• Membrane and Water Treatment
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• v.8 no.3
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• pp.279-292
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• 2017

This study was aimed at ultrafiltration (UF) as a pretreatment before reverse osmosis (RO) within the scheme of hybrid reverse osmosis-multistage flush (RO-MSF) desalination. Seawater at elevated temperature (after MSF heat-exchangers) was used as a feed in this process. The pretreatment system was represented as a set of functionally-linked technological segments such as: UF filtration, backwashing, chemical- enhanced backwashing, cleaning, waste disposal, etc. The process represents the sequences of operating cycles. The cycle, in turn, consists of the following unit operations: filtration, backwashing and chemical-enhanced backwashing (CEB). Quantitative assessment was based on the following indicators: normalized permeability, transmembrane pressure, specific energy and water consumption, specific waste generation. UF pre-treatment is accompanied by the following waste streams: $W1=1.19{\times}10$ power of $-2m^3$ (disposed NaOCl with 0.0044% wt.)/$m^3$ (filtrate); $W2=5.95{\times}10$ power of $-3m^3$ (disposed $H_2SO_4$ with 0.052% wt.)/$m^3$(filtrate); $W3=7.26{\times}10$ power of $-2m^3$ (disposed sea water)/$m^3$ (filtrate). Specific energy consumption is $1.11{\times}10$ power of $-1kWh/m^3$ (filtrate). The indicators evaluated over the cycles with conventional (non-chemical) backwashing were compared with the cycles accompanied by CEB. A positive impact of CEB on performance indicators was demonstrated namely: normalized UF resistance remains unchanged within the regime accompanied by CEB, whereas the lack of CEB results in 30% of its growth. Those quantitative indicators can be incorporated into the target function for solving different optimization problems. They can be used in the software for optimisation of operating regimes or in the synthesis of optimal flow- diagram. The cycle characteristics, process parameters and water quality data are attached.

• Advances in Computational Design
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• v.3 no.4
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• pp.367-384
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• 2018

The consideration of constructability issues at the design stage can lead to improved construction performance with smooth project delivery and savings in time and money. Empirical studies demonstrate the value obtained by integrating construction knowledge with the building design process, and its benefits for owners, contractors and designers. However, it is still a challenge to implement the concept into current design practice. There is a need for a decision support tool to aid designers in reviewing their design constructability, deploying current technological tools, such as BIM. Such tools are beneficial at the conceptual design stage when there is a room to improve the design significantly with less incurred cost. This research investigates how current process- and object-oriented models can be used to assess design constructability. It proposes a BIM-based model using embedded information within the design environment to conduct the assessment. The modelling framework is demonstrated in four key parts; namely, the conceptual design model, the constructability assessment model, the assessment process model and the decision-making phase. Each is associated with a set of components and functions that contribute towards the targeted constructability assessment outcomes. The proposed framework is the first to combine a numerical assessment system and a rule-based system, allowing for both quantitative and qualitative approaches. The modelling framework and its implementation through a prototype are described in this paper. It is believed that this framework is the first to enable users to transfer their construction knowledge and experience directly into a design platform linked to BIM models. The assessment criteria can be customised by the users who can reflect their own constructability preferences into various specialised profiles that can be added to the constructability assessment model. It also allows for the integration of the assessment process with the design phase, facilitating the optimisation of constructability performance from the early design stage.

• Smart Structures and Systems
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• v.15 no.6
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• pp.1393-1410
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• 2015

An original sensor system based on Fiber Bragg Gratings (FBG) for the strain monitoring of an adaptive wing element is presented in this paper. One of the main aims of the SARISTU project is in fact to measure the shape of a deformable wing for performance optimization. In detail, an Adaptive Trailing Edge (ATE) is monitored chord- and span-wise in order to estimate the deviation between the actual and the desired shape and, then, to allow attaining a prediction of the real aerodynamic behavior with respect to the expected one. The integration of a sensor system is not trivial: it has to fit inside the available room and to comply with the primary issue of the FBG protection. Moreover, dealing with morphing structures, large deformations are expected and a certain modulation is necessary to keep the measured strain inside the permissible measure range. In what follows, the mathematical model of an original FBG-based structural sensor system is presented, designed to evaluate the chord-wise strain of an Adaptive Trailing Edge device. Numerical and experimental results are compared, using a proof-of-concept setup. Further investigations aimed at improving the sensor capabilities, were finally addressed. The elasticity of the sensor structure was exploited to enlarge both the measurement and the linearity range. An optimisation process was then implemented to find out an optimal thickness distribution of the sensor system in order to alleviate the strain level within the referred component.

• Geophysics and Geophysical Exploration
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• v.9 no.1
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• pp.44-49
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• 2006

In this study, the resolution capabilities of electrical resistivity tomography (ERT) in the monitoring of $CO_2$ injection are investigated. The pole-pole and bipole-bipole electrode configuration types are used between two uncased boreholes straddling the $CO_2$ plume. Forward responses for an initial pre-injection model and three models for subsequent stages of $CO_2$ injection are calculated for the two different electrode configuration types, noise is added and the theoretical data are inverted with both L1- and L2-norm optimisation. The results show that $CO_2$ volumes over a certain threshold can be detected with confidence. The L1-norm proved superior to the L2-norm in most instances. Normalisation of the inverted models with the pre-injection inverse model gives good images of the regions of changing resistivity, and an integrated measure of the total change in resistivity proves to be a valid measure of the total injected volume.

• International Journal of Fluid Machinery and Systems
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• v.4 no.2
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• pp.271-288
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• 2011

The mathematical modelling of screw compressor processes and its implementation in their design began about 30 years ago with the publication of several pioneering papers on this topic, mainly at Purdue Compressor Conferences. This led to the gradual introduction of computer aided design, which, in turn, resulted in huge improvements in these machines, especially in oil-flooded air compressors, where the market is very competitive. A review of progress in such methods is presented in this paper together with their application in successful compressor designs. As a result of their introduction, even small details are now considered significant in efforts to improve performance and reduce costs. Despite this, there are still possibilities to introduce new methods and procedures for improved rotor profiles, design optimisation for each specified duty and specialized compressor design, all of which can lead to a better product and new areas of application. A review of methods and procedures which lead to modern screw compressor practice is presented in this paper. This paper is intended to give a cross section through activities being done in mathematical modelling of screw compressor process through last five decades. It is expected to serve as a basis for further contributions in the area and as a challenge to the forthcoming generations of scientists and engineers to concentrate their efforts in finding future and more extended approaches and submit their contributions.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.8
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• pp.4169-4172
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• 2012

Background: The majority of women in rural India have poor or no access to cervical cancer screening services, although one.quarter of all cervical cancers in the world occur there. Several large trials have proven the efficacy of low-tech cervical cancer screening methods in the Indian context but none have documented the necessary components and processes of implementing this evidence in a low-resource setting. Methods: This paper discusses a feasible model of implementation of cervical cancer screening programme in low-resource settings developed through a pilot research project carried out in rural Tamilnadu, India. The programme used visual inspection of cervix after acetic acid application (VIA) as a screening tool, nurses in the primary care centres as the primary screeners and peer educators within Self-Help Women groups to raise community awareness. Results: The uptake of screening was initially low despite the access to a screening programme. However, the programme witnessed an incremental increase in the number of women accessing screening with increasing community awareness. Conclusions: The investigators recommend 4 key components to programme implementation in low-resource setting: 1) Evidence-based, cost-effective test and treatment available within the reach of the community; 2) Appropriate referral pathways; 3) Skilled health workers and necessary equipment; and 4) Optimisation of health literacy, beliefs, attitudes of the community.

• The Journal of the Acoustical Society of Korea
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• v.13 no.1E
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• pp.55-63
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• 1994

A decision-theretic concept is introduced to investigate whether targets of interest in array sensor systems are present at some steering direction or not. The solutions to this problem are described as a set of discrete numbers 0 or 1 corresponding to the direction under consideration. This coded number representation is transplanted in the optimisation technique based on the Hopfield neural network, which may provide an easy understanding of determining the direction of arrival (DOA) of sources. Difficulties encountered in using the conventional state schemes of Hopfield neural network models are addressed and their related issues are raised. To deal with them, an idea that a neuron that decreases more energy difference for its state change of 0 to 1can have higher priority in the order of state transition than others is introduced. This does not only lead to an new state update scheme but also opens a different story in comparison to previous work. To cast the perspectives of the proposed approach and illustrate its effectiveness in source direction finding in array sensor system. simulation results and related discussions are presented in this paper.

• Proceedings of the Korean Vacuum Society Conference
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• 2014.02a
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• pp.253.2-253.2
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• 2014

Micro hollow cathode discharges (MHCDs) are high-pressure, non-equilibrium discharges. Those MHCDs are useful to produce an excimer radiation. A major advantage of excimer sources is their high internal efficiency which may reach values up to 40% when operated under optimum conditions. To produce strong excimer radiation, the optimisation of the discharge conditions however needs a detailed knowledge of the properties of the discharge plasma itself. The electron density and temperature influence the excitation as well as plasma chemistry reactions and the gas temperature plays a major role as a significant energy loss process limiting efficiency of excimer radiation. Most of the recent spectroscopic investigations are focusing on the ultraviolet or vacuum ultraviolet range for direct detection of the excimer. In our experiments we have concentrated on investigating the micro hollow cathodes from the near UV to the near infrared (300~850 nm) to measure the basic plasma parameters using standard plasma diagnostic techniques such as stark broadening for electron density and the relative line intensity method for electron temperature. Finally, the neutral gas temperature was measured by means of the vibrational rotational structures of the second positive system of nitrogen.

• Environmental Engineering Research
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• v.25 no.4
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• pp.479-487
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• 2020

Current assumptions are used in the formulation of pseudo-first (PFO) and second-order (PSO) models to describe the kinetic data of filtration based on ideal operating conditions. This paper presents a new model developed with pseudo n^th order and based on real assumption. A comparison was performed between PFO, PSO and the new model to highlight their performance and the optimisation of the pseudo-order equation, using MATLAB software. Adsorption characteristic of bovine serum albumin adsorption on the track-etched membrane are used as a medium based on protein filtration data were extracted from the literature for different concentrations to demonstrate the comparison between PFO/PSO and the new model. The pseudo first and second-order kinetic models were applied to test the experimental data and they did not provide reasonable values. The results show that the predicted values are consistent with experimental values giving a good correlation coefficient R² = 0.997 and a minimum root mean squared error RMSE = 0.0171. Indeed, the experimental results follow the new model and the optimal pseudo equation order n = 1.115, the most suitable curves for the new model. As a result, we used different experimental adsorption data from the literature to examine and check the applicability and validity of the model.

• Journal of Korea Society of Digital Industry and Information Management
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• v.12 no.1
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• pp.1-12
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• 2016

The current economic crisis is making new demands on manufacturing industry, in particular, in terms of the flexibility and efficiency of production processes. This requires production and administrative processes to be meshed with each other by means of IT systems to optimise the use and capacity utilisation of machines and lines but also to be able to respond rapidly to wrong developments in production and thus to minimise adverse impacts on the business. The future scenario of the "smart factory" represents the zenith of this development. The factory can be modified and expanded at will, combines all components from different manufacturers and enables them to take on context-related tasks autonomously. Integrated user interfaces will still be required at most for basic functionalities. The complex control operations will run wirelessly and ad hoc via mobile terminals such as PDAs or smartphones. The comnination of IoT, and Big Data optimisation is bringing about huge opportunities. these processes are not just limited to manufacturing, anywhere a supply chain environment exists can benefit from information provided by linked devices and access to big data to inform their decision support. Building a smart factory with smart assets at its core means reaching those desired new levels of productivity and efficiency. It means smart products that leverage advanced traceability, connectivity and intelligence. For businesses, it means being able to address the talent crunch through more autonomous. In a Smart Factory, machinery and equipment will have the ability to improve processes through self-optimization and autonomous decision-making.