluate the behaviour and design of LSBs with simply supported conditions subject to pure bending and predominant shear actions. To date, however, no investigation has been conducted into the effect of real support conditions on the shear strength of LSBs. Hence a detailed experimental study based on 25 shear tests was undertaken to investigate the shear behaviour and strength of LSBs with real support conditions. Simply supported test specimens of LSBs with aspect ratios of 1.0 and 1.5 were loaded at mid-span until failure. It was found that the effect of using one WSP on the shear behaviour of LSB is significant and there is about 25% shear capacity reduction due to the lateral movement of the bottom flange at the supports. Shear capacity of LSB was also found to decrease when full height WSPs were not used. Suitably improved support connections were developed to improve the shear capacity of LSBs based on test results. Details of the recommended support connections and shear capacity results are given in this paper.

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Pollution on electrical insulators is one of the greatest causes of failure of substations subjected to high levels of salinity and environmental pollution. Considering leakage current as the main indicator of pollution on insulators, this paper focus on establishing the effect of the environmental conditions on the risk of failure due to pollution on insulators and determining the significant change in the magnitude of the pollution on the insulators during dry and humid periods. Hierarchical segmentation analysis was used to establish the effect of environmental conditions on the risk of failure due to pollution on insulators. The Kruskal-Wallis test was utilized to determine the significant changes in the magnitude of the pollution due to climate periods. An important result was the discovery that leakage current was more common on insulators during dry periods than humid ones. There was also a higher risk of failure due to pollution during dry periods. During the humid period, various temperatures and wind directions produced a small change in the risk of failure. As a technical result, operators of electrical substations can now identify the cause of an increase in risk of failure due to pollution in the area. The research provides a contribution towards the behaviour of the leakage current under conditions similar to those of the Colombian Caribbean coast and how they affect the risk of failure of the substation due to pollution.

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Diketopyrrolopyrole-naphthalene polymer (PDPP-TNT), a donor-acceptor co-polymer, has shown versatile behavior demonstrating high performances in organic field-effect transistors (OFETs) and organic photovoltaic (OPV) devices. In this paper we report investigation of charge carrier dynamics in PDPP-TNT, and [6,6]-phenyl C71 butyric acid methyl ester (PC71BM) bulk-heterojunction based inverted OPV devices using current density-voltage (J-V) characteristics, space charge limited current (SCLC) measurements, capacitance-voltage (C-V) characteristics, and impedance spectroscopy (IS). OPV devices in inverted architecture, ITO/ZnO/PDPP-TNT:PC71BM/MoO3/Ag, are processed and characterized at room conditions. The power conversion efficiency (PCE) of these devices are measured ∼3.8%, with reasonably good fill-factor 54.6%. The analysis of impedance spectra exhibits electron’s mobility ∼2 × 10−3 cm2V−1s−1, and lifetime in the range of 0.03-0.23 ms. SCLC measurements give hole mobility of 1.12 × 10−5 cm2V−1s−1, and electron mobility of 8.7 × 10−4 cm2V−1s−1.

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Fire safety plays a vital role in building design because appropriate level of fire safety is important to safeguard lives and property. Cold-formed steel channel sections along with fire-resistive plasterboards are used to construct light-gauge steel frame (LSF) floor systems to provide adequate fire resistance ratings (FRR). It is common practice to use lipped channel sections (LCS) as joists in LSF floor systems, and past research has only considered such systems. This research focuses on adopting improved joist sections such as hollow flange channel (HFC) sections to improve the structural performance and FRR of cold-formed LSF floor systems under standard fire conditions. The structural and thermal performances of LSF floor systems made of a welded HFC, LiteSteel Beams (LSB), with different plasterboard and insulation configurations, were investigated using four full-scale fire tests under standard fires. These fire tests showed that the new LSF floor system with LSB joists improved the FRR in comparison to that of conventional LCS joists. Fire tests have provided valuable structural and thermal performance data of tested floor systems that included time-temperature profiles and failure times, temperatures, and modes. This paper presents the details of the fire tests conducted in this study and their results along with some important findings.

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The climate in the Arctic is changing faster than anywhere else on earth. Poorly understood feedback processes relating to Arctic clouds and aerosol–cloud interactions contribute to a poor understanding of the present changes in the Arctic climate system, and also to a large spread in projections of future climate in the Arctic. The problem is exacerbated by the paucity of research-quality observations in the central Arctic. Improved formulations in climate models require such observations, which can only come from measurements in situ in this difficult-to-reach region with logistically demanding environmental conditions. The Arctic Summer Cloud Ocean Study (ASCOS) was the most extensive central Arctic Ocean expedition with an atmospheric focus during the International Polar Year (IPY) 2007–2008. ASCOS focused on the study of the formation and life cycle of low-level Arctic clouds. ASCOS departed from Longyearbyen on Svalbard on 2 August and returned on 9 September 2008. In transit into and out of the pack ice, four short research stations were undertaken in the Fram Strait: two in open water and two in the marginal ice zone. After traversing the pack ice northward, an ice camp was set up on 12 August at 87°21' N, 01°29' W and remained in operation through 1 September, drifting with the ice. During this time, extensive measurements were taken of atmospheric gas and particle chemistry and physics, mesoscale and boundary-layer meteorology, marine biology and chemistry, and upper ocean physics. ASCOS provides a unique interdisciplinary data set for development and testing of new hypotheses on cloud processes, their interactions with the sea ice and ocean and associated physical, chemical, and biological processes and interactions. For example, the first-ever quantitative observation of bubbles in Arctic leads, combined with the unique discovery of marine organic material, polymer gels with an origin in the ocean, inside cloud droplets suggests the possibility of primary marine organically derived cloud condensation nuclei in Arctic stratocumulus clouds. Direct observations of surface fluxes of aerosols could, however, not explain observed variability in aerosol concentrations, and the balance between local and remote aerosols sources remains open. Lack of cloud condensation nuclei (CCN) was at times a controlling factor in low-level cloud formation, and hence for the impact of clouds on the surface energy budget. ASCOS provided detailed measurements of the surface energy balance from late summer melt into the initial autumn freeze-up, and documented the effects of clouds and storms on the surface energy balance during this transition. In addition to such process-level studies, the unique, independent ASCOS data set can and is being used for validation of satellite retrievals, operational models, and reanalysis data sets.

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Alloy nanoparticles (NPs) of gold and palladium on ZrO2 support (Au–Pd@ZrO2) were found to be highly active in oxidation of benzyl alcohols and can be used for the tandem synthesis of imines from benzyl alcohols and amines via a one-pot, two-step process at mild reaction conditions. The first step of the process is oxidation of benzyl alcohol to benzaldehyde, excellent yields were achieved after 7 h reaction at 40 °C without addition of any base. In the second step, aniline was introduced into the reaction system to produced N-benzylideneaniline. The benzaldehyde obtained in the first step was completely consumed within 1 h. A range of benzyl alcohols and amines were investigated for the general applicability of the Au–Pd alloy catalysts. It is found that the performance of the catalysts depends on the Au–Pd metal contents and composition. The optimal catalyst is 3.0 wt% Au–Pd@ZrO2 with a Au:Pd molar ratio 1:1. The alloy NP catalyst exhibited superior catalytic properties to pure AuNP or PdNP because the surface of alloy NPs has higher charge heterogeneity than that of pure metal NPs according to simulation of density function theory (DFT)

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Objective: The aim of this study was to develop a model capable of predicting variability in the mental workload experienced by frontline operators under routine and nonroutine conditions. Background: Excess workload is a risk that needs to be managed in safety-critical industries. Predictive models are needed to manage this risk effectively yet are difficult to develop. Much of the difficulty stems from the fact that workload prediction is a multilevel problem. Method: A multilevel workload model was developed in Study 1 with data collected from an en route air traffic management center. Dynamic density metrics were used to predict variability in workload within and between work units while controlling for variability among raters. The model was cross-validated in Studies 2 and 3 with the use of a high-fidelity simulator. Results: Reported workload generally remained within the bounds of the 90% prediction interval in Studies 2 and 3. Workload crossed the upper bound of the prediction interval only under nonroutine conditions. Qualitative analyses suggest that nonroutine events caused workload to cross the upper bound of the prediction interval because the controllers could not manage their workload strategically. Conclusion: The model performed well under both routine and nonroutine conditions and over different patterns of workload variation. Application: Workload prediction models can be used to support both strategic and tactical workload management. Strategic uses include the analysis of historical and projected workflows and the assessment of staffing needs. Tactical uses include the dynamic reallocation of resources to meet changes in demand.

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Uncertainty assessments of herbicide losses from rice paddies in Japan associated with local meteorological conditions and water management practices were performed using a pesticide fate and transport model, PCPF-1, under the Monte Carlo (MC) simulation scheme. First, MC simulations were conducted for five different cities with a prescribed water management scenario and a 10-year meteorological dataset of each city. The effectiveness of water management was observed regarding the reduction of pesticide runoff. However, a greater potential of pesticide runoff remained in Western Japan. Secondly, an extended analysis was attempted to evaluate the effects of local water management and meteorological conditions between the Chikugo River basin and the Sakura River basin using uncertainty inputs processed from observed water management data. The results showed that because of more severe rainfall events, significant pesticide runoff occurred in the Chikugo River basin even when appropriate irrigation practices were implemented. © Pesticide Science Society of Japan.

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The stability of five illicit drug markers in wastewater was tested under different sewer conditions using laboratory-scale sewer reactors. Wastewater was spiked with deuterium labelled isotopes of cocaine, benzoyl ecgonine, methamphetamine, MDMA and 6-acetyl morphine to avoid interference from the native isotopes already present in the wastewater matrix. The sewer reactors were operated at 20 °C and pH 7.5, and wastewater was sampled at 0, 0.25, 0.5, 1, 2, 3, 6, 9 and 12 h to measure the transformation/degradation of these marker compounds. The results showed that while methamphetamine, MDMA and benzoyl ecgonine were stable in the sewer reactors, cocaine and 6-acetyl morphine degraded quickly. Their degradation rates are significantly higher than the values reportedly measured in wastewater alone (without biofilms). All the degradation processes followed first order kinetics. Benzoyl ecgonine and morphine were also formed from the degradation of cocaine and 6-acetyl morphine, respectively, with stable formation rates throughout the test. These findings suggest that, in sewage epidemiology, it is essential to have relevant information of the sewer system (i.e. type of sewer, hydraulic retention time) in order to accurately back-estimate the consumption of illicit drugs. More research is required to look into detailed sewer conditions (e.g. temperature, pH and ratio of biofilm area to wastewater volume among others) to identify their effects on the fate of illicit drug markers in sewer systems.

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Creatinine was proposed to be used as a population normalising factor in sewage epidemiology but its stability in the sewer system has not been assessed. This study thus aimed to evaluate the fate of creatinine under different sewer conditions using laboratory sewer reactors. The results showed that while creatinine was stable in wastewater only, it degraded quickly in reactors with the presence of sewer biofilms. The degradation followed first order kinetics with significantly higher rate in rising main condition than in gravity sewer condition. Additionally, daily loads of creatinine were determined in wastewater samples collected on Census day from 10 wastewater treatment plants around Australia. The measured loads of creatinine from those samples were much lower than expected and did not correlate with the populations across the sampled treatment plants. The results suggested that creatinine may not be a suitable biomarker for population normalisation purpose in sewage epidemiology, especially in sewer catchment with high percentage of rising mains.