Search results for: production process optimization

Authors: Yi Jin, Xu Tang, Cuiyang Feng

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The ‘11th five-year’ and ‘12th five-year’ plans have clearly put forward to strictly control the total amount and intensity of energy and water consumption. The synergy effect of energy and water has rarely been considered in the process of energy and water saving in China, where its contribution cannot be maximized. Energy sectors consume large amounts of energy and water when producing massive energy, which makes them both energy and water intensive. Therefore, the synergy effect in these sectors is significant. This paper assesses and optimizes the synergy effect in three energy sectors under the background of promoting energy and water saving. Results show that: From the perspective of critical path, chemical industry, mining and processing of non-metal ores and smelting and pressing of metals are coupling points in the process of energy and water flowing to energy sectors, in which the implementation of energy and water saving policies can bring significant synergy effect. Multi-objective optimization shows that increasing efforts on input restructuring can effectively improve synergy effects; relatively large synergetic energy saving and little water saving are obtained after solely reducing the energy and water intensity of coupling sectors. By optimizing the input structure of sectors, especially the coupling sectors, the synergy effect of energy and water saving can be improved in energy sectors under the premise of keeping economy running stably.

Keywords: critical path, energy sector, multi-objective optimization, synergy effect, water

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Authors: Mohammad Reza Esmaili

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One of the most important parts of the restoration process of a power network is the synchronizing of its subsystems. In this situation, the biggest concern of the system operators will be the reduction of the standing phase angle (SPA) between the endpoints of the two islands. In this regard, the system operators perform various actions and maneuvers so that the synchronization operation of the subsystems is successfully carried out and the system finally reaches acceptable stability. The most common of these actions include load control, generation control and, in some cases, changing the network topology. Although these maneuvers are simple and common, due to the weak network and extreme load changes, the restoration will be associated with low speed. One of the best ways to control the SPA is to use FACTS devices. By applying a soft control signal, these tools can reduce the SPA between two subsystems with more speed and accuracy, and the synchronization process can be done in less time. Meanwhile, the unified power controller (UPFC), a series-parallel compensator device with the change of transmission line power and proper adjustment of the phase angle, will be the proposed option in order to realize the subject of this research. Therefore, with the optimal placement of UPFC in a power system, in addition to improving the normal conditions of the system, it is expected to be effective in reducing the SPA during power system restoration. Therefore, the presented paper provides an optimal structure to coordinate the three problems of improving the division of subsystems, reducing the SPA and optimal power flow with the aim of determining the optimal location of UPFC and optimal subsystems. The proposed objective functions in this paper include maximizing the quality of the subsystems, reducing the SPA at the endpoints of the subsystems, and reducing the losses of the power system. Since there will be a possibility of creating contradictions in the simultaneous optimization of the proposed objective functions, the structure of the proposed optimization problem is introduced as a non-linear multi-objective problem, and the Pareto optimization method is used to solve it. The innovative technique proposed to implement the optimization process of the mentioned problem is an optimization algorithm called the water cycle (WCA). To evaluate the proposed method, the IEEE 39 bus power system will be used.

Keywords: UPFC, SPA, water cycle algorithm, multi-objective problem, pareto

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Authors: James M. Wakiru, Liliane Pintelon, Peter Muchiri, Peter Chemweno

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The fast-changing business and operational environment are forcing organizations to adopt asset performance management strategies, not only to reduce costs but also maintain operational and production policies while addressing demand. To attain optimal asset performance management, a framework that ensures a continuous and systematic approach to analyzing an organization’s current maturity level and expected improvement regarding asset maintenance processes, strategies, technologies, capabilities, and systems is essential. Moreover, this framework while addressing maintenance-intensive organizations should consider the diverse business, operational and technical context (often dynamic) an organization is in and realistically prescribe or relate to the appropriate tools and systems the organization can potentially employ in the respective level, to improve and attain their maturity goals. This paper proposes an asset maintenance maturity model to assess the current capabilities, strength and weaknesses of maintenance processes an organization is using and analyze gaps for improvement via structuring set levels of achievement. At the epicentre of the proposed framework is the utilization of maintenance objective selected by an organization for various maintenance optimization programs. The framework adapts the Capability Maturity Model of assessing the maintenance process maturity levels in the organization.

Keywords: asset maintenance, maturity models, maintenance objectives, optimization

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Authors: Joy Marie Mora, Mark Daniel De Luna, Tsair-Wang Chung

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Transesterification reaction of soybean oil with methanol was carried out to produce fatty acid methyl esters (FAME) using calcined alkali metal (Na and Li) supported by pumice silica as the solid base catalyst. Pumice silica catalyst was activated by loading alkali metal ions to its surface via an ion-exchange method. Response surface methodology (RSM) in combination with Box-Behnken design (BBD) was used to optimize the operating parameters in biodiesel production, namely: reaction temperature, methanol to oil molar ratio, reaction time, and catalyst concentration. Using the optimized sets of parameters, FAME yields using sodium and lithium silicate catalysts were 98.80% and 98.77%, respectively. A pseudo-first order kinetic equation was applied to evaluate the kinetic parameters of the reaction. The prepared catalysts were characterized by several techniques such as X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), Brunauer-Emmett-Teller (BET) sorptometer, and scanning electron microscopy (SEM). In addition, the reusability of the catalysts was successfully tested in two subsequent cycles.

Keywords: alkali metal, biodiesel, Box-Behnken design, heterogeneous catalyst, kinetics, optimization, pumice, transesterification

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Authors: Amara Prakasa Rao, N. V. S. N. Sarma

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This paper describes the synthesis of linear array geometry with minimum sidelobe level and null control using the Taguchi method. Based on the concept of the orthogonal array, Taguchi method effectively reduces the number of tests required in an optimization process. Taguchi method has been successfully applied in many fields such as mechanical, chemical engineering, power electronics, etc. Compared to other evolutionary methods such as genetic algorithms, simulated annealing and particle swarm optimization, the Taguchi method is much easier to understand and implement. It requires less computational/iteration processing to optimize the problem. Different cases are considered to illustrate the performance of this technique. Simulation results show that this method outperforms the other evolution algorithms (like GA, PSO) for smart antenna systems design.

Keywords: array factor, beamforming, null placement, optimization method, orthogonal array, Taguchi method, smart antenna system

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Authors: Nixon Kuruvila, H. V. Ravindra

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Wire-cut Electro Discharge Machining (WEDM) is a special form of conventional EDM process in which electrode is a continuously moving conductive wire. The present study aims at determining parametric influence and optimum process parameters of Wire-EDM using Taguchi’s Technique and Genetic algorithm. The variation of the performance parameters with machining parameters was mathematically modeled by Regression analysis method. The objective functions are Dimensional Accuracy (DA) and Material Removal Rate (MRR). Experiments were designed as per Taguchi’s L16 Orthogonal Array (OA) where in Pulse-on duration, Pulse-off duration, Current, Bed-speed and Flushing rate have been considered as the important input parameters. The matrix experiments were conducted for the material Oil Hardened Non Shrinking Steel (OHNS) having the thickness of 40 mm. The results of the study reveals that among the machining parameters it is preferable to go in for lower pulse-off duration for achieving over all good performance. Regarding MRR, OHNS is to be eroded with medium pulse-off duration and higher flush rate. Finally, the validation exercise performed with the optimum levels of the process parameters. The results confirm the efficiency of the approach employed for optimization of process parameters in this study.

Keywords: dimensional accuracy (DA), regression analysis (RA), Taguchi method (TM), volumetric material removal rate (VMRR)

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Authors: A. Samer Ezeldin, Sarah A. Fotouh

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Optimization of resources is very important in all fields, as in construction management. Project managers have to face problems regarding management of cost, time and available resources of single projects and more problems arise when managing multiple projects. Most of the studies focused on optimization of resources for a single project, but, this paper will discuss the design and modeling of multiple resources optimization for multiple projects using Genetic Algorithm. Most of the companies in construction industry optimize the resources for single projects only, but with the presence of several mega projects in several developing countries running at the same time, there is a need for a model to enhance the efficiency of available resources and decreases the fluctuation as much as possible. The proposed model calculates the cost of each resource, tries to minimize the cost of extra resources as much as possible and generates the schedule of each project within a selected program.

Keywords: construction management, genetic algorithm, multiple projects, multiple resources, optimization

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Authors: Abate Getnet Demisash, Beshatu Taye Hatew, Ababo Geleta Gudisa

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As consumption trends of fish are rising in Ethiopia, assessment of the environmental performance of Fisheries becomes vital. Hence, Cleaner Production Assessment was conducted on Lake Tana No.1 Fish Supply Association. This paper focuses on determining the characteristics, quantity and setting up cleaner production option for the site with experimental investigation. The survey analysis showed that illegal waste dumping in Lake Tana is common practice in the area and some of the main reasons raised were they have no option than doing this for discharging fish wastes. Quantifying a fish waste by examination of records at the point of generation resulted in generation rate of 72,822.61 kg per year which is a significant amount of waste and needs management system. The result of the proximate analysis showed high free fat content of about 12.33% and this was a good candidate for the production of biodiesel that has been set as an option for fish waste utilization. Among the different waste management options, waste reduction by product optimization which involves biodiesel production was chosen as a potential method. Laboratory scale experiments were performed to produce renewable energy source from the wastes. The resulting biodiesel was characterized and found to have a density of 0.756kg/L, viscosity 0.24p and 153°C flash points which shows the product has values in compliance with American Society for Testing and Materials (ASTM) standards.

Keywords: biodiesel, cleaner production, renewable energy, clean energy, waste to energy

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Authors: Shashank Tiwari, S. P. Mahapatra

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The aim of this technique is to reduce the steps of process scales up, save time & cost of the industries. This technique will minimise the steps of process scale up. The new steps are, Novel Lab Scale, Novel Lab Scale Trials, Novel Trial Batches, Novel Exhibit Batches, Novel Validation Batches. In these steps, it is not divided to validation batches in three parts but the data of trials batches, Exhibit Batches and Validation batches are use and compile for production and used for validation. It also increases the batch size of the trial, exhibit batches. The new size of trials batches is not less than fifty Thousand, the exhibit batches increase up to two lack and the validation batches up to five lack. After preparing the batches all their data & drugs use for stability & maintain the validation record and compile data for the technology transfer in production department for preparing the marketed size batches.

Keywords: batches, technique, preparation, scale up, validation

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Authors: Di Han, Lingfeng Li, Peixue Zhang, Yuzhuo Zhang

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Since natural gas extracted from the wellhead of a gas well, after passing through the throttle valve, causes a rapid decrease in temperature along with a decrease in pressure, which creates conditions for hydrate generation. In order to solve the problem of hydrate generation in the process of wellhead gathering, effective measures should be taken to prevent hydrate generation. In this paper, we firstly introduce the principle of natural gas throttling temperature drop and the theoretical basis of hydrate inhibitor injection calculation, and then use HYSYS software to simulate and calculate the three processes and determine the key process parameters. The hydrate control process applicable to the skid design of natural gas wellhead gathering skids was determined by comparing the hydrate control effect, energy consumption of key equipment and process adaptability.

Keywords: natural gas, hydrate control, skid design, HYSYS

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Authors: Indu Bhushan Sharma, Rashmi Saraswat

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The thermotolerant, solvent stable and alkalophilic lipase producing bacterial strain was isolated from the water sample of the foothills of Trikuta Mountain in Kakryal (Reasi district) in Jammu and Kashmir, India. The lipase-producing microorganisms were screened using tributyrin agar plates. The selected microbe was optimized for maximum lipase production by subjecting to various carbon and nitrogen sources, incubation period and inoculum size. The selected strain was identified as Bacillus subtilis strain kakrayal_1 (BSK_1) using 16S rRNA sequence analysis. Effect of pH, temperature, metal ions, detergents and organic solvents were studied on lipase activity. Lipase was found to be stable over a pH range of 6.0 to 9.0 and exhibited maximum activity at pH 8. Lipolytic activity was highest at 37°C and the enzyme activity remained at 60°C for 24hrs, hence, established as thermo-tolerant. Production of lipase was significantly induced by vegetable oil and the best nitrogen source was found to be peptone. The isolated Bacillus lipase was stimulated by pre-treatment with Mn2+, Ca2+, K+, Zn2+, and Fe2+. Lipase was stable in detergents such as triton X 100, tween 20 and Tween 80. The 100% ethyl acetate enhanced lipase activity whereas, lipase activity were found to be stable in Hexane. The optimization resulted in 4 fold increase in lipase production. Bacillus lipases are ‘generally recognized as safe’ (GRAS) and are industrially interesting. The inducible alkaline, thermo-tolerant lipase exhibited the ability to be stable in detergents and organic solvents. This could be further researched as a potential biocatalyst for industrial applications such as biotransformation, detergent formulation, bioremediation and organic synthesis.

Keywords: bacillus, lipase, thermotolerant, alkalophilic

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Authors: Siri Marthe Arbo, Afaf Saai, Sture Sørli, Mette Nedreberg

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This work aims to establish a reliable approach for optimizing a Laser Metal Deposition (LMD) process for a critical maritime component, based on the material properties and structural performance required by the maritime industry. The component of interest is a water jet impeller, for which specific requirements for material properties are defined. The developed approach is based on the assessment of the effects of LMD process parameters on microstructure and material performance of standard AM 2205 duplex stainless steel powder. Duplex stainless steel offers attractive properties for maritime applications, combining high strength, enhanced ductility and excellent corrosion resistance due to the specific amounts of ferrite and austenite. These properties are strongly affected by the microstructural characteristics in addition to microstructural defects such as porosity and welding defects, all strongly influenced by the chosen LMD process parameters. In this study, the influence of deposition speed and heat input was evaluated. First, the influences of deposition speed and heat input on the microstructure characteristics, including ferrite/austenite fraction, amount of porosity and welding defects, were evaluated. Then, the achieved mechanical properties were evaluated by standard testing methods, measuring the hardness, tensile strength and elongation, bending force and impact energy. The measured properties were compared to the requirements of the water jet impeller. The results show that the required amounts of ferrite and austenite can be achieved directly by the LMD process without post-weld heat treatments. No intermetallic phases were observed in the material produced by the investigated process parameters. A high deposition speed was found to reduce the ductility due to the formation of welding defects. An increased heat input was associated with reduced strength due to the coarsening of the ferrite/austenite microstructure. The microstructure characterizations and measured mechanical performance demonstrate the great potential of the LMD process and generate a valuable database for the optimization of the LMD process for duplex stainless steels.

Keywords: duplex stainless steel, laser metal deposition, process optimization, microstructure, mechanical properties

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Authors: Badr M. Alshammari, T. Guesmi

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In this paper, the concept of a non-dominated sorting multi-objective particle swarm optimization with local search (NSPSO-LS) is presented for the optimal design of multimachine power system stabilizers (PSSs). The controller design is formulated as an optimization problem in order to shift the system electromechanical modes in a pre-specified region in the s-plan. A composite set of objective functions comprising the damping factor and the damping ratio of the undamped and lightly damped electromechanical modes is considered. The performance of the proposed optimization algorithm is verified for the 3-machine 9-bus system. Simulation results based on eigenvalue analysis and nonlinear time-domain simulation show the potential and superiority of the NSPSO-LS algorithm in tuning PSSs over a wide range of loading conditions and large disturbance compared to the classic PSO technique and genetic algorithms.

Keywords: multi-objective optimization, particle swarm optimization, power system stabilizer, low frequency oscillations

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Authors: Gagandeep Singh

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The sensor field optimization is a serious issue in WSNs and has been ignored by many researchers. As in numerous real-time sensing fields the sensor nodes on the corners i.e. on the segment boundaries will become lifeless early because no extraordinary safety is presented for them. Accordingly, in this research work the central objective is on the segment based optimization by separating the sensor field between advance and normal segments. The inspiration at the back this sensor field optimization is to extend the time spam when the first sensor node dies. For the reason that in normal sensor nodes which were exist on the borders may become lifeless early because the space among them and the base station is more so they consume more power so at last will become lifeless soon.

Keywords: WSNs, ECRSEP, SEP, field optimization, energy

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Authors: Carolina Zambrana, Grover Zurita

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The food loss production that occurs in deficient agricultural production is one of the major problems worldwide. This puts the population's food security and the efficiency of farming investments at risk. It is to be expected that this food security will be achieved with the own and efficient production of each country. It will have an impact on the well-being of its population and, thus, also on food sovereignty. The production losses in quantity and quality occur due to the lack of efficient detection of diseases at an early stage. It is very difficult to solve the agriculture efficiency using traditional methods since it takes a long time to be carried out due to detection imprecision of the main diseases, especially when the production areas are extensive. Therefore, the main objective of this research study is to perform a systematic literature review, of the latest five years, of Precision Agriculture (PA) to be able to understand the state of the art of the set of new technologies, procedures, and optimization processes with Artificial Intelligence (AI). This study will focus on Corns, Potatoes, and Rice diagnostic diseases. The extensive literature review will be performed on Elsevier, Scopus, and IEEE databases. In addition, this research will focus on advanced digital imaging processing and the development of software and hardware for PA. The convolution neural network will be handling special attention due to its outstanding diagnostic results. Moreover, the studied data will be incorporated with artificial intelligence algorithms for the automatic diagnosis of crop quality. Finally, precision agriculture with technology applied to the agricultural sector allows the land to be exploited efficiently. This system requires sensors, drones, data acquisition cards, and global positioning systems. This research seeks to merge different areas of science, control engineering, electronics, digital image processing, and artificial intelligence for the development, in the near future, of a low-cost image measurement system that allows the optimization of crops with AI.

Keywords: precision agriculture, convolutional neural network, deep learning, artificial intelligence

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Authors: Tie-Qing Zhang, Seunghun Jung, Young-Bae Kim

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This research is devoted to developing a membrane reactor to flexibly meet the hydrogen demand of onboard fuel cells, which is an important part of green energy development. Among many renewable chemical products, dimethyl ether (DME) has the advantages of low reaction temperature (400 °C in this study), high hydrogen atom content, low toxicity, and easy preparation. Autothermal reforming, on the other hand, has a high hydrogen recovery rate and exhibits thermal neutrality during the reaction process, so the additional heat source in the hydrogen production process can be omitted. Therefore, the DME auto thermal reforming process was adopted in this study. To control the temperature of the reaction catalyst bed and hydrogen production rate, a Model Predictive Control (MPC) scheme was designed. Taking the above two variables as the control objectives, stable operation of the reformer can be achieved by controlling the flow rates of DME, steam, and high-purity air in real-time. To prevent catalyst poisoning in the fuel cell, the hydrogen needs to be purified to reduce the carbon monoxide content to below 50 ppm. Therefore, a Pd-Ag hydrogen semi-permeable membrane with a thickness of 3-5 μm was inserted into the auto thermal reactor, and the permeation efficiency of hydrogen was improved by steam purging on the permeation side. Finally, hydrogen with a purity of 99.99 was obtained.

Keywords: hydrogen production, auto thermal reforming, membrane, fuel cell

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Authors: Saad M. Darwish

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Recently, software quality issues have come to be seen as important subject as we see an enormous growth of agencies involved in software industries. However, these agencies cannot guarantee the quality of their products, thus leaving users in uncertainties. Software certification is the extension of quality by means that quality needs to be measured prior to certification granting process. This research participates in solving the problem of software assessment by proposing a model for assessment and certification of software product that uses a fuzzy inference engine to integrate both of process–driven and application-driven quality assurance strategies. The key idea of the on hand model is to improve the compactness and the interpretability of the model’s fuzzy rules via employing an ant colony optimization algorithm (ACO), which tries to find good rules description by dint of compound rules initially expressed with traditional single rules. The model has been tested by case study and the results have demonstrated feasibility and practicability of the model in a real environment.

Keywords: software quality, quality assurance, software certification model, software assessment

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Authors: D. S. Nagesh, G. L. Datta

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In the field of welding, various studies had been made by some of the previous investigators to predict as well as optimize weld bead geometric descriptors. Modeling of weld bead shape is important for predicting the quality of welds. In most of the cases, design of experiments technique to postulate multiple linear regression equations have been used. Nowadays, Genetic Algorithm (GA) an intelligent information treatment system with the characteristics of treating complex relationships as seen in welding processes used as a tool for inverse mapping/optimization of the process is attempted.

Keywords: smaw, genetic algorithm, bead geometry, optimization/inverse mapping

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Authors: D. S. Nagesh, G. L. Datta

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In the field of welding, various studies had been made by some of the previous investigators to predict as well as optimize weld bead geometric descriptors. Modeling of weld bead shape is important for predicting the quality of welds. In most of the cases design of experiments technique to postulate multiple linear regression equations have been used. Nowadays Genetic Algorithm (GA) an intelligent information treatment system with the characteristics of treating complex relationships as seen in welding processes used as a tool for inverse mapping/optimization of the process is attempted.

Keywords: SMAW, genetic algorithm, bead geometry, optimization/inverse mapping

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Authors: Shoumodip Roy, Ankit Singhania, M. K. G. Choudhury, Santanu Mallick, M. K. Agarwal, R. V. Ramna, Uttam Singh

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One of the key corporate goals of Tata Steel company is to demonstrate Environment Leadership. Decreasing specific CO₂ emission is one of the key steps to achieve the stated corporate goal. At any Blast Furnace, specific CO₂ emission is directly proportional to fuel intake. To reduce the fuel intake at G Blast Furnace, an initial benchmarking exercise was carried out with international and domestic Blast Furnaces to determine the potential for improvement. The gap identified during the exercise revealed that the benchmark Blast Furnaces operated with superior raw material quality than that in G Blast Furnace. However, since the raw materials to G Blast Furnace are sourced from the captive mines, improvement in the raw material quality was out of scope. Therefore, trials were taken with different operating regimes, to identify the key process parameters, which on optimization could significantly reduce the fuel intake in G Blast Furnace. The key process parameters identified from the trial were the Stoichiometric Oxygen Ratio, Melting Capacity ratio and the burden distribution inside the furnace. These identified process parameters were optimized to bridge the gap in fuel intake at G Blast Furnace, thereby reducing specific CO₂ emission to benchmark levels. This paradigm shift enabled to lower the fuel intake by 70kg per ton of liquid iron produced, thereby reducing the specific CO₂ emission by 15 percent.

Keywords: benchmark, blast furnace, CO₂ emission, fuel rate

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Authors: A. Chatel, I. S. Torreguitart, T. Verstraete

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The paper deals with a single point optimization of the LS89 turbine using an adjoint optimization and defining the design variables within a CAD system. The advantage of including the CAD model in the design system is that higher level constraints can be imposed on the shape, allowing the optimized model or component to be manufactured. However, CAD-based approaches restrict the design space compared to node-based approaches where every node is free to move. In order to preserve a rich design space, we develop a methodology to refine the CAD model during the optimization and to create the best parameterization to use at each time. This study presents a methodology to progressively refine the design space, which combines parametric effectiveness with a differential evolutionary algorithm in order to create an optimal parameterization. In this manuscript, we show that by doing the parameterization at the CAD level, we can impose higher level constraints on the shape, such as the axial chord length, the trailing edge radius and G2 geometric continuity between the suction side and pressure side at the leading edge. Additionally, the adjoint sensitivities are filtered out and only smooth shapes are produced during the optimization process. The use of algorithmic differentiation for the CAD kernel and grid generator allows computing the grid sensitivities to machine accuracy and avoid the limited arithmetic precision and the truncation error of finite differences. Then, the parametric effectiveness is computed to rate the ability of a set of CAD design parameters to produce the design shape change dictated by the adjoint sensitivities. During the optimization process, the design space is progressively enlarged using the knot insertion algorithm which allows introducing new control points whilst preserving the initial shape. The position of the inserted knots is generally assumed. However, this assumption can hinder the creation of better parameterizations that would allow producing more localized shape changes where the adjoint sensitivities dictate. To address this, we propose using a differential evolutionary algorithm to maximize the parametric effectiveness by optimizing the location of the inserted knots. This allows the optimizer to gradually explore larger design spaces and to use an optimal CAD-based parameterization during the course of the optimization. The method is tested on the LS89 turbine cascade and large aerodynamic improvements in the entropy generation are achieved whilst keeping the exit flow angle fixed. The trailing edge and axial chord length, which are kept fixed as manufacturing constraints. The optimization results show that the multilevel optimizations were more efficient than the single level optimization, even though they used the same number of design variables at the end of the multilevel optimizations. Furthermore, the multilevel optimization where the parameterization is created using the optimal knot positions results in a more efficient strategy to reach a better optimum than the multilevel optimization where the position of the knots is arbitrarily assumed.

Keywords: adjoint, CAD, knots, multilevel, optimization, parametric effectiveness

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Authors: Weiwei Xie, Yichao Li

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The initial installation of the umbilical can affect the subsequent installation process and final installation. Meanwhile, the design of both ends of the ultra-deep water dynamic umbilical (UDWDU), as well as the design of the surface unit and the subsea production system connected by UDWDU,], varies in different oil and gas fields. To optimize the installation process of UDWDU, on the basis of the summary and analysis of the surface-end and the subsea-end design of UDWDU and the mainstream construction resources, the method of initial installation from the surface unit side or the subsea production system side of UDWDU is studied, and each initiation installation method is pointed out if some difficulties that may be encountered.

Keywords: dynamic umbilical, ultra-deep-water, initial installation, installation process

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Authors: H. Ghodbane, A. A. Taleb, O. Kraa

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This paper presents geometric design of induction heating system. The objective of this design is to improve the temperature distribution in the load. The study of such a device requires the use of models or modeling representation, physical, mathematical, and numerical. This modeling is the basis of the understanding, the design, and optimization of these systems. The optimization technique is to find values of variables that maximize or minimize the objective function.

Keywords: optimization, modeling, geometric design system, temperature increase

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Authors: Abiodun Ladanu Ajala, Wuyi Oke

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Mathematical simulation and optimization models packaged within interactive computer programs provide a common way for planners and managers to predict the behaviour of any proposed water resources system design or management policy before it is implemented. Modeling presents a principal technique of predicting the behaviour of the proposed infrastructural designs or management policies. Models can be developed and used to help identify specific alternative plans that best meet those objectives. This study discusses various types of models, their development, architecture, data requirements, and applications in the field of engineering. It also outlines the advantages and limitations of each the optimization and simulation models presented. The techniques explored in this review include; dynamic programming, linear programming, fuzzy optimization, evolutionary algorithms and finally artificial intelligence techniques. Previous studies carried out using some of the techniques mentioned above were reviewed, and most of the results from different researches showed that indeed optimization and simulation provides viable alternatives and predictions which form a basis for decision making in building engineering structures and also in engineering planning and management.

Keywords: linear programming, mutation, optimization, simulation

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Authors: Dharmit Viroja, Prerakkumar Shah, Rajanikant Gajera, Ruchit Shah

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With present scenario of aging oil and gas fields with high water cuts, volatile oil prices and increasing greenhouse gas emission, the need for alleviating such issues has necessitated for oil and gas industry to make the maximum out of available assets, infrastructure and reserves in mother Earth. Study undertaken emphasizes on utilizing Geothermal Energy under specific reservoir conditions for Enhanced oil Recovery (EOR) to boost up production. Allied benefits of this process include mitigation of electricity problem in remote fields and controlled CO-emission. Utilization of this energy for EOR and increasing economic life of field could surely be rewarding. A new way to value oil lands would be considered if geothermal co-production is integrated in the field development program. Temperature profile of co-produced fluid across its journey is a pivotal issue which has been studied. Geo pressured reservoirs resulting from trapped brine under an impermeable bed is also a frontier for exploitation. Hot geothermal fluid is a by-product of large number of oil and gas wells, historically this hot water has been seen as an inconvenience; however, it can be looked at as a useful resource. The production of hot fluids from abandoned and co-production of hot fluids from producing wells has potential to prolong life of oil and gas fields. The study encompasses various factors which are required for use of this technology and application of this process across various phases of oil and gas value chain. Interdisciplinary approach in oil and gas value chain has shown potential for economic production of estimated oil and gas reserves.

Keywords: enhanced oil recovery, geo-pressured reservoirs, geothermal energy, oil and gas value chain

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Authors: Rashid S. Mohammad, Shicheng Zhang, Sun Lu, Syed Jamal-Ud-Din, Xinzhe Zhao

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A compositional reservoir simulation model (CMG-GEM) was used for cyclic CO₂ injection process in unconventional tight reservoir. Cyclic CO₂ injection is an enhanced oil recovery process consisting of injection, shut-in, and production. The study of cyclic CO₂ injection and hydrocarbon recovery in ultra-low permeability reservoirs is mainly a function of rock, fluid, and operational parameters. CMG-GEM was used to study several design parameters of cyclic CO₂ injection process to distinguish the parameters with maximum effect on the oil recovery and to comprehend the behavior of cyclic CO₂ injection in tight reservoir. On the other hand, permeability reduction induced by asphaltene precipitation is one of the major issues in the oil industry due to its plugging onto the porous media which reduces the oil productivity. In addition to asphaltene deposition, solubility of CO₂ in the aquifer is one of the safest and permanent trapping techniques when considering CO₂ storage mechanisms in geological formations. However, the effects of the above uncertain parameters on the process of CO₂ enhanced oil recovery have not been understood systematically. Hence, it is absolutely necessary to study the most significant parameters which dominate the process. The main objective of this study is to improve techniques for designing cyclic CO₂ injection process while considering the effects of asphaltene deposition and solubility of CO₂ in the brine in order to prevent asphaltene precipitation, minimize CO₂ emission, optimize cyclic CO₂ injection, and maximize oil production.

Keywords: tight reservoirs, cyclic O₂ injection, asphaltene, solubility, reservoir simulation

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Authors: Xiaojing Gao, James Njuguna

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This paper emphasizes the importance of integrating project management and systems engineering for innovative system design and production development. The research highlights the need for a flexible approach that unifies these disciplines, as their isolation often leads to communication challenges and complexity within multidisciplinary teams. The paper aims to elucidate the intricate relationship between project management and systems engineering, recommending the consolidation of engineering disciplines into a single lifecycle for improved support of the design and development process. The research identifies a synergy between these disciplines, focusing on streamlining information communication during product design and development. The insights gained from this process can lead to product design optimization. Additionally, the paper introduces a proposed Project Management-Based Systems Engineering (PMBSE) framework, emphasizing effective communication, efficient processes, and advanced tools to enhance product development outcomes within the product lifecycle.

Keywords: system engineering, product design and development, project management, cross-disciplinary

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Authors: Pulak Swain, A. K. Ojha

Abstract:

Portfolio optimization is based on dealing with the problems of efficient asset allocation. Risk and Expected return are two conflicting criteria in such problems, where the investor prefers the return to be high and the risk to be low. Using multi-objective approach we can solve those type of problems. However the information which we have for the input parameters are generally ambiguous and the input values can fluctuate around some nominal values. We can not ignore the uncertainty in input values, as they can affect the asset allocation drastically. So we use Robust Optimization approach to the problems where the input parameters comes under box uncertainty. In this paper, we solve the multi criteria robust problem with the help of  E- constraint method.

Keywords: portfolio optimization, multi-objective optimization, ϵ - constraint method, box uncertainty, robust optimization

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Authors: Lela Pintarić, Iva Rezić, Ana Vrsalović Presečki

Abstract:

Considering an enormous increase of the use of metal nanoparticles with the exactly defined characteristics, the main goal of this research was to found the optimal and environmental friendly method of their synthesis. The synthesis of the inorganic core-shell nanoparticles was optimized as a model. The core-shell nanoparticles are composed of the enzyme core belted with the metal ions, oxides or salts as a shell. In this research, enzyme urease was the core catalyst and the shell nanoparticle was made of silver. Silver nanoparticles are widespread utilized and some of their common uses are: as an addition to disinfectants to ensure an aseptic environment for the patients, as a surface coating for neurosurgical shunts and venous catheters, as an addition to implants, in production of socks for diabetics and athletic clothing where they improve antibacterial characteristics, etc. Characteristics of synthesized nanoparticles directly depend on of their size, so the special care during this optimization was given to the determination of the size of the synthesized nanoparticles. For the purpose of the above mentioned optimization, sixteen experiments were generated by the Design of Experiments (DoE) method and conducted under various temperatures, with different initial concentration of the silver nitrate and constant concentration of the urease of two separate manufacturers. Synthesized nanoparticles were analyzed by the Nanoparticle Tracking Analysis (NTA) method on Malvern NanoSight NS300. Results showed that the initial concentration of the silver ions does not affect the concentration of the synthesized silver nanoparticles neither their size distribution. On the other hand, temperature of the experiments has affected both of the mentioned values.

Keywords: core-shell nanoparticles, optimization, silver, urease

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Authors: Sidra Shaheen, Nadir Naveed Siddiqui, Shah Ali Ul Qader

Abstract:

In recent years, significant progress has been made in discovering and developing new bacterial polysaccharides producing organisms possessing extremely functional properties. Levan is a natural biopolymer of fructose which is produced by transfructosylation reaction in the presence of levansucrase. It is one of the industrially promising enzymes that offer a variety of industrial applications in the field of cosmetics, foods and pharmaceuticals. Although levan has significant applications but the yield of levan produced is not equal to other biopolymers due to the inefficiency of producer microorganism. Among wide range of levansucrase producing microorganisms, Zymomonas mobilis is considered as a potential candidate for large scale production of this natural polysaccharide. The present investigation is concerned with the isolation of levansucrase producing natural isolate having maximum enzyme production. Furthermore, production parameters were optimized to get higher enzyme yield. Levansucrase was partially purified and characterized to study its applicability on industrial scale. The results of this study revealed that the bacterial strain Z. mobilis KIBGE-IB14 was the best producer of levansucrase. Bacterial growth and enzyme production was greatly influenced by physical and chemical parameters. Maximum levansucrase production was achieved after 24 hours of fermentation at 30°C using modified medium of pH-6.5. Contrary to other levansucrases, the one presented in the current study is able to produce high amount of products in relatively short period of time with optimum temperature at 35°C. Due to these advantages, this enzyme can be used on large scale for commercial production of levan and other important metabolites.

Keywords: levansucrase, metabolites, polysaccharides, transfructosylation

Procedia PDF Downloads 497