Search results for: multi stage flash distillation
7086 A Modified NSGA-II Algorithm for Solving Multi-Objective Flexible Job Shop Scheduling Problem
Authors: Aydin Teymourifar, Gurkan Ozturk, Ozan Bahadir
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NSGA-II is one of the most well-known and most widely used evolutionary algorithms. In addition to its new versions, such as NSGA-III, there are several modified types of this algorithm in the literature. In this paper, a hybrid NSGA-II algorithm has been suggested for solving the multi-objective flexible job shop scheduling problem. For a better search, new neighborhood-based crossover and mutation operators are defined. To create new generations, the neighbors of the selected individuals by the tournament selection are constructed. Also, at the end of each iteration, before sorting, neighbors of a certain number of good solutions are derived, except for solutions protected by elitism. The neighbors are generated using a constraint-based neural network that uses various constructs. The non-dominated sorting and crowding distance operators are same as the classic NSGA-II. A comparison based on some multi-objective benchmarks from the literature shows the efficiency of the algorithm.Keywords: flexible job shop scheduling problem, multi-objective optimization, NSGA-II algorithm, neighborhood structures
Procedia PDF Downloads 2347085 Deep Learning-Based Automated Structure Deterioration Detection for Building Structures: A Technological Advancement for Ensuring Structural Integrity
Authors: Kavita Bodke
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Structural health monitoring (SHM) is experiencing growth, necessitating the development of distinct methodologies to address its expanding scope effectively. In this study, we developed automatic structure damage identification, which incorporates three unique types of a building’s structural integrity. The first pertains to the presence of fractures within the structure, the second relates to the issue of dampness within the structure, and the third involves corrosion inside the structure. This study employs image classification techniques to discern between intact and impaired structures within structural data. The aim of this research is to find automatic damage detection with the probability of each damage class being present in one image. Based on this probability, we know which class has a higher probability or is more affected than the other classes. Utilizing photographs captured by a mobile camera serves as the input for an image classification system. Image classification was employed in our study to perform multi-class and multi-label classification. The objective was to categorize structural data based on the presence of cracks, moisture, and corrosion. In the context of multi-class image classification, our study employed three distinct methodologies: Random Forest, Multilayer Perceptron, and CNN. For the task of multi-label image classification, the models employed were Rasnet, Xceptionet, and Inception.Keywords: SHM, CNN, deep learning, multi-class classification, multi-label classification
Procedia PDF Downloads 427084 Efficient Implementation of Finite Volume Multi-Resolution Weno Scheme on Adaptive Cartesian Grids
Authors: Yuchen Yang, Zhenming Wang, Jun Zhu, Ning Zhao
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An easy-to-implement and robust finite volume multi-resolution Weighted Essentially Non-Oscillatory (WENO) scheme is proposed on adaptive cartesian grids in this paper. Such a multi-resolution WENO scheme is combined with the ghost cell immersed boundary method (IBM) and wall-function technique to solve Navier-Stokes equations. Unlike the k-exact finite volume WENO schemes which involve large amounts of extra storage, repeatedly solving the matrix generated in a least-square method or the process of calculating optimal linear weights on adaptive cartesian grids, the present methodology only adds very small overhead and can be easily implemented in existing edge-based computational fluid dynamics (CFD) codes with minor modifications. Also, the linear weights of this adaptive finite volume multi-resolution WENO scheme can be any positive numbers on condition that their sum is one. It is a way of bypassing the calculation of the optimal linear weights and such a multi-resolution WENO scheme avoids dealing with the negative linear weights on adaptive cartesian grids. Some benchmark viscous problems are numerical solved to show the efficiency and good performance of this adaptive multi-resolution WENO scheme. Compared with a second-order edge-based method, the presented method can be implemented into an adaptive cartesian grid with slight modification for big Reynolds number problems.Keywords: adaptive mesh refinement method, finite volume multi-resolution WENO scheme, immersed boundary method, wall-function technique.
Procedia PDF Downloads 1527083 Possibility of Membrane Filtration to Treatment of Effluent from Digestate
Authors: Marcin Debowski, Marcin Zielinski, Magdalena Zielinska, Paulina Rusanowska
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The problem with digestate management is one of the most important factors influencing on the development and operation of biogas plant. Turbidity and bacterial contamination negatively affect the growth of algae, which can limit the use of the effluent in the production of algae biomass on a large scale. These problems can be overcome by cultivating of algae species resistant to environmental factors, such as Chlorella sp., Scenedesmus sp., or reducing load of organic compounds to prevent bacterial contamination. The effluent requires dilution and/or purification. One of the methods of effluent treatment is the use of a membrane technology such as microfiltration (MF), ultrafiltration (UF), nanofiltration (NF) and reverse osmosis (RO), depending on the membrane pore size and the cut off point. Membranes are a physical barrier to solids and particles larger than the size of the pores. MF membranes have the largest pores and are used to remove turbidity, suspensions, bacteria and some viruses. UF membranes remove also color, odor and organic compounds with high molecular weight. In treatment of wastewater or other waste streams, MF and UF can provide a sufficient degree of purification. NF membranes are used to remove natural organic matter from waters, water disinfection products and sulfates. RO membranes are applied to remove monovalent ions such as Na⁺ or K⁺. The effluent was used in UF for medium to cultivation of two microalgae: Chlorella sp. and Phaeodactylum tricornutum. Growth rates of Chlorella sp. and P. tricornutum were similar: 0.216 d⁻¹ and 0.200 d⁻¹ (Chlorella sp.); 0.128 d⁻¹ and 0.126 d⁻¹ (P. tricornutum), on synthetic medium and permeate from UF, respectively. The final biomass composition was also similar, regardless of the medium. Removal of nitrogen was 92% and 71% by Chlorella sp. and P. tricornutum, respectively. The fermentation effluents after UF and dilution were also used for cultivation of algae Scenedesmus sp. that is resistant to environmental conditions. The authors recommended the development of biorafinery based on the production of algae for the biogas production. There are examples of using a multi-stage membrane system to purify the liquid fraction from digestate. After the initial UF, RO is used to remove ammonium nitrogen and COD. To obtain a permeate with a concentration of ammonium nitrogen allowing to discharge it into the environment, it was necessary to apply three-stage RO. The composition of the permeate after two-stage RO was: COD 50–60 mg/dm³, dry solids 0 mg/dm³, ammonium nitrogen 300–320 mg/dm³, total nitrogen 320–340 mg/dm³, total phosphorus 53 mg/dm³. However compostion of permeate after three-stage RO was: COD < 5 mg/dm³, dry solids 0 mg/dm³, ammonium nitrogen 0 mg/dm³, total nitrogen 3.5 mg/dm³, total phosphorus < 0,05 mg/dm³. Last stage of RO might be replaced by ion exchange process. The negative aspect of membrane filtration systems is the fact that the permeate is about 50% of the introduced volume, the remainder is the retentate. The management of a retentate might involve recirculation to a biogas plant.Keywords: digestate, membrane filtration, microalgae cultivation, Chlorella sp.
Procedia PDF Downloads 3537082 Using Seismic Base Isolation Systems in High-Rise Hospital Buildings and a Hybrid Proposal
Authors: Elif Bakkaloglu, Necdet Torunbalci
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The fact of earthquakes in Turkiye is an inevitable natural disaster. Therefore, buildings must be prepared for this natural hazard. Especially in hospital buildings, earthquake resistance is an essential point because hospitals are one of the first places where people come after an earthquake. Although hospital buildings are more suitable for horizontal architecture, it is necessary to construct and expand multi-storey hospital buildings due to difficulties in finding suitable places as a result of excessive urbanization, difficulties in obtaining appropriate size land and decrease in suitable places and increase in land values. In Turkiye, using seismic isolators in public hospitals, which are placed in first-degree earthquake zone and have more than 100 beds, is made obligatory by general instruction. As a result of this decision, it may sometimes be necessary to construct seismic isolated multi-storey hospital buildings in cities where those problems are experienced. Although widespread use of seismic isolators in Japan, there are few multi-storey buildings in which seismic isolators are used in Turkiye. As it is known, base isolation systems are the most effective methods of earthquake resistance, as number of floors increases, center of gravity moves away from base in multi-storey buildings, increasing the overturning effect and limiting the use of these systems. In this context, it is aimed to investigate structural systems of multi-storey buildings which built using seismic isolation methods in the World. In addition to this, a working principle is suggested for disseminating seismic isolators in multi-storey hospital buildings. The results to be obtained from the study will guide architects who design multi-storey hospital buildings in their architectural designs and engineers in terms of structural system design.Keywords: earthquake, energy absorbing systems, hospital, seismic isolation systems
Procedia PDF Downloads 1577081 The Effect of Main Factors on Forces during FSJ Processing of AA2024 Aluminum
Authors: Dunwen Zuo, Yongfang Deng, Bo Song
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An attempt is made here to measure the forces of three directions, under conditions of different feed speeds, different tilt angles of tool and without or with the pin on the tool, by using octagonal ring dynamometer in the AA2024 aluminum FSJ (Friction Stir Joining) process, and investigate how four main factors influence forces in the FSJ process. It is found that, high feed speed lead to small feed force and small lateral force, but high feed speed leads to large feed force in the stable joining stage of process. As the rotational speed increasing, the time of axial force drop from the maximum to the minimum required increased in the push-up process. In the stable joining stage, the rotational speed has little effect on the feed force; large rotational speed leads to small lateral force and axial force. The maximum axial force increases as the tilt angle of tool increases at the downward movement stage. At the moment of start feeding, as tilt angle of tool increases, the amplitudes of the axial force increasing become large. In the stable joining stage, with the increase of tilt angle of tool, the axial force is increased, the lateral force is decreased, and the feed force almost unchanged. The tool with pin will decrease axial force in the downward movement stage. The feed force and lateral force will increase, but the axial force will reduced in the stable joining stage by using the tool with pin compare to by using the tool without pin.Keywords: FSJ, force factor, AA2024 aluminum, friction stir joining
Procedia PDF Downloads 4957080 Optimal Design of RC Pier Accompanied with Multi Sliding Friction Damping Mechanism Using Combination of SNOPT and ANN Method
Authors: Angga S. Fajar, Y. Takahashi, J. Kiyono, S. Sawada
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The structural system concept of RC pier accompanied with multi sliding friction damping mechanism was developed based on numerical analysis approach. However in the implementation, to make design for such kind of this structural system consumes a lot of effort in case high of complexity. During making design, the special behaviors of this structural system should be considered including flexible small deformation, sufficient elastic deformation capacity, sufficient lateral force resistance, and sufficient energy dissipation. The confinement distribution of friction devices has significant influence to its. Optimization and prediction with multi function regression of this structural system expected capable of providing easier and simpler design method. The confinement distribution of friction devices is optimized with SNOPT in Opensees, while some design variables of the structure are predicted using multi function regression of ANN. Based on the optimization and prediction this structural system is able to be designed easily and simply.Keywords: RC Pier, multi sliding friction device, optimal design, flexible small deformation
Procedia PDF Downloads 3697079 Multi-Atlas Segmentation Based on Dynamic Energy Model: Application to Brain MR Images
Authors: Jie Huo, Jonathan Wu
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Segmentation of anatomical structures in medical images is essential for scientific inquiry into the complex relationships between biological structure and clinical diagnosis, treatment and assessment. As a method of incorporating the prior knowledge and the anatomical structure similarity between a target image and atlases, multi-atlas segmentation has been successfully applied in segmenting a variety of medical images, including the brain, cardiac, and abdominal images. The basic idea of multi-atlas segmentation is to transfer the labels in atlases to the coordinate of the target image by matching the target patch to the atlas patch in the neighborhood. However, this technique is limited by the pairwise registration between target image and atlases. In this paper, a novel multi-atlas segmentation approach is proposed by introducing a dynamic energy model. First, the target is mapped to each atlas image by minimizing the dynamic energy function, then the segmentation of target image is generated by weighted fusion based on the energy. The method is tested on MICCAI 2012 Multi-Atlas Labeling Challenge dataset which includes 20 target images and 15 atlases images. The paper also analyzes the influence of different parameters of the dynamic energy model on the segmentation accuracy and measures the dice coefficient by using different feature terms with the energy model. The highest mean dice coefficient obtained with the proposed method is 0.861, which is competitive compared with the recently published method.Keywords: brain MRI segmentation, dynamic energy model, multi-atlas segmentation, energy minimization
Procedia PDF Downloads 3397078 Effect of Salinity on Carbon Isotope Discrimination in Chamomile
Authors: Mehdi Ghanavati
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The Effects of salinity level and duration on carbon isotope discrimination (Δ) of Matricaria chamomilla and Matricaria aurea were evaluated. Four ecotypes of M. chamomilla and four ecotypes of M. aurea were grown at different NaCl concentrations (control, 6, 12 and 18 dS/m) in sand culture condition. Carbon isotope discrimination (Δ) varied significantly (p<0.001) among ecotypes. The amount of carbon isotope discrimination (Δ) increased in first salinity level (6 dS/m), but in other levels (12 and 18 dS/m) it did not increase. Stages of salinity treatments (two stages: first from seedling stage until the end of the experiment and second stage of stress exertion began at stem elongation and seedlings emergence from rosette stage to harvest) had not a significant difference. Study of two spices of chamomile showed the M. aurea had a higher amount of carbon isotope discrimination (Δ) (22.9%) than M. chamomilla (22.48%).Keywords: salinity, carbon isotope discrimination, Matricaria chamomilla, Matricaria aurea
Procedia PDF Downloads 4457077 Genetic Algorithms Multi-Objective Model for Project Scheduling
Authors: Elsheikh Asser
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Time and cost are the main goals of the construction project management. The first schedule developed may not be a suitable schedule for beginning or completing the project to achieve the target completion time at a minimum total cost. In general, there are trade-offs between time and cost (TCT) to complete the activities of a project. This research presents genetic algorithms (GAs) multi-objective model for project scheduling considering different scenarios such as least cost, least time, and target time.Keywords: genetic algorithms, time-cost trade-off, multi-objective model, project scheduling
Procedia PDF Downloads 4147076 Multi-Sensor Target Tracking Using Ensemble Learning
Authors: Bhekisipho Twala, Mantepu Masetshaba, Ramapulana Nkoana
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Multiple classifier systems combine several individual classifiers to deliver a final classification decision. However, an increasingly controversial question is whether such systems can outperform the single best classifier, and if so, what form of multiple classifiers system yields the most significant benefit. Also, multi-target tracking detection using multiple sensors is an important research field in mobile techniques and military applications. In this paper, several multiple classifiers systems are evaluated in terms of their ability to predict a system’s failure or success for multi-sensor target tracking tasks. The Bristol Eden project dataset is utilised for this task. Experimental and simulation results show that the human activity identification system can fulfill requirements of target tracking due to improved sensors classification performances with multiple classifier systems constructed using boosting achieving higher accuracy rates.Keywords: single classifier, ensemble learning, multi-target tracking, multiple classifiers
Procedia PDF Downloads 2767075 A Study of Transferable Strategies in Multilanguage Learning
Authors: Zixi You
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With the demand of multilingual speakers increasing in the job market, multi-language learning programs have become more and more popular among undergraduate students. A study on multi-language learning strategies is therefore highly demanded on both practical and theoretical levels. Based on previous classification of learning strategies in SLA, and an investigation of BA Modern Language program students (with post-A level L2 and ab initio L3 learning experience from year one), this study explores and compares different types of learning strategies used by multi-language speakers and learners, transferable learning strategies between L2 and L3, and factors affecting the transfer. The results indicate that all the 23 types of learning strategies of L2 are employed when learning L3 from ab initio level, yet with different tendencies. Learning strategy transfer from L2 to L3 (i.e., the learners attribute the applying of these L3 learning strategies to be a direct result of their L2 learning experience) are observed in all 23 types of learning strategies. Comparatively, six types of “cognitive strategies” have higher transfer tendency than others. With regard to the failure of the transfer of some particular L2 strategies and the development of independent L3 strategies of individual learners, factors such as language proficiency, language typology and learning environment have played important roles among others. The presentation of this study will provide audiences with detailed data, insightful analysis and discussion on both theoretical and practical aspects of multi-language learning that will benefit both students and educators.Keywords: learning strategy, multi-language acquisition, second language acquisition, strategy transfer
Procedia PDF Downloads 5797074 Creating a Professional Knowledge Base for Multi-Grade Teaching: Case Studies
Authors: Matshidiso Joyce Taole, Linley Cornish
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Teacher’s professional knowledge has become the focus of interest over decades and the interest has intensified in the 21st century. Teachers are expected to develop their professional academic expertise continually, on an ongoing basis. Such professional development may relate to acquiring enhanced expertise in terms of leadership, curriculum development, teaching and learning, assessment of/for learning and feedback for enhanced learning. The paper focuses on professional knowledge base required for teachers in multi-grade contexts. This paper argues that although teacher knowledge is strongly related to individual experiences and contexts, there are elements of teacher knowledge that are particular to multi-grade context. The study employed qualitative design using interviews and observations. The participants were multi-grade teachers and teaching principals. The study revealed that teachers need to develop skills such as learner grouping, differentiating the curriculum, planning, time management and be life-long learners so that they stay relevant and up to date with developments not only in the education sector but globally. This will help teachers to learn increasingly sophisticated methods for engaging the diverse needs of students in their classrooms.Keywords: curriculum differentiation, multi-grade, planning, teacher knowledge
Procedia PDF Downloads 4217073 A Multi-Objective Optimization Tool for Dual-Mode Operating Active Magnetic Regenerator Model
Authors: Anna Ouskova Leonteva, Michel Risser, Anne Jeannin-Girardon, Pierre Parrend, Pierre Collet
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This paper proposes an efficient optimization tool for an active magnetic regenerator (AMR) model, operating in two modes: magnetic refrigeration system (MRS) and thermo-magnetic generator (TMG). The aim of this optimizer is to improve the design of the AMR by applying a multi-physics multi-scales numerical model as a core of evaluation functions to achieve industrial requirements for refrigeration and energy conservation systems. Based on the multi-objective non-dominated sorting genetic algorithm 3 (NSGA3), it maximizes four different objectives: efficiency and power density for MRS and TMG. The main contribution of this work is in the simultaneously application of a CPU-parallel NSGA3 version to the AMR model in both modes for studying impact of control and design parameters on the performance. The parametric study of the optimization results are presented. The main conclusion is that the common (for TMG and MRS modes) optimal parameters can be found by the proposed tool.Keywords: ecological refrigeration systems, active magnetic regenerator, thermo-magnetic generator, multi-objective evolutionary optimization, industrial optimization problem, real-world application
Procedia PDF Downloads 1177072 Urea Amperometric Biosensor Based on Entrapment Immobilization of Urease onto a Nanostructured Polypyrrol and Multi-Walled Carbon Nanotube
Authors: Hamide Amani, Afshin FarahBakhsh, Iman Farahbakhsh
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In this paper, an amprometric biosensor based on surface modified polypyrrole (PPy) has been developed for the quantitative estimation of urea in aqueous solutions. The incorporation of urease (Urs) into a bipolymeric substrate consisting of PPy was performed by entrapment to the polymeric matrix, PPy acts as amperometric transducer in these biosensors. To increase the membrane conductivity, multi-walled carbon nanotubes (MWCNT) were added to the PPy solution. The entrapped MWCNT in PPy film and the bipolymer layers were prepared for construction of Pt/PPy/MWCNT/Urs. Two different configurations of working electrodes were evaluated to investigate the potential use of the modified membranes in biosensors. The evaluation of two different configurations of working electrodes suggested that the second configuration, which was composed of an electrode-mediator-(pyrrole and multi-walled carbon nanotube) structure and enzyme, is the best candidate for biosensor applications.Keywords: urea biosensor, polypyrrole, multi-walled carbon nanotube, urease
Procedia PDF Downloads 3357071 Multi-Temporal Cloud Detection and Removal in Satellite Imagery for Land Resources Investigation
Authors: Feng Yin
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Clouds are inevitable contaminants in optical satellite imagery, and prevent the satellite imaging systems from acquiring clear view of the earth surface. The presence of clouds in satellite imagery bring negative influences for remote sensing land resources investigation. As a consequence, detecting the locations of clouds in satellite imagery is an essential preprocessing step, and further remove the existing clouds is crucial for the application of imagery. In this paper, a multi-temporal based satellite imagery cloud detection and removal method is proposed, which will be used for large-scale land resource investigation. The proposed method is mainly composed of four steps. First, cloud masks are generated for cloud contaminated images by single temporal cloud detection based on multiple spectral features. Then, a cloud-free reference image of target areas is synthesized by weighted averaging time-series images in which cloud pixels are ignored. Thirdly, the refined cloud detection results are acquired by multi-temporal analysis based on the reference image. Finally, detected clouds are removed via multi-temporal linear regression. The results of a case application in Hubei province indicate that the proposed multi-temporal cloud detection and removal method is effective and promising for large-scale land resource investigation.Keywords: cloud detection, cloud remove, multi-temporal imagery, land resources investigation
Procedia PDF Downloads 2827070 Comparative Study of Static and Dynamic Bending Forces during 3-Roller Cone Frustum Bending Process
Authors: Mahesh K. Chudasama, Harit K. Raval
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3-roller conical bending process is widely used in the industries for manufacturing of conical sections and shells. It involves static as well dynamic bending stages. Analytical models for prediction of bending force during static as well as dynamic bending stage are available in the literature. In this paper, bending forces required for static bending stage and dynamic bending stages have been compared using the analytical models. It is concluded that force required for dynamic bending is very less as compared to the bending force required during the static bending stage.Keywords: analytical modeling, cone frustum, dynamic bending, static bending
Procedia PDF Downloads 3097069 Assessment of ATC with Shunt FACTS Devices
Authors: Ashwani Kumar, Jitender Kumar
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In this paper, an optimal power flow based approach has been applied for multi-transactions deregulated environment for ATC determination with SVC and STATCOM. The main contribution of the paper is (i) OPF based approach for evaluation of ATC with multi-transactions, (ii) ATC enhancement with FACTS devices viz. SVC and STATCOM for intact and line contingency cases, (iii) impact of ZIP load on ATC determination and comparison of ATC obtained with SVC and STATCOM. The results have been determined for intact and line contingency cases taking simultaneous as well as single transaction cases for IEEE 24 bus RTS.Keywords: available transfer capability, FACTS devices, line contingency, multi-transactions, ZIP load model
Procedia PDF Downloads 6087068 Development and Verification of the Idom Shielding Optimization Tool
Authors: Omar Bouhassoun, Cristian Garrido, César Hueso
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The radiation shielding design is an optimization problem with multiple -constrained- objective functions (radiation dose, weight, price, etc.) that depend on several parameters (material, thickness, position, etc.). The classical approach for shielding design consists of a brute force trial-and-error process subject to previous designer experience. Therefore, the result is an empirical solution but not optimal, which can degrade the overall performance of the shielding. In order to automate the shielding design procedure, the IDOM Shielding Optimization Tool (ISOT) has been developed. This software combines optimization algorithms with the capabilities to read/write input files, run calculations, as well as parse output files for different radiation transport codes. In the first stage, the software was established to adjust the input files for two well-known Monte Carlo codes (MCNP and Serpent) and optimize the result (weight, volume, price, dose rate) using multi-objective genetic algorithms. Nevertheless, its modular implementation easily allows the inclusion of more radiation transport codes and optimization algorithms. The work related to the development of ISOT and its verification on a simple 3D multi-layer shielding problem using both MCNP and Serpent will be presented. ISOT looks very promising for achieving an optimal solution to complex shielding problems.Keywords: optimization, shielding, nuclear, genetic algorithm
Procedia PDF Downloads 1137067 Finding Optimal Operation Condition in a Biological Nutrient Removal Process with Balancing Effluent Quality, Economic Cost and GHG Emissions
Authors: Seungchul Lee, Minjeong Kim, Iman Janghorban Esfahani, Jeong Tai Kim, ChangKyoo Yoo
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It is hard to maintain the effluent quality of the wastewater treatment plants (WWTPs) under with fixed types of operational control because of continuously changed influent flow rate and pollutant load. The aims of this study is development of multi-loop multi-objective control (ML-MOC) strategy in plant-wide scope targeting four objectives: 1) maximization of nutrient removal efficiency, 2) minimization of operational cost, 3) maximization of CH4 production in anaerobic digestion (AD) for CH4 reuse as a heat source and energy source, and 4) minimization of N2O gas emission to cope with global warming. First, benchmark simulation mode is modified to describe N2O dynamic in biological process, namely benchmark simulation model for greenhouse gases (BSM2G). Then, three types of single-loop proportional-integral (PI) controllers for DO controller, NO3 controller, and CH4 controller are implemented. Their optimal set-points of the controllers are found by using multi-objective genetic algorithm (MOGA). Finally, multi loop-MOC in BSM2G is implemented and evaluated in BSM2G. Compared with the reference case, the ML-MOC with the optimal set-points showed best control performances than references with improved performances of 34%, 5% and 79% of effluent quality, CH4 productivity, and N2O emission respectively, with the decrease of 65% in operational cost.Keywords: Benchmark simulation model for greenhouse gas, multi-loop multi-objective controller, multi-objective genetic algorithm, wastewater treatment plant
Procedia PDF Downloads 5077066 Studying Roughness Effects on Flow Regimes in Offshore Pipelines
Authors: Mohammad Sadegh Narges, Zahra Ghadampour
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Due to the specific condition, offshore pipelines are given careful consideration and care in both design and operation. Most of the offshore pipeline flows are multi-phase. Multi-phase flows construct different pattern or flow regimes (in simultaneous gas-liquid flow, flow regimes like slug flow, wave and …) under different circumstances. One of the influencing factors on the flow regime is the pipeline roughness value. So far, roughness value influences and the sensitivity of the present models to this parameter have not been taken into consideration. Therefore, roughness value influences on the flow regimes in offshore pipelines are discussed in this paper. Results showed that geometry, absolute pipeline roughness value (materials that the pipeline is made of) and flow phases prevailing the system are of the influential parameters on the flow regimes prevailing multi-phase pipelines in a way that a change in any of these parameters results in a change in flow regimes in all or part of the pipeline system.Keywords: absolute roughness, flow regime, multi-phase flow, offshore pipelines
Procedia PDF Downloads 3777065 Establishment of an Information Platform Increases Spontaneous Reporting of Adverse Drug Reactions
Authors: Pei-Chun Chen, Chi-Ting Tseng, Lih-Chi Chen, Kai-Hsiang Yang
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Introduction: The pharmacist is responsible for encouraging adverse drug reaction (ADR) reporting. In a local center in Northern Taiwan, promotion and rewarding of ADR reporting have continued for over six years but failed to bring significant changes. This study aims to find a solution to increase ADR reporting. Research question or hypothesis: We hypothesized that under-reporting is due to the inconvenience of the reporting system. Reports were made conventionally through printed sheets. We proposed that reports made per month will increase if they were computerized. Study design: An ADR reporting platform was established in April 2015, before which was defined as the first stage of this study (January-March, 2015) and after which the second stage. The third stage commenced in November, 2015, after adding a reporting module to physicians prescription system. ADRs could be reported simultaneously when documenting drug allergies. Methods: ADR report rates during the three stages of the study were compared. Effects of the information platform on reporting were also analyzed. Results: During the first stage, the number of ADR reports averaged 6 per month. In the second stage, the number of reports per month averaged 1.86. Introducing the information platform had little effect on the monthly number of ADR reports. The average number of reports each month during the third stage of the study was 11±3.06, with 70.43% made electronically. Reports per month increased significantly after installing the reporting module in November, 2015 (P<0.001, t-test). In the first two stages, 29.03% of ADR reports were made by physicians, as compared to 70.42% of cases in the third stage of the study. Increased physician reporting possibly account for these differences. Conclusion: Adding a reporting module to the prescription system significantly increased ADR reporting. Improved accessibility is likely the cause. The addition of similar modules to computer systems of other healthcare professions may be considered to encourage spontaneous ADR reporting.Keywords: adverse drug reactions, adverse drug reaction reporting systems, regional hospital, prescription system
Procedia PDF Downloads 3557064 Winter Wheat Yield Forecasting Using Sentinel-2 Imagery at the Early Stages
Authors: Chunhua Liao, Jinfei Wang, Bo Shan, Yang Song, Yongjun He, Taifeng Dong
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Winter wheat is one of the main crops in Canada. Forecasting of within-field variability of yield in winter wheat at the early stages is essential for precision farming. However, the crop yield modelling based on high spatial resolution satellite data is generally affected by the lack of continuous satellite observations, resulting in reducing the generalization ability of the models and increasing the difficulty of crop yield forecasting at the early stages. In this study, the correlations between Sentinel-2 data (vegetation indices and reflectance) and yield data collected by combine harvester were investigated and a generalized multivariate linear regression (MLR) model was built and tested with data acquired in different years. It was found that the four-band reflectance (blue, green, red, near-infrared) performed better than their vegetation indices (NDVI, EVI, WDRVI and OSAVI) in wheat yield prediction. The optimum phenological stage for wheat yield prediction with highest accuracy was at the growing stages from the end of the flowering to the beginning of the filling stage. The best MLR model was therefore built to predict wheat yield before harvest using Sentinel-2 data acquired at the end of the flowering stage. Further, to improve the ability of the yield prediction at the early stages, three simple unsupervised domain adaptation (DA) methods were adopted to transform the reflectance data at the early stages to the optimum phenological stage. The winter wheat yield prediction using multiple vegetation indices showed higher accuracy than using single vegetation index. The optimum stage for winter wheat yield forecasting varied with different fields when using vegetation indices, while it was consistent when using multispectral reflectance and the optimum stage for winter wheat yield prediction was at the end of flowering stage. The average testing RMSE of the MLR model at the end of the flowering stage was 604.48 kg/ha. Near the booting stage, the average testing RMSE of yield prediction using the best MLR was reduced to 799.18 kg/ha when applying the mean matching domain adaptation approach to transform the data to the target domain (at the end of the flowering) compared to that using the original data based on the models developed at the booting stage directly (“MLR at the early stage”) (RMSE =1140.64 kg/ha). This study demonstrated that the simple mean matching (MM) performed better than other DA methods and it was found that “DA then MLR at the optimum stage” performed better than “MLR directly at the early stages” for winter wheat yield forecasting at the early stages. The results indicated that the DA had a great potential in near real-time crop yield forecasting at the early stages. This study indicated that the simple domain adaptation methods had a great potential in crop yield prediction at the early stages using remote sensing data.Keywords: wheat yield prediction, domain adaptation, Sentinel-2, within-field scale
Procedia PDF Downloads 687063 Digital Homeostasis: Tangible Computing as a Multi-Sensory Installation
Authors: Andrea Macruz
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This paper explores computation as a process for design by examining how computers can become more than an operative strategy in a designer's toolkit. It documents this, building upon concepts of neuroscience and Antonio Damasio's Homeostasis Theory, which is the control of bodily states through feedback intended to keep conditions favorable for life. To do this, it follows a methodology through algorithmic drawing and discusses the outcomes of three multi-sensory design installations, which culminated from a course in an academic setting. It explains both the studio process that took place to create the installations and the computational process that was developed, related to the fields of algorithmic design and tangible computing. It discusses how designers can use computational range to achieve homeostasis related to sensory data in a multi-sensory installation. The outcomes show clearly how people and computers interact with different sensory modalities and affordances. They propose using computers as meta-physical stabilizers rather than tools.Keywords: algorithmic drawing, Antonio Damasio, emotion, homeostasis, multi-sensory installation, neuroscience
Procedia PDF Downloads 1117062 High Order Block Implicit Multi-Step (Hobim) Methods for the Solution of Stiff Ordinary Differential Equations
Authors: J. P. Chollom, G. M. Kumleng, S. Longwap
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The search for higher order A-stable linear multi-step methods has been the interest of many numerical analysts and has been realized through either higher derivatives of the solution or by inserting additional off step points, supper future points and the likes. These methods are suitable for the solution of stiff differential equations which exhibit characteristics that place a severe restriction on the choice of step size. It becomes necessary that only methods with large regions of absolute stability remain suitable for such equations. In this paper, high order block implicit multi-step methods of the hybrid form up to order twelve have been constructed using the multi-step collocation approach by inserting one or more off step points in the multi-step method. The accuracy and stability properties of the new methods are investigated and are shown to yield A-stable methods, a property desirable of methods suitable for the solution of stiff ODE’s. The new High Order Block Implicit Multistep methods used as block integrators are tested on stiff differential systems and the results reveal that the new methods are efficient and compete favourably with the state of the art Matlab ode23 code.Keywords: block linear multistep methods, high order, implicit, stiff differential equations
Procedia PDF Downloads 3627061 Multi-Objective Exergy Optimization of an Organic Rankine Cycle with Cyclohexane as Working Fluid
Authors: Touil Djamal, Fergani Zineb
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In this study, an Organic Rankine Cycle (ORC) with Cyclohexane working fluid is proposed for cogeneration in the cement industry. In this regard: first, a parametric study is conducted to evaluate the effects of some key parameters on the system performances. Next, single and multi-objective optimizations are performed to achieve the system optimal design. The optimization considers the exergy efficiency, the cost per exergy unit and the environmental impact of the net produced power as objective functions. Finally, exergy, exergoeconomic and exergoenvironmental analysis of the cycle is carried out at the optimum operating conditions. The results show that the turbine inlet pressure, the pinch point temperature difference and the heat transfer fluid temperature have significant effects on the performances of the ORC system.Keywords: organic rankine cycle, multi-objective optimization, exergy, exergoeconomic, exergoenvironmental, multi-objective optimisation, organic rankine cycle, cement plant
Procedia PDF Downloads 2837060 A Novel Multi-Attribute Green Decision Making Model for Environmental Supply Chain Sustainability
Authors: Amirhossein Mahlouji
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In current business market, the concept of integrating environmental sustainability into long-term as well as routine operations is becoming a prevailing trend. Therefore, several stimuli are helping organization to move toward environmental sustainability. The concept of green supply chain management can help provide a strategic framework to develop a customized sustainability roadmap for each organization. In this regard, this paper is mainly focused on presenting a strategic decision making framework that will assist top level decision-making issues. This decision-making tool is based on literature and practice in the area of environmentally conscious business practices. The goal of this paper will be on the components and parameters of green supply chain management and how they serve as a baseline for the decision framework. Later, the applicability of a multi-input multi-output decision model (MIMO), will be analyzed as the analytical network process, within the green supply chain.Keywords: Multi-attribute, Green Supply Chain, Environmental, Sustainability
Procedia PDF Downloads 1567059 Developing the Morphological Field of Problem Context to Assist Multi-Methodology in Operations Research
Authors: Mahnaz Hosseinzadeh, Mohammad Reza Mehregan
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In this paper, we have developed a morphological field to assist multi- methodology (combining methodologies together in whole or part) in Operations Research (OR) for the problem contexts in Iranian organizations. So, we have attempted to identify some dimensions for problem context according to Iranian organizational problems. Then, a general morphological program is designed which helps the OR practitioner to determine the suitable OR methodology as output for any configuration of conditions in a problem context as input and to reveal the fields necessary to be improved in OR. Applying such a program would have interesting results for OR practitioners.Keywords: hard, soft and emancipatory operations research, General Morphological Analysis (GMA), multi-methodology, problem context
Procedia PDF Downloads 3027058 Analytical Modeling of Equivalent Magnetic Circuit in Multi-segment and Multi-barrier Synchronous Reluctance Motor
Authors: Huai-Cong Liu,Tae Chul Jeong,Ju Lee
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This paper describes characteristic analysis of a synchronous reluctance motor (SynRM)’s rotor with the Multi-segment and Multi-layer structure. The magnetic-saturation phenomenon in SynRM is often appeared. Therefore, when modeling analysis of SynRM the calculation of nonlinear magnetic field needs to be considered. An important influence factor on the convergence process is how to determine the relative permeability. An improved method, which ensures the calculation, is convergence by linear iterative method for saturated magnetic field. If there are inflection points on the magnetic curve,an optimum convergence method of solution for nonlinear magnetic field was provided. Then the equivalent magnetic circuit is calculated, and d,q-axis inductance can be got. At last, this process is applied to design a 7.5Kw SynRM and its validity is verified by comparing with the result of finite element method (FEM) and experimental test data.Keywords: SynRM, magnetic-saturation, magnetic circuit, analytical modeling
Procedia PDF Downloads 5087057 Reversibility of Photosynthetic Activity and Pigment-protein Complexes Expression During Seed Development of Soybean and Black Soybean
Authors: Tzan-Chain Lee
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Seeds are non-leaves green tissues. Photosynthesis begins with light absorption by chlorophyll and then the energy transfer between two pigment-protein complexes (PPC). Most studies of photosynthesis and PPC expression were focused on leaves; however, during seeds’ development were rare. Developed seeds from beginning pod (stage R3) to dried seed (stage R8), and the dried seed after sowing for 1-4 day, were analyzed for their chlorophyll contents. Thornber and MARS gel systems analysis compositions of PPC. Chlorophyll fluorescence was used to detect maximal photosynthetic efficiency (Fv/Fm). During soybean and black soybean seeds development (stages R3-R6), Fv/Fm up to 0.8, and then down-regulated after full seed (stage R7). In dried seed (stage R8), the two plant seeds lost photosynthetic activity (Fv/Fm=0), but chlorophyll degradation only occurred in soybean after full seed. After seeds sowing for 4 days, chlorophyll drastically increased in soybean seeds, and Fv/Fm recovered to 0.8 in the two seeds. In PPC, the two soybean seeds contained all PPC during seeds development (stages R3-R6), including CPI, CPII, A1, AB1, AB2, and AB3. However, many proteins A1, AB1, AB2, and CPI were totally missing in the two dried seeds (stage R8). The deficiency of these proteins in dried seeds might be caused by the incomplete photosynthetic activity. After seeds germination and seedling exposed to light for 4 days, all PPC were recovered, suggesting that completed PPC took place in the two soybean seeds. This study showed the reversibility of photosynthetic activity and pigment-protein complexes during soybean and black soybean seeds development.Keywords: light-harvesting complex, pigment–protein complexes, soybean cotyledon, grana development
Procedia PDF Downloads 154