Search results for: particle swarm optimization algorithm (PSO)

Authors: Qian Chen, Lin Xu, Ping Ju, Zhuoran Li, Yiping Yu, Yuqing Jin

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The operation of power grid is becoming more and more complex and difficult due to its rapid development towards high voltage, long distance, and large capacity. For instance, many large-scale wind farms have connected to power grid, where their fluctuation and randomness is very likely to affect the stability and safety of the grid. Fortunately, many new-type equipments based on power electronics have been applied to power grid, such as UPFC (Unified Power Flow Controller), TCSC (Thyristor Controlled Series Compensation), STATCOM (Static Synchronous Compensator) and so on, which can help to deal with the problem above. Compared with traditional equipment such as generator, new-type controllable devices, represented by the FACTS (Flexible AC Transmission System), have more accurate control ability and respond faster. But they are too expensive to use widely. Therefore, on the basis of the comparison and analysis of the controlling characteristics between traditional control equipment and new-type controllable equipment in both time and space scale, a coordinated optimizing control method within mutil-time-space frame is proposed in this paper to bring both kinds of advantages into play, which can better both control ability and economical efficiency. Firstly, the coordination of different space sizes of grid is studied focused on the fluctuation caused by large-scale wind farms connected to power grid. With generator, FSC (Fixed Series Compensation) and TCSC, the coordination method on two-layer regional power grid vs. its sub grid is studied in detail. The coordination control model is built, the corresponding scheme is promoted, and the conclusion is verified by simulation. By analysis, interface power flow can be controlled by generator and the specific line power flow between two-layer regions can be adjusted by FSC and TCSC. The smaller the interface power flow adjusted by generator, the bigger the control margin of TCSC, instead, the total consumption of generator is much higher. Secondly, the coordination of different time sizes is studied to further the amount of the total consumption of generator and the control margin of TCSC, where the minimum control cost can be acquired. The coordination method on two-layer ultra short-term correction vs. AGC (Automatic Generation Control) is studied with generator, FSC and TCSC. The optimal control model is founded, genetic algorithm is selected to solve the problem, and the conclusion is verified by simulation. Finally, the aforementioned method within multi-time-space scale is analyzed with practical cases, and simulated on PSASP (Power System Analysis Software Package) platform. The correctness and effectiveness are verified by the simulation result. Moreover, this coordinated optimizing control method can contribute to the decrease of control cost and will provide reference to the following studies in this field.

Keywords: FACTS, multi-space-time frame, optimal control, TCSC

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Authors: Sharon Hovav, Ilya Levner, Oren Nahum, Istvan Szabo

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In modern large-scale logistic centers (e.g., big automated warehouses), complex logistic operations performed by human staff (pickers) need to be coordinated with the operations of automated facilities (robots, conveyors, cranes, lifts, flow racks, etc.). The efficiency of advanced logistic centers strongly depends on optimizing picking technologies in synch with the facility/product layout, as well as on optimal distribution of material flows (products) in the system. The challenge is to develop a mathematical operations research (OR) tool that will optimize system cost-effectiveness. In this work, we propose a model that describes an automatic logistic center consisting of a set of workstations located at several galleries (floors), with each station containing a known number of flow racks. The requirements of each product and the working capacity of stations served by a given set of workers (pickers) are assumed as predetermined. The goal of the model is to maximize system efficiency. The proposed model includes two echelons. The first is the setting of the (optimal) number of workstations needed to create the total processing/logistic system, subject to picker capacities. The second echelon deals with the assignment of the products to the workstations and flow racks, aimed to achieve maximal throughputs of picked products over the entire system given picker capacities and budget constraints. The solutions to the problems at the two echelons interact to balance the overall load in the flow racks and maximize overall efficiency. We have developed an operations research model within each echelon. In the first echelon, the problem of calculating the optimal number of workstations is formulated as a non-standard bin-packing problem with capacity constraints for each bin. The problem arising in the second echelon is presented as a constrained product-workstation-flow rack assignment problem with non-standard mini-max criteria in which the workload maximum is calculated across all workstations in the center and the exterior minimum is calculated across all possible product-workstation-flow rack assignments. The OR problems arising in each echelon are proved to be NP-hard. Consequently, we find and develop heuristic and approximation solution algorithms based on exploiting and improving local optimums. The LC model considered in this work is highly dynamic and is recalculated periodically based on updated demand forecasts that reflect market trends, technological changes, seasonality, and the introduction of new items. The suggested two-echelon approach and the min-max balancing scheme are shown to work effectively on illustrative examples and real-life logistic data.

Keywords: logistics center, product-workstation, assignment, maximum performance, load balancing, fast algorithm

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Authors: Khethiwe Mtshali, Zamantungwa T. H. Khumalo, Stanford Kwenda, Ismail Arshad, Oriel M. M. Thekisoe

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Ecologically, the gut, mammary glands and bloodstream consist of distinct microbial communities of commensals, mutualists and pathogens, forming a complex ecosystem of niches. The by-products derived from these body sites i.e. faeces, milk and blood, respectively, have many uses in rural communities where they aid in the facilitation of day-to-day household activities and occasional rituals. Thus, although livestock rearing plays a vital role in the sustenance of the livelihoods of rural communities, it may serve as a potent reservoir of different pathogenic organisms that could have devastating health and economic implications. This study aimed to simultaneously explore the microbial profiles of corresponding faecal, milk and blood samples from lactating cows using 16S rRNA metagenomic sequencing. Bacterial communities were inferred through the Divisive Amplicon Denoising Algorithm 2 (DADA2) pipeline coupled with SILVA database v138. All downstream analyses were performed in R v3.6.1. Alpha-diversity metrics showed significant differences between faeces and blood, faeces and milk, but did not vary significantly between blood and milk (Kruskal-Wallis, P < 0.05). Beta-diversity metrics on Principal Coordinate Analysis (PCoA) and Non-Metric Dimensional Scaling (NMDS) clustered samples by type, suggesting that microbial communities of the studied niches are significantly different (PERMANOVA, P < 0.05). A number of taxa were significantly differentially abundant (DA) between groups based on the Wald test implemented in the DESeq2 package (Padj < 0.01). The majority of the DA taxa were significantly enriched in faeces than in milk and blood, except for the genus Anaplasma, which was significantly enriched in blood and was, in turn, the most abundant taxon overall. A total of 30 phyla, 74 classes, 156 orders, 243 families and 408 genera were obtained from the overall analysis. The most abundant phyla obtained between the three body sites were Firmicutes, Bacteroidota, and Proteobacteria. A total of 58 genus-level taxa were simultaneously detected between the sample groups, while bacterial signatures of at least 8 of these occurred concurrently in corresponding faeces, milk and blood samples from the same group of animals constituting a pool. The important taxa identified in this study could be categorized into four potentially pathogenic clusters: i) arthropod-borne; ii) food-borne and zoonotic; iii) mastitogenic and; iv) metritic and abortigenic. This study provides insight into the microbial composition of bovine faeces, milk, and blood and its extent of overlapping. It further highlights the potential risk of disease occurrence and transmission between the animals and the inhabitants of the sampled rural community, pertaining to their unsanitary practices associated with the use of cattle by-products.

Keywords: microbial profiling, 16S rRNA, NGS, feces, milk, blood, lactating cows, small-scale farmers

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Authors: Pei-Jyun Hsieh, Cheng-Hsuan Li, Bor-Chen Kuo

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For hyperspectral image classification, feature reduction is an important pre-processing for avoiding the Hughes phenomena due to the difficulty for collecting training samples. Hence, lots of researches developed feature selection methods such as F-score, HSIC (Hilbert-Schmidt Independence Criterion), and etc., to improve hyperspectral image classification. However, most of them only consider the class separability in the original space, i.e., a linear class separability. In this study, we proposed a nonlinear class separability measure based on kernel trick for selecting an appropriate feature subset. The proposed nonlinear class separability was formed by a generalized RBF kernel with different bandwidths with respect to different features. Moreover, it considered the within-class separability and the between-class separability. A genetic algorithm was applied to tune these bandwidths such that the smallest with-class separability and the largest between-class separability simultaneously. This indicates the corresponding feature space is more suitable for classification. In addition, the corresponding nonlinear classification boundary can separate classes very well. These optimal bandwidths also show the importance of bands for hyperspectral image classification. The reciprocals of these bandwidths can be viewed as weights of bands. The smaller bandwidth, the larger weight of the band, and the more importance for classification. Hence, the descending order of the reciprocals of the bands gives an order for selecting the appropriate feature subsets. In the experiments, three hyperspectral image data sets, the Indian Pine Site data set, the PAVIA data set, and the Salinas A data set, were used to demonstrate the selected feature subsets by the proposed nonlinear feature selection method are more appropriate for hyperspectral image classification. Only ten percent of samples were randomly selected to form the training dataset. All non-background samples were used to form the testing dataset. The support vector machine was applied to classify these testing samples based on selected feature subsets. According to the experiments on the Indian Pine Site data set with 220 bands, the highest accuracies by applying the proposed method, F-score, and HSIC are 0.8795, 0.8795, and 0.87404, respectively. However, the proposed method selects 158 features. F-score and HSIC select 168 features and 217 features, respectively. Moreover, the classification accuracies increase dramatically only using first few features. The classification accuracies with respect to feature subsets of 10 features, 20 features, 50 features, and 110 features are 0.69587, 0.7348, 0.79217, and 0.84164, respectively. Furthermore, only using half selected features (110 features) of the proposed method, the corresponding classification accuracy (0.84168) is approximate to the highest classification accuracy, 0.8795. For other two hyperspectral image data sets, the PAVIA data set and Salinas A data set, we can obtain the similar results. These results illustrate our proposed method can efficiently find feature subsets to improve hyperspectral image classification. One can apply the proposed method to determine the suitable feature subset first according to specific purposes. Then researchers can only use the corresponding sensors to obtain the hyperspectral image and classify the samples. This can not only improve the classification performance but also reduce the cost for obtaining hyperspectral images.

Keywords: hyperspectral image classification, nonlinear feature selection, kernel trick, support vector machine

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Authors: Antonella Falanga, Armando Cartenì

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"Big data" refers to extremely vast and complex sets of data, encompassing extraordinarily large and intricate datasets that require specific tools for meaningful analysis and processing. These datasets can stem from diverse origins like sensors, mobile devices, online transactions, social media platforms, and more. The utilization of big data is pivotal, offering the chance to leverage vast information for substantial advantages across diverse fields, thereby enhancing comprehension, decision-making, efficiency, and fostering innovation in various domains. Big data, distinguished by its remarkable attributes of enormous volume, high velocity, diverse variety, and significant value, represent a transformative force reshaping the industry worldwide. Their pervasive impact continues to unlock new possibilities, driving innovation and advancements in technology, decision-making processes, and societal progress in an increasingly data-centric world. The use of these technologies is becoming more widespread, facilitating and accelerating operations that were once much more complicated. In particular, big data impacts across multiple sectors such as business and commerce, healthcare and science, finance, education, geography, agriculture, media and entertainment and also mobility and logistics. Within the transportation sector, which is the focus of this study, big data applications encompass a wide variety, spanning across optimization in vehicle routing, real-time traffic management and monitoring, logistics efficiency, reduction of travel times and congestion, enhancement of the overall transportation systems, but also mitigation of pollutant emissions contributing to environmental sustainability. Meanwhile, in public administration and the development of smart cities, big data aids in improving public services, urban planning, and decision-making processes, leading to more efficient and sustainable urban environments. Access to vast data reservoirs enables deeper insights, revealing hidden patterns and facilitating more precise and timely decision-making. Additionally, advancements in cloud computing and artificial intelligence (AI) have further amplified the potential of big data, enabling more sophisticated and comprehensive analyses. Certainly, utilizing big data presents various advantages but also entails several challenges regarding data privacy and security, ensuring data quality, managing and storing large volumes of data effectively, integrating data from diverse sources, the need for specialized skills to interpret analysis results, ethical considerations in data use, and evaluating costs against benefits. Addressing these difficulties requires well-structured strategies and policies to balance the benefits of big data with privacy, security, and efficient data management concerns. Building upon these premises, the current research investigates the efficacy and influence of big data by conducting an overview of the primary and recent implementations of big data in transportation systems. Overall, this research allows us to conclude that big data better provide to enhance rational decision-making for mobility choices and is imperative for adeptly planning and allocating investments in transportation infrastructures and services.

Keywords: big data, public transport, sustainable mobility, transport demand, transportation planning

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Authors: Haya Salah, Srinivas Sharan

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Healthcare facilities use appointment systems to schedule their appointments and to manage access to their medical services. With the growing demand for outpatient care, it is now imperative to manage physician's time effectively. However, high variation in consultation duration affects the clinical scheduler's ability to estimate the appointment duration and allocate provider time appropriately. Underestimating consultation times can lead to physician's burnout, misdiagnosis, and patient dissatisfaction. On the other hand, appointment durations that are longer than required lead to doctor idle time and fewer patient visits. Therefore, a good estimation of consultation duration has the potential to improve timely access to care, resource utilization, quality of care, and patient satisfaction. Although the literature on factors influencing consultation length abound, little work has done to predict it using based data-driven approaches. Therefore, this study aims to predict consultation duration using supervised machine learning algorithms (ML), which predicts an outcome variable (e.g., consultation) based on potential features that influence the outcome. In particular, ML algorithms learn from a historical dataset without explicitly being programmed and uncover the relationship between the features and outcome variable. A subset of the data used in this study has been obtained from the electronic medical records (EMR) of four different outpatient clinics located in central Pennsylvania, USA. Also, publicly available information on doctor's characteristics such as gender and experience has been extracted from online sources. This research develops three popular ML algorithms (deep learning, random forest, gradient boosting machine) to predict the treatment time required for a patient and conducts a comparative analysis of these algorithms with respect to predictive performance. The findings of this study indicate that ML algorithms have the potential to predict the provider service time with superior accuracy. While the current approach of experience-based appointment duration estimation adopted by the clinic resulted in a mean absolute percentage error of 25.8%, the Deep learning algorithm developed in this study yielded the best performance with a MAPE of 12.24%, followed by gradient boosting machine (13.26%) and random forests (14.71%). Besides, this research also identified the critical variables affecting consultation duration to be patient type (new vs. established), doctor's experience, zip code, appointment day, and doctor's specialty. Moreover, several practical insights are obtained based on the comparative analysis of the ML algorithms. The machine learning approach presented in this study can serve as a decision support tool and could be integrated into the appointment system for effectively managing patient scheduling.

Keywords: clinical decision support system, machine learning algorithms, patient scheduling, prediction models, provider service time

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Authors: Jérôme de Reffye, Marc Antoni

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Following the development of the ERTMS system, we think it is interesting to develop another software-based track circuit system which would fit secondary railway lines with an easy-to-work implementation and a low sensitivity to rail-wheel impedance variations. We called this track circuit 'Track Railway by Automatic Circuits.' To be internationally implemented, this system must not have any mechanical component and must be compatible with existing track circuit systems. For example, the system is independent from the French 'Joints Isolants Collés' that isolate track sections from one another, and it is equally independent from component used in Germany called 'Counting Axles,' in French 'compteur d’essieux.' This track circuit is fully interoperable. Such universality is obtained by replacing the train detection mechanical system with a space-time filtering of train position. The various track sections are defined by the frequency of a continuous signal. The set of frequencies related to the track sections is a set of orthogonal functions in a Hilbert Space. Thus the failure probability of track sections separation is precisely calculated on the basis of signal-to-noise ratio. SNR is a function of the level of traction current conducted by rails. This is the reason why we developed a very powerful algorithm to reject noise and jamming to obtain an SNR compatible with the precision required for the track circuit and SIL 4 level. The SIL 4 level is thus reachable by an adjustment of the set of orthogonal functions. Our major contributions to railway engineering signalling science are i) Train space localization is precisely defined by a calibration system. The operation bypasses the GSM-R radio system of the ERTMS system. Moreover, the track circuit is naturally protected against radio-type jammers. After the calibration operation, the track circuit is autonomous. ii) A mathematical topology adapted to train space localization by following the train through a linear time filtering of the received signal. Track sections are numerically defined and can be modified with a software update. The system was numerically simulated, and results were beyond our expectations. We achieved a precision of one meter. Rail-ground and rail-wheel impedance sensitivity analysis gave excellent results. Results are now complete and ready to be published. This work was initialised as a research project of the French Railways developed by the Pi-Ramses Company under SNCF contract and required five years to obtain the results. This track circuit is already at Level 3 of the ERTMS system, and it will be much cheaper to implement and to work. The traffic regulation is based on variable length track sections. As the traffic growths, the maximum speed is reduced, and the track section lengths are decreasing. It is possible if the elementary track section is correctly defined for the minimum speed and if every track section is able to emit with variable frequencies.

Keywords: track section, track circuits, space-time crossing, adaptive track section, automatic railway signalling

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Authors: Medan Isaeva, Anna Degtyareva

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Context: Biliary atresia is a common reason for liver transplants in children, and the Kasai procedure can potentially be successful in avoiding the need for transplantation. However, it is important to identify factors that influence surgical outcomes in order to optimize treatment and improve patient outcomes. Research aim: The aim of this study was to develop prognostic models to assess the outcomes of the Kasai procedure in children with biliary atresia. Methodology: This retrospective study analyzed data from 166 children with biliary atresia who underwent the Kasai procedure between 2002 and 2021. The effectiveness of the operation was assessed based on specific criteria, including post-operative stool color, jaundice reduction, and bilirubin levels. The study involved a comparative analysis of various parameters, such as gestational age, birth weight, age at operation, physical development, liver and spleen sizes, and laboratory values including bilirubin, ALT, AST, and others, measured pre- and post-operation. Ultrasonographic evaluations were also conducted pre-operation, assessing the hepatobiliary system and related quantitative parameters. The study was carried out by two experienced specialists in pediatric hepatology. Comparative analysis and multifactorial logistic regression were used as the primary statistical methods. Findings: The study identified several statistically significant predictors of a successful Kasai procedure, including the presence of the gallbladder and levels of cholesterol and direct bilirubin post-operation. A detectable gallbladder was associated with a higher probability of surgical success, while elevated post-operative cholesterol and direct bilirubin levels were indicative of a reduced chance of positive outcomes. Theoretical importance: The findings of this study contribute to the optimization of treatment strategies for children with biliary atresia undergoing the Kasai procedure. By identifying early predictive signs of success, clinicians can modify treatment plans and manage patient care more effectively and proactively. Data collection and analysis procedures: Data for this analysis were obtained from the health records of patients who received the Kasai procedure. Comparative analysis and multifactorial logistic regression were employed to analyze the data and identify significant predictors. Question addressed: The study addressed the question of identifying predictive factors for the success of the Kasai procedure in children with biliary atresia. Conclusion: The developed prognostic models serve as valuable tools for early detection of patients who are less likely to benefit from the Kasai procedure. This enables clinicians to modify treatment plans and manage patient care more effectively and proactively. Potential limitations of the study: The study has several limitations. Its retrospective nature may introduce biases and inconsistencies in data collection. Being single centered, the results might not be generalizable to wider populations due to variations in surgical and postoperative practices. Also, other potential influencing factors beyond the clinical, laboratory, and ultrasonographic parameters considered in this study were not explored, which could affect the outcomes of the Kasai operation. Future studies could benefit from including a broader range of factors.

Keywords: biliary atresia, kasai operation, prognostic model, native liver survival

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Authors: Athina Puype, Lorenzo Malerba, Nico De Wispelaere, Roumen Petrov, Jilt Sietsma

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Reduced activation ferritic/martensitic (RAFM) steels like EUROFER97 are primary candidate structural materials for first wall application in the future demonstration (DEMO) fusion reactor. Existing steels of this type obtain their functional properties by a two-stage heat treatment, which consists of an annealing stage at 980°C for thirty minutes followed by quenching and an additional tempering stage at 750°C for two hours. This thermal quench and temper (Q&T) treatment creates a microstructure of tempered martensite with, as main precipitates, M23C6 carbides, with M = Fe, Cr and carbonitrides of MX type, e.g. TaC and VN. The resulting microstructure determines the mechanical properties of the steel. The ductility is largely determined by the tempered martensite matrix, while the resistance to mechanical degradation, determined by the spatial and size distribution of precipitates and the martensite crystals, plays a key role in the high temperature properties of the steel. Unfortunately, the high temperature response of EUROFER97 is currently insufficient for long term use in fusion reactors, due to instability of the matrix phase and coarsening of the precipitates at prolonged high temperature exposure. The objective of this study is to induce grain refinement by appropriate modifications of the processing route in order to increase the high temperature strength of a lab-cast EUROFER RAFM steel grade. The goal of the work is to obtain improved mechanical behavior at elevated temperatures with respect to conventionally heat treated EUROFER97. A dilatometric study was conducted to study the effect of the annealing temperature on the mechanical properties after a Q&T treatment. The microstructural features were investigated with scanning electron microscopy (SEM), electron back-scattered diffraction (EBSD) and transmission electron microscopy (TEM). Additionally, hardness measurements, tensile tests at elevated temperatures and Charpy V-notch impact testing of KLST-type MCVN specimens were performed to study the mechanical properties of the furnace-heated lab-cast EUROFER RAFM steel grade. A significant prior austenite grain (PAG) refinement was obtained by lowering the annealing temperature of the conventionally used Q&T treatment for EUROFER97. The reduction of the PAG results in finer martensitic constituents upon quenching, which offers more nucleation sites for carbide and carbonitride formation upon tempering. The ductile-to-brittle transition temperature (DBTT) was found to decrease with decreasing martensitic block size. Additionally, an increased resistance against high temperature degradation was accomplished in the fine grained martensitic materials with smallest precipitates obtained by tailoring the annealing temperature of the Q&T treatment. It is concluded that the microstructural refinement has a pronounced effect on the DBTT without significant loss of strength and ductility. Further investigation into the optimization of the processing route is recommended to improve the mechanical behavior of RAFM steels at elevated temperatures.

Keywords: ductile-to-brittle transition temperature (DBTT), EUROFER, reduced activation ferritic/martensitic (RAFM) steels, thermal treatments

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Authors: Hameed Rukayat Opeyemi, Pericles Pilidis Pagone Emmanuele, Agbadede Roupa, Allison Isaiah

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Climate change represents one of the single most challenging problems facing the world today. According to the National Oceanic and Administrative Association, Atmospheric temperature rose almost 25% since 1958, Artic sea ice has shrunk 40% since 1959 and global sea levels have risen more than 5.5cm since 1990. Power plants are the major culprits of GHG emission to the atmosphere. Several technologies have been proposed to reduce the amount of GHG emitted to the atmosphere from power plant, one of which is the less researched Advanced zero-emission power plant. The advanced zero emission power plants make use of mixed conductive membrane (MCM) reactor also known as oxygen transfer membrane (OTM) for oxygen transfer. The MCM employs membrane separation process. The membrane separation process was first introduced in 1899 when Walter Hermann Nernst investigated electric current between metals and solutions. He found that when a dense ceramic is heated, the current of oxygen molecules move through it. In the bid to curb the amount of GHG emitted to the atmosphere, the membrane separation process was applied to the field of power engineering in the low carbon cycle known as the Advanced zero emission power plant (AZEP cycle). The AZEP cycle was originally invented by Norsk Hydro, Norway and ABB Alstom power (now known as Demag Delaval Industrial turbomachinery AB), Sweden. The AZEP drew a lot of attention because its ability to capture ~100% CO2 and also boasts of about 30-50% cost reduction compared to other carbon abatement technologies, the penalty in efficiency is also not as much as its counterparts and crowns it with almost zero NOx emissions due to very low nitrogen concentrations in the working fluid. The advanced zero emission power plants differ from a conventional gas turbine in the sense that its combustor is substituted with the mixed conductive membrane (MCM-reactor). The MCM-reactor is made up of the combustor, low-temperature heat exchanger LTHX (referred to by some authors as air preheater the mixed conductive membrane responsible for oxygen transfer and the high-temperature heat exchanger and in some layouts, the bleed gas heat exchanger. Air is taken in by the compressor and compressed to a temperature of about 723 Kelvin and pressure of 2 Mega-Pascals. The membrane area needed for oxygen transfer is reduced by increasing the temperature of 90% of the air using the LTHX; the temperature is also increased to facilitate oxygen transfer through the membrane. The air stream enters the LTHX through the transition duct leading to inlet of the LTHX. The temperature of the air stream is then increased to about 1150 K depending on the design point specification of the plant and the efficiency of the heat exchanging system. The amount of oxygen transported through the membrane is directly proportional to the temperature of air going through the membrane. The AZEP cycle was developed using the Fortran software and economic analysis was conducted using excel and Matlab followed by optimization case study. The Simple bleed gas heat exchange layout (100 % CO2 capture), Bleed gas heat exchanger layout with flue gas turbine (100 % CO2 capture), Pre-expansion reheating layout (Sequential burning layout)–AZEP 85% (85% CO2 capture) and Pre-expansion reheating layout (Sequential burning layout) with flue gas turbine–AZEP 85% (85% CO2 capture). This paper discusses monte carlo risk analysis of four possible layouts of the AZEP cycle.

Keywords: gas turbine, global warming, green house gas, fossil fuel power plants

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Authors: Joana Almeida, Kendall Reid, Jonas Bengtsson

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Pallets are devices that are used for moving and storing freight and are nearly omnipresent in supply chains. The market is dominated by timber pallets, with plastic being a common alternative. Either option underpins the use of important resources (oil, land, timber), the emission of greenhouse gases and additional waste generation in most supply chains. This study uses a dynamic approach to the life cycle assessment (LCA) of pallets. It demonstrates that what ultimately defines the environmental burden of pallets in the supply chain is how often the length of its lifespan, which depends on the durability of the material and on how pallets are utilized. This study proposes a life cycle assessment (LCA) of pallets in supply chains supported by an algorithm that estimates pallet durability in function of material resilience and of logistics. The LCA runs from cradle-to-grave, including raw material provision, manufacture, transport and end of life. The scope is representative of timber and plastic pallets in the Australian and South-East Asia markets. The materials included in this analysis are: -tropical mixed hardwood, unsustainably harvested in SE Asia; -certified softwood, sustainably harvested; -conventional plastic, a mix of virgin and scrap plastic; -recycled plastic pallets, 100% mixed plastic scrap, which are being pioneered by Re > Pal. The logistical model purports that more complex supply chains and rougher handling subject pallets to higher stress loads. More stress shortens the lifespan of pallets in function of their composition. Timber pallets can be repaired, extending their lifespan, while plastic pallets cannot. At the factory gate, softwood pallets have the lowest carbon footprint. Re > pal follows closely due to its burden-free feedstock. Tropical mixed hardwood and plastic pallets have the highest footprints. Harvesting tropical mixed hardwood in SE Asia often leads to deforestation, leading to emissions from land use change. The higher footprint of plastic pallets is due to the production of virgin plastic. Our findings show that manufacture alone does not determine the sustainability of pallets. Even though certified softwood pallets have lower carbon footprint and their lifespan can be extended by repair, the need for re-supply of materials and disposal of waste timber offsets this advantage. It also leads to most waste being generated among all pallets. In a supply chain context, Re > Pal pallets have the lowest footprint due to lower replacement and disposal needs. In addition, Re > Pal are nearly ‘waste neutral’, because the waste that is generated throughout their life cycle is almost totally offset by the scrap uptake for production. The absolute results of this study can be confirmed by progressing the logistics model, improving data quality, expanding the range of materials and utilization practices. Still, this LCA demonstrates that considering logistics, raw materials and material durability is central for sustainable decision-making on pallet purchasing, management and disposal.

Keywords: carbon footprint, life cycle assessment, recycled plastic, waste

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Authors: Harpal Singh, Sakshi Batra

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The widespread and easy accesses to multimedia contents and possibility to make numerous copies without loss of significant fidelity have roused the requirement of digital rights management. Thus this problem can be effectively solved by Digital watermarking technology. This is a concept of embedding some sort of data or special pattern (watermark) in the multimedia content; this information will later prove ownership in case of a dispute, trace the marked document’s dissemination, identify a misappropriating person or simply inform user about the rights-holder. The primary motive of digital watermarking is to embed the data imperceptibly and robustly in the host information. Extensive counts of watermarking techniques have been developed to embed copyright marks or data in digital images, video, audio and other multimedia objects. With the development of digital video-based innovations, copyright dilemma for the multimedia industry increases. Video watermarking had been proposed in recent years to serve the issue of illicit copying and allocation of videos. It is the process of embedding copyright information in video bit streams. Practically video watermarking schemes have to address some serious challenges as compared to image watermarking schemes like real-time requirements in the video broadcasting, large volume of inherently redundant data between frames, the unbalance between the motion and motionless regions etc. and they are particularly vulnerable to attacks, for example, frame swapping, statistical analysis, rotation, noise, median and crop attacks. In this paper, an effective, robust and imperceptible video watermarking algorithm is proposed based on hybridization of powerful mathematical transforms; Fractional Fourier Transform (FrFT), Discrete Wavelet transforms (DWT) and Singular Value Decomposition (SVD) using redundant wavelet. This scheme utilizes various transforms for embedding watermarks on different layers by using Hybrid systems. For this purpose, the video frames are portioned into layers (RGB) and the watermark is being embedded in two forms in the video frames using SVD portioning of the watermark, and DWT sub-band decomposition of host video, to facilitate copyright safeguard as well as reliability. The FrFT orders are used as the encryption key that allows the watermarking method to be more robust against various attacks. The fidelity of the scheme is enhanced by introducing key generation and wavelet based key embedding watermarking scheme. Thus, for watermark embedding and extraction, same key is required. Therefore the key must be shared between the owner and the verifier via some safe network. This paper demonstrates the performance by considering different qualitative metrics namely Peak Signal to Noise ratio, Structure similarity index and correlation values and also apply some attacks to prove the robustness. The Experimental results are presented to demonstrate that the proposed scheme can withstand a variety of video processing attacks as well as imperceptibility.

Keywords: discrete wavelet transform, robustness, video watermarking, watermark

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Authors: Jose Neri, Fabrice Canto, Alastair Magnaldo, Laurent Guillerme, Vincent Dugas

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A miniaturized and automated approach for the volumetric titration of free nitric acid in U(VI) solutions is presented. Free acidity measurement refers to the acidity quantification in solutions containing hydrolysable heavy metal ions such as U(VI), U(IV) or Pu(IV) without taking into account the acidity contribution from the hydrolysis of such metal ions. It is, in fact, an operation having an essential role for the control of the nuclear fuel recycling process. The main objective behind the technical optimization of the actual ‘beaker’ method was to reduce the amount of radioactive substance to be handled by the laboratory personnel, to ease the instrumentation adjustability within a glove-box environment and to allow a high-throughput analysis for conducting more cost-effective operations. The measurement technique is based on the concept of the Taylor-Aris dispersion in order to create inside of a 200 μm x 5cm circular cylindrical micro-channel a linear concentration gradient in less than a second. The proposed analytical methodology relies on the actinide complexation using pH 5.6 sodium oxalate solution and subsequent alkalimetric titration of nitric acid with sodium hydroxide. The titration process is followed with a CCD camera for fluorescence detection; the neutralization boundary can be visualized in a detection range of 500nm- 600nm thanks to the addition of a pH sensitive fluorophore. The operating principle of the developed device allows the active generation of linear concentration gradients using a single cylindrical micro channel. This feature simplifies the fabrication and ease of use of the micro device, as it does not need a complex micro channel network or passive mixers to generate the chemical gradient. Moreover, since the linear gradient is determined by the liquid reagents input pressure, its generation can be fully achieved in faster intervals than one second, being a more timely-efficient gradient generation process compared to other source-sink passive diffusion devices. The resulting linear gradient generator device was therefore adapted to perform for the first time, a volumetric titration on a chip where the amount of reagents used is fixed to the total volume of the micro channel, avoiding an important waste generation like in other flow-based titration techniques. The associated analytical method is automated and its linearity has been proven for the free acidity determination of U(VI) samples containing up to 0.5M of actinide ion and nitric acid in a concentration range of 0.5M to 3M. In addition to automation, the developed analytical methodology and technique greatly improves the standard off-line oxalate complexation and alkalimetric titration method by reducing a thousand fold the required sample volume, forty times the nuclear waste per analysis as well as the analysis time by eight-fold. The developed device represents, therefore, a great step towards an easy-to-handle nuclear-related application, which in the short term could be used to improve laboratory safety as much as to reduce the environmental impact of the radioanalytical chain.

Keywords: free acidity, lab-on-a-chip, linear concentration gradient, Taylor-Aris dispersion, volumetric titration

Procedia PDF Downloads 365

Authors: Veenu Bala, Yashpal S. Chhonker, Bhavana Kushwaha, Rabi S. Bhatta, Gopal Gupta, Vishnu L. Sharma

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According to UNAIDS 2013 estimate nearly 52% of all individuals living with HIV are now women of reproductive age (15–44 years). Seventy-five percent cases of HIV acquisition are through heterosexual contacts and sexually transmitted infections (STIs), attributable to unsafe sexual behaviour. Each year, an estimated 500 million people acquire atleast one of four STIs: chlamydia, gonorrhoea, syphilis and trichomoniasis. Trichomonas vaginalis (TV) is exclusively sexually transmitted in adults, accounting for 30% of STI cases and associated with pelvic inflammatory disease (PID), vaginitis and pregnancy complications in women. TV infection resulted in impaired vaginal milieu, eventually favoring HIV transmission. In the absence of an effective prophylactic HIV vaccine, prevention of new infections has become a priority. It was thought worthwhile to integrate HIV prevention and reproductive health services including unintended pregnancy protection for women as both are related with unprotected sex. Initially, nonoxynol-9 (N-9) had been proposed as a spermicidal agent with microbicidal activity but on the contrary it increased HIV susceptibility due to surfactant action. Thus, to accomplish an urgent need of novel woman controlled non-detergent microbicidal spermicides benzenepropanamine analogues have been synthesized. At first, five benzenepropanamine-dithiocarbamate hybrids have been synthesized and evaluated for their spermicidal, anti-Trichomonas and anti-fungal activities along with safety profiling to cervicovaginal cells. In order to further enhance the scope of above study benzenepropanamine was hybridized with thiourea as to introduce anti-HIV potential. The synthesized hybrid molecules were evaluated for their reverse transcriptase (RT) inhibition, spermicidal, anti-Trichomonas and antimicrobial activities as well as their safety against vaginal flora and cervical cells. simulated vaginal fluid (SVF) stability and pharmacokinetics of most potent compound versus N-9 was examined in female Newzealand (NZ) rabbits to observe its absorption into systemic circulation and subsequent exposure in blood plasma through vaginal wall. The study resulted in the most promising compound N-butyl-4-(3-oxo-3-phenylpropyl) piperazin-1-carbothioamide (29) exhibiting better activity profile than N-9 as it showed RT inhibition (72.30 %), anti-Trichomonas (MIC, 46.72 µM against MTZ susceptible and MIC, 187.68 µM against resistant strain), spermicidal (MEC, 0.01%) and antifungal activity (MIC, 3.12–50 µg/mL) against four fungal strains. The high safety against vaginal epithelium (HeLa cells) and compatibility with vaginal flora (lactobacillus), SVF stability and least vaginal absorption supported its suitability for topical vaginal application. Docking study was performed to gain an insight into the binding mode and interactions of the most promising compound, N-butyl-4-(3-oxo-3-phenylpropyl) piperazin-1-carbothioamide (29) with HIV-1 Reverse Transcriptase. The docking study has revealed that compound (29) interacted with HIV-1 RT similar to standard drug Nevirapine. It may be concluded that hybridization of benzenepropanamine and thiourea moiety resulted into novel lead with multiple activities including RT inhibition. A further lead optimization may result into effective vaginal microbicides having spermicidal, anti-Trichomonas, antifungal and anti-HIV potential altogether with enhanced safety to cervico-vaginal cells in comparison to Nonoxynol-9.

Keywords: microbicidal, nonoxynol-9, reverse transcriptase, spermicide

Procedia PDF Downloads 328

Authors: Gerhard Gritsch, Ana Skupch, Manfred Hartmann, Wolfgang Frühwirt, Hannes Perko, Dieter Grossegger, Tilmann Kluge

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Rehabilitation of stroke patients is dominated by classical physiotherapy. Nowadays, a field of research is the application of neurofeedback techniques in order to help stroke patients to get rid of their motor impairments. Especially, if a certain limb is completely paralyzed, neurofeedback is often the last option to cure the patient. Certain exercises, like the imagination of the impaired motor function, have to be performed to stimulate the neuroplasticity of the brain, such that in the neighboring parts of the injured cortex the corresponding activity takes place. During the exercises, it is very important to keep the motivation of the patient at a high level. For this reason, the missing natural feedback due to a movement of the effected limb may be replaced by a synthetic feedback based on the motor-related brain function. To generate such a synthetic feedback a system is needed which measures, detects, localizes and visualizes the motor related µ-rhythm. Fast therapeutic success can only be achieved if the feedback features high specificity, comes in real-time and without large delay. We describe such an approach that offers a 3D visualization of µ-rhythms in real time with a delay of 500ms. This is accomplished by combining smart EEG preprocessing in the frequency domain with source localization techniques. The algorithm first selects the EEG channel featuring the most prominent rhythm in the alpha frequency band from a so-called motor channel set (C4, CZ, C3; CP6, CP4, CP2, CP1, CP3, CP5). If the amplitude in the alpha frequency band of this certain electrode exceeds a threshold, a µ-rhythm is detected. To prevent detection of a mixture of posterior alpha activity and µ-activity, the amplitudes in the alpha band outside the motor channel set are not allowed to be in the same range as the main channel. The EEG signal of the main channel is used as template for calculating the spatial distribution of the µ - rhythm over all electrodes. This spatial distribution is the input for a inverse method which provides the 3D distribution of the µ - activity within the brain which is visualized in 3D as color coded activity map. This approach mitigates the influence of lid artifacts on the localization performance. The first results of several healthy subjects show that the system is capable of detecting and localizing the rarely appearing µ-rhythm. In most cases the results match with findings from visual EEG analysis. Frequent eye-lid artifacts have no influence on the system performance. Furthermore, the system will be able to run in real-time. Due to the design of the frequency transformation the processing delay is 500ms. First results are promising and we plan to extend the test data set to further evaluate the performance of the system. The relevance of the system with respect to the therapy of stroke patients has to be shown in studies with real patients after CE certification of the system. This work was performed within the project ‘LiveSolo’ funded by the Austrian Research Promotion Agency (FFG) (project number: 853263).

Keywords: real-time EEG neuroimaging, neurofeedback, stroke, EEG–signal processing, rehabilitation

Procedia PDF Downloads 362

Authors: Ben Morrow, Patrick O'Hara, Natalie Ban, Tunai Marques, Molly Fraser, Christopher Bone

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Relative to commercial fisheries, recreational fisheries are often poorly understood and pose various challenges for monitoring frameworks. In British Columbia (BC), Canada, Pacific salmon are heavily targeted by recreational fishers while also being a key source of nutrient flow and crucial prey for a variety of marine and terrestrial fauna, including endangered Southern Resident killer whales (Orcinus orca). Although commercial fisheries were historically responsible for the majority of salmon retention, recreational fishing now comprises both greater effort and retention. The current monitoring scheme for recreational salmon fisheries involves aerial-roving creel surveys. However, this method has been identified as costly and having low predictive power as it is often limited to sampling fragments of fluid and temporally dynamic fisheries. This study used imagery from two shore-based autonomous cameras in a highly active recreational fishery around Sooke, BC, and evaluated their efficacy in supplementing existing aerial-roving surveys for monitoring a recreational salmon fishery. This study involved continuous monitoring and high temporal resolution (over one million images analyzed in a single fishing season), using a deep learning-based vessel detection algorithm and a custom image annotation tool to efficiently thin datasets. This allowed for the quantification of peak-season effort from a busy harbour, species-specific retention estimates, high levels of detected fishing events at a nearby popular fishing location, as well as the proportion of the fishery management area represented by cameras. Then, this study demonstrated how it could substantially enhance the temporal resolution of a fishery through diel activity pattern analyses, scaled monthly to visualize clusters of activity. This work also highlighted considerable off-season fishing detection, currently unaccounted for in the existing monitoring framework. These results demonstrate several distinct applications of autonomous cameras for providing enhanced detail currently unavailable in the current monitoring framework, each of which has important considerations for the managerial allocation of resources. Further, the approach and methodology can benefit other studies that apply shore-based camera monitoring, supplement aerial-roving creel surveys to improve fine-scale temporal understanding, inform the optimal timing of creel surveys, and improve the predictive power of recreational stock assessments to preserve important and endangered fish species.

Keywords: cameras, monitoring, recreational fishing, stock assessment

Procedia PDF Downloads 91

Authors: Hameed Rukayat Opeyemi, Pericles Pilidis, Pagone Emanuele

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Climate change represents one of the single most challenging problems facing the world today. According to the National Oceanic and Administrative Association, Atmospheric temperature rose almost 25% since 1958, Artic sea ice has shrunk 40% since 1959 and global sea levels have risen more than 5.5 cm since 1990. Power plants are the major culprits of GHG emission to the atmosphere. Several technologies have been proposed to reduce the amount of GHG emitted to the atmosphere from power plant, one of which is the less researched Advanced zero emission power plant. The advanced zero emission power plants make use of mixed conductive membrane (MCM) reactor also known as oxygen transfer membrane (OTM) for oxygen transfer. The MCM employs membrane separation process. The membrane separation process was first introduced in 1899 when Walter Hermann Nernst investigated electric current between metals and solutions. He found that when a dense ceramic is heated, current of oxygen molecules move through it. In the bid to curb the amount of GHG emitted to the atmosphere, the membrane separation process was applied to the field of power engineering in the low carbon cycle known as the Advanced zero emission power plant (AZEP cycle). The AZEP cycle was originally invented by Norsk Hydro, Norway and ABB Alstom power (now known as Demag Delaval Industrial turbo machinery AB), Sweden. The AZEP drew a lot of attention because its ability to capture ~100% CO2 and also boasts of about 30-50 % cost reduction compared to other carbon abatement technologies, the penalty in efficiency is also not as much as its counterparts and crowns it with almost zero NOx emissions due to very low nitrogen concentrations in the working fluid. The advanced zero emission power plants differ from a conventional gas turbine in the sense that its combustor is substituted with the mixed conductive membrane (MCM-reactor). The MCM-reactor is made up of the combustor, low temperature heat exchanger LTHX (referred to by some authors as air pre-heater the mixed conductive membrane responsible for oxygen transfer and the high temperature heat exchanger and in some layouts, the bleed gas heat exchanger. Air is taken in by the compressor and compressed to a temperature of about 723 Kelvin and pressure of 2 Mega-Pascals. The membrane area needed for oxygen transfer is reduced by increasing the temperature of 90% of the air using the LTHX; the temperature is also increased to facilitate oxygen transfer through the membrane. The air stream enters the LTHX through the transition duct leading to inlet of the LTHX. The temperature of the air stream is then increased to about 1150 K depending on the design point specification of the plant and the efficiency of the heat exchanging system. The amount of oxygen transported through the membrane is directly proportional to the temperature of air going through the membrane. The AZEP cycle was developed using the Fortran software and economic analysis was conducted using excel and Matlab followed by optimization case study. This paper discusses techno-economic analysis of four possible layouts of the AZEP cycle. The Simple bleed gas heat exchange layout (100 % CO2 capture), Bleed gas heat exchanger layout with flue gas turbine (100 % CO2 capture), Pre-expansion reheating layout (Sequential burning layout) – AZEP 85 % (85 % CO2 capture) and Pre-expansion reheating layout (Sequential burning layout) with flue gas turbine– AZEP 85 % (85 % CO2 capture). This paper discusses Montecarlo risk analysis of four possible layouts of the AZEP cycle.

Keywords: gas turbine, global warming, green house gases, power plants

Procedia PDF Downloads 450

Authors: Omaima A. Sharaf, Wafaa M. Abd El-Rahim, Hassan Moawad, Michael J. Sadowsky

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Textile industry is one of the important industries in the worldwide. It is known that the eco-friendly industrial and agricultural activities are significant for socio-economic stability of all countries. The absence of appropriate industrial waste water treatments is essential barrier for sustainable development in food and agricultural sectors especially in developing country like Egypt. Thus, the development of enzymatic bioremediation technology for textile dye removal will enhance the collaboration between scientists who develop the technology and industry where this technology will be implemented towards the safe disposal of the textile dye wastes. Highly efficient microorganisms are of most importance in developing and using highly effective biological treatment processes. Bacterial degradation of azo dyes is generally initiated by an enzymatic step that involves cleavage of azo linkages, usually with the aid of an azoreductase as electron donor. Thus, expanding the spectrum of microorganisms with high enzymatic activities as azoreductases and discovering novel azo-dye degrading enzymes, with enhanced stability and superior catalytic properties, are necessary for many environmental and industrial applications. Consequently, the use of molecular tools has become increasingly integrated into the understanding of enzyme properties and characterization. Researchers have utilized a gene cloning and expression methods as a tool to produce recombinant protein for decolorizing dyes more efficiently. Thus, presumptive evidence for the presence of genes encoding azoreductases in the genomes of selected local, and most potent azo-degrading strains were obtained by using specific oligonucleotides primers. These potent strains have been isolated from textile industrial wastewater in Egypt and identified using 16S rRNA sequence analysis as 'Lysinibacillus macrolidesB8, Brevibacillus parabrevisB11, Bacillus coagulansB7, and B. cereusB5'. PCR products of two full length genes designated as (AZO1;621bp and AZO2;534bp) were detected. BLASTx results indicated that AZO1 gene was corresponding to predicted azoreductase from of Bacillus sp. ABP14, complete genome, multispecies azoreductase [Bacillus], It was submitted to the gene bank by an accession no., BankIt2085371 AZO1 MG923210 (621bp; 207 amino acids). AZO1 was generated from the DNA of our identified strains Lysinibacillus macrolidesB8. On the other hand, AZO2 gene was corresponding to a predicted azoreductase from Bacillus cereus strain S2-8. Gene bank accession no. was BankIt2085839 AZO2 MG932081 (534bp;178 amino acids) and it was amplified from our Bacillus coagulansB7. Both genes were successfully cloned into pCR2.1TOPO (Invitrogen) and in pET28b+ vectors, then they transformed into E. coli DH5α and BL21(DE3) cells for heterologous expression studies. Our recombinant azoreductases (AZO1&AZO2) exhibited potential enzyme activity and efficiently decolorized an azo dye (Direct violet). They exhibited pH stability between 6 and 8 with optimum temperature up to 60°C and 37 °C after induction by 1mM and 1.5mM IPTG, for both AZO1 &AZO2, respectively. These results suggested that further optimization and purification of these recombinant proteins by using different heterologous expression systems will give great potential for the sustainable utilization of these recombinant enzymes in several industrial applications especially in wastewater treatments.

Keywords: azoreductases, decolorization, enzyme activity, gene cloning and expression

Procedia PDF Downloads 98

Authors: Farhan A. Alenizi

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Digital watermarking has evolved in the past years as an important means for data authentication and ownership protection. The images and video watermarking was well known in the field of multimedia processing; however, 3D objects' watermarking techniques have emerged as an important means for the same purposes, as 3D mesh models are in increasing use in different areas of scientific, industrial, and medical applications. Like the image watermarking techniques, 3D watermarking can take place in either space or transform domains. Unlike images and video watermarking, where the frames have regular structures in both space and temporal domains, 3D objects are represented in different ways as meshes that are basically irregular samplings of surfaces; moreover, meshes can undergo a large variety of alterations which may be hard to tackle. This makes the watermarking process more challenging. While the transform domain watermarking is preferable in images and videos, they are still difficult to implement in 3d meshes due to the huge number of vertices involved and the complicated topology and geometry, and hence the difficulty to perform the spectral decomposition, even though significant work was done in the field. Spatial domain watermarking has attracted significant attention in the past years; they can either act on the topology or on the geometry of the model. Exploiting the statistical characteristics in the 3D mesh models from both geometrical and topological aspects was useful in hiding data. However, doing that with minimal surface distortions to the mesh attracted significant research in the field. A 3D mesh blind watermarking technique is proposed in this research. The watermarking method depends on modifying the vertices' positions with respect to the center of the object. An optimal method will be developed to reduce the errors, minimizing the distortions that the 3d object may experience due to the watermarking process, and reducing the computational complexity due to the iterations and other factors. The technique relies on the displacement process of the vertices' locations depending on the modification of the variances of the vertices’ norms. Statistical analyses were performed to establish the proper distributions that best fit each mesh, and hence establishing the bins sizes. Several optimizing approaches were introduced in the realms of mesh local roughness, the statistical distributions of the norms, and the displacements in the mesh centers. To evaluate the algorithm's robustness against other common geometry and connectivity attacks, the watermarked objects were subjected to uniform noise, Laplacian smoothing, vertices quantization, simplification, and cropping. Experimental results showed that the approach is robust in terms of both perceptual and quantitative qualities. It was also robust against both geometry and connectivity attacks. Moreover, the probability of true positive detection versus the probability of false-positive detection was evaluated. To validate the accuracy of the test cases, the receiver operating characteristics (ROC) curves were drawn, and they’ve shown robustness from this aspect. 3D watermarking is still a new field but still a promising one.

Keywords: watermarking, mesh objects, local roughness, Laplacian Smoothing

Procedia PDF Downloads 138

Authors: Salvatore Luongo, Carlo Luongo

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This paper discusses the implementation solutions to reduce the computational load for the Traffic Situational Awareness with Alerts (TSAA) application, based on Automatic Dependent Surveillance-Broadcast (ADS-B) technology. In 2008, there were 23 total mid-air collisions involving general aviation fixed-wing aircraft, 6 of which were fatal leading to 21 fatalities. These collisions occurred during visual meteorological conditions, indicating the limitations of the see-and-avoid concept for mid-air collision avoidance as defined in the Federal Aviation Administration’s (FAA). The commercial aviation aircraft are already equipped with collision avoidance system called TCAS, which is based on classic transponder technology. This system dramatically reduced the number of mid-air collisions involving air transport aircraft. In general aviation, the same reduction in mid-air collisions has not occurred, so this reduction is the main objective of the TSAA application. The major difference between the original conflict detection application and the TSAA application is that the conflict detection is focused on preventing loss of separation in en-route environments. Instead TSAA is devoted to reducing the probability of mid-air collision in all phases of flight. The TSAA application increases the flight crew traffic situation awareness providing alerts of traffic that are detected in conflict with ownship in support of the see-and-avoid responsibility. The relevant effort has been spent in the design process and the code generation in order to maximize the efficiency and performances in terms of computational load and memory consumption reduction. The TSAA architecture is divided into two high-level systems: the “Threats database” and the “Conflict detector”. The first one receives the traffic data from ADS-B device and provides the memorization of the target’s data history. Conflict detector module estimates ownship and targets trajectories in order to perform the detection of possible future loss of separation between ownship and each target. Finally, the alerts are verified by additional conflict verification logic, in order to prevent possible undesirable behaviors of the alert flag. In order to reduce the computational load, a pre-check evaluation module is used. This pre-check is only a computational optimization, so the performances of the conflict detector system are not modified in terms of number of alerts detected. The pre-check module uses analytical trajectories propagation for both target and ownship. This allows major accuracy and avoids the step-by-step propagation, which requests major computational load. Furthermore, the pre-check permits to exclude the target that is certainly not a threat, using an analytical and efficient geometrical approach, in order to decrease the computational load for the following modules. This software improvement is not suggested by FAA documents, and so it is the main innovation of this work. The efficiency and efficacy of this enhancement are verified using fast-time and real-time simulations and by the execution on a real device in several FAA scenarios. The final implementation also permits the FAA software certification in compliance with DO-178B standard. The computational load reduction allows the installation of TSAA application also on devices with multiple applications and/or low capacity in terms of available memory and computational capabilities

Keywords: traffic situation awareness, general aviation, aircraft conflict detection, computational load reduction, implementation solutions, software certification

Procedia PDF Downloads 254

Authors: Vanja Vlajkov, Ivana PajčIn, Mila Grahovac, Marta Loc, Dragana Budakov, Jovana Grahovac

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The rhizosphere soil refers to the plant roots' dynamic environment characterized by their inhabitants' high biological activity. Rhizospheric bacteria are recognized as effective biocontrol agents and considered cardinal in alternative strategies for securing ecological plant diseases management. The need to suppress fungal pathogens is an urgent task, not only because of the direct economic losses caused by infection but also due to their ability to produce mycotoxins with harmful effects on human health. Aspergillus and Fusarium species are well-known producers of toxigenic metabolites with a high capacity to colonize crops and enter the food chain. The bacteria belonging to the Bacillus genus has been conceded as a plant beneficial species in agricultural practice and identified as plant growth-promoting rhizobacteria (PGPR). Besides incontestable potential, the full commercialization of microbial biopesticides is in the preliminary phase. Thus, there is a constant need for estimating the suitability of novel strains to be used as a central point of viable bioprocess leading to market-ready product development. In the present study, 76 potential producing strains were isolated from the rhizosphere soil, sampled from different localities in the Autonomous Province of Vojvodina, Republic of Serbia. The selective isolation process of strains started by resuspending 1 g of soil samples in 9 ml of saline and incubating at 28° C for 15 minutes at 150 rpm. After homogenization, thermal treatment at 100° C for 7 minutes was performed. Dilution series (10-1-10-3) were prepared, and 500 µl of each was inoculated on nutrient agar plates and incubated at 28° C for 48 h. The pure cultures of morphologically different strains indicating belonging to the Bacillus genus were obtained by the spread-plate technique. The cultivation of the isolated strains was carried out in an Erlenmeyer flask for 96 h, at 28 °C, 170 rpm. The antagonistic activity screening included two phytopathogenic fungi as test microorganisms: Aspergillus sp. and Fusarium sp. The mycelial growth inhibition was estimated based on the antimicrobial activity testing of cultivation broth by the diffusion method. For the Aspergillus sp., the highest antifungal activity was recorded for the isolates Kro-4a and Mah-1a. In contrast, for the Fusarium sp., following 15 isolates exhibited the highest antagonistic effect Par-1, Par-2, Par-3, Par-4, Kup-4, Paš-1b, Pap-3, Kro-2, Kro-3a, Kro-3b, Kra-1a, Kra-1b, Šar-1, Šar-2b and Šar-4. One-way ANOVA was performed to determine the antagonists' effect statistical significance on inhibition zone diameter. Duncan's multiple range test was conducted to define homogenous groups of antagonists with the same level of statistical significance regarding their effect on antimicrobial activity of the tested cultivation broth against tested pathogens. The study results have pointed out the significant in vitro potential of the isolated strains to be used as biocontrol agents for the suppression of the tested mycotoxigenic fungi. Further research should include the identification and detailed characterization of the most promising isolates and mode of action of the selected strains as biocontrol agents. The following research should also involve bioprocess optimization steps to fully reach the selected strains' potential as microbial biopesticides and design cost-effective biotechnological production.

Keywords: Bacillus, biocontrol, bioprocess, mycotoxigenic fungi

Procedia PDF Downloads 174

Authors: Brayden Mi

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Reverse time migration has been widely used in the Petroleum exploration industry to reveal subsurface images and to detect rock and fluid properties since the early 1980s. The seismic technology involves the construction of a velocity model through interpretive model construction, seismic tomography, or full waveform inversion, and the application of the reverse-time propagation of acquired seismic data and the original wavelet used in the acquisition. The methodology has matured from 2D, simple media to present-day to handle full 3D imaging challenges in extremely complex geological conditions. Conventional Ultrasound computed tomography (USCT) utilize travel-time-inversion to reconstruct the velocity structure of an organ. With the velocity structure, USCT data can be migrated with the “bend-ray” method, also known as migration. Its seismic application counterpart is called Kirchhoff depth migration, in which the source of reflective energy is traced by ray-tracing and summed to produce a subsurface image. It is well known that ray-tracing-based migration has severe limitations in strongly heterogeneous media and irregular acquisition geometries. Reverse time migration (RTM), on the other hand, fully accounts for the wave phenomena, including multiple arrives and turning rays due to complex velocity structure. It has the capability to fully reconstruct the image detectable in its acquisition aperture. The RTM algorithms typically require a rather accurate velocity model and demand high computing powers, and may not be applicable to real-time imaging as normally required in day-to-day medical operations. However, with the improvement of computing technology, such a computational bottleneck may not present a challenge in the near future. The present-day (RTM) algorithms are typically implemented from a flat datum for the seismic industry. It can be modified to accommodate any acquisition geometry and aperture, as long as sufficient illumination is provided. Such flexibility of RTM can be conveniently implemented for the application in USCT imaging if the spatial coordinates of the transmitters and receivers are known and enough data is collected to provide full illumination. This paper proposes an implementation of a full 3D RTM algorithm for USCT imaging to produce an accurate 3D acoustic image based on the Phase-shift-plus-interpolation (PSPI) method for wavefield extrapolation. In this method, each acquired data set (shot) is propagated back in time, and a known ultrasound wavelet is propagated forward in time, with PSPI wavefield extrapolation and a piece-wise constant velocity model of the organ (breast). The imaging condition is then applied to produce a partial image. Although each image is subject to the limitation of its own illumination aperture, the stack of multiple partial images will produce a full image of the organ, with a much-reduced noise level if compared with individual partial images.

Keywords: illumination, reverse time migration (RTM), ultrasound computed tomography (USCT), wavefield extrapolation

Procedia PDF Downloads 50

Authors: İsmail Kavdır, M. Burak Büyükcan, Ferhat Kurtulmuş

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Table olive is a valuable product especially in Mediterranean countries. It is usually consumed after some fermentation process. Defects happened naturally or as a result of an impact while olives are still fresh may become more distinct after processing period. Defected olives are not desired both in table olive and olive oil industries as it will affect the final product quality and reduce market prices considerably. Therefore it is critical to sort table olives before processing or even after processing according to their quality and surface defects. However, doing manual sorting has many drawbacks such as high expenses, subjectivity, tediousness and inconsistency. Quality criterions for green olives were accepted as color and free of mechanical defects, wrinkling, surface blemishes and rotting. In this study, it was aimed to classify fresh table olives using different classifiers and NIR spectroscopy readings and also to compare the classifiers. For this purpose, green (Ayvalik variety) olives were classified based on their surface feature properties such as defect-free, with bruised defect and with fly defect using FT-NIR spectroscopy and classification algorithms such as artificial neural networks, ident and cluster. Bruker multi-purpose analyzer (MPA) FT-NIR spectrometer (Bruker Optik, GmbH, Ettlingen Germany) was used for spectral measurements. The spectrometer was equipped with InGaAs detectors (TE-InGaAs internal for reflectance and RT-InGaAs external for transmittance) and a 20-watt high intensity tungsten–halogen NIR light source. Reflectance measurements were performed with a fiber optic probe (type IN 261) which covered the wavelengths between 780–2500 nm, while transmittance measurements were performed between 800 and 1725 nm. Thirty-two scans were acquired for each reflectance spectrum in about 15.32 s while 128 scans were obtained for transmittance in about 62 s. Resolution was 8 cm⁻¹ for both spectral measurement modes. Instrument control was done using OPUS software (Bruker Optik, GmbH, Ettlingen Germany). Classification applications were performed using three classifiers; Backpropagation Neural Networks, ident and cluster classification algorithms. For these classification applications, Neural Network tool box in Matlab, ident and cluster modules in OPUS software were used. Classifications were performed considering different scenarios; two quality conditions at once (good vs bruised, good vs fly defect) and three quality conditions at once (good, bruised and fly defect). Two spectrometer readings were used in classification applications; reflectance and transmittance. Classification results obtained using artificial neural networks algorithm in discriminating good olives from bruised olives, from olives with fly defect and from the olive group including both bruised and fly defected olives with success rates respectively changing between 97 and 99%, 61 and 94% and between 58.67 and 92%. On the other hand, classification results obtained for discriminating good olives from bruised ones and also for discriminating good olives from fly defected olives using the ident method ranged between 75-97.5% and 32.5-57.5%, respectfully; results obtained for the same classification applications using the cluster method ranged between 52.5-97.5% and between 22.5-57.5%.

Keywords: artificial neural networks, statistical classifiers, NIR spectroscopy, reflectance, transmittance

Procedia PDF Downloads 224

Authors: Korbinian Schmidtner, Rudolf Sailer, Perry Bartelt, Wolfgang Fellin, Jan-Thomas Fischer, Matthias Granig

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This study focuses on the evaluation of snow avalanche simulations, based on a survey that has been carried out among avalanche experts. In the last decades, the application of avalanche simulation tools has gained recognition within the realm of hazard management. Traditionally, avalanche runout models were used to predict extreme avalanche runout and prepare avalanche maps. This has changed rather dramatically with the application of numerical models. For safety regulations such as road safety simulation tools are now being coupled with real-time meteorological measurements to predict frequent avalanche hazard. That places new demands on model accuracy and requires the simulation of physical processes that previously could be ignored. These simulation tools are based on a deterministic description of the avalanche movement allowing to predict certain quantities (e.g. pressure, velocities, flow heights, runout lengths etc.) of the avalanche flow. Because of the highly variable regimes of the flowing snow, no uniform rheological law describing the motion of an avalanche is known. Therefore, analogies to fluid dynamical laws of other materials are stated. To transfer these constitutional laws to snow flows, certain assumptions and adjustments have to be imposed. Besides these limitations, there exist high uncertainties regarding the initial and boundary conditions. Further challenges arise when implementing the underlying flow model equations into an algorithm executable by a computer. This implementation is constrained by the choice of adequate numerical methods and their computational feasibility. Hence, the model development is compelled to introduce further simplifications and the related uncertainties. In the light of these issues many questions arise on avalanche simulations, on their assets and drawbacks, on potentials for improvements as well as their application in practice. To address these questions a survey among experts in the field of avalanche science (e.g. researchers, practitioners, engineers) from various countries has been conducted. In the questionnaire, special attention is drawn on the expert’s opinion regarding the influence of certain variables on the simulation result, their uncertainty and the reliability of the results. Furthermore, it was tested to which degree a simulation result influences the decision making for a hazard assessment. A discrepancy could be found between a large uncertainty of the simulation input parameters as compared to a relatively high reliability of the results. This contradiction can be explained taking into account how the experts employ the simulations. The credibility of the simulations is the result of a rather thoroughly simulation study, where different assumptions are tested, comparing the results of different flow models along with the use of supplemental data such as chronicles, field observation, silent witnesses i.a. which are regarded as essential for the hazard assessment and for sanctioning simulation results. As the importance of avalanche simulations grows within the hazard management along with their further development studies focusing on the modeling fashion could contribute to a better understanding how knowledge of the avalanche process can be gained by running simulations.

Keywords: expert interview, hazard management, modeling, simulation, snow avalanche

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Authors: M. Shahab Uddin, Pennung Warnitchai

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Currently more than half of the world’s populations are living in cities, and the number and sizes of cities are growing faster than ever. Cities rely on the effective functioning of complex and interdependent critical infrastructures networks to provide public services, enhance the quality of life, and save the community from hazards and disasters. In contrast, complex connectivity and interdependency among the urban critical infrastructures bring management challenges and make the urban system prone to the domino effect. Unplanned rapid growth, increased connectivity, and interdependency among the infrastructures, resource scarcity, and many other socio-political factors are affecting the typical state of an urban system and making it susceptible to numerous sorts of diversion. In addition to internal vulnerabilities, urban systems are consistently facing external threats from natural and manmade hazards. Cities are not just complex, interdependent system, but also makeup hubs of the economy, politics, culture, education, etc. For survival and sustainability, complex urban systems in the current world need to manage their vulnerabilities and hazardous incidents more wisely and more interactively. Coordinated management in such systems makes for huge potential when it comes to absorbing negative effects in case some of its components were to function improperly. On the other hand, ineffective management during a similar situation of overall disorder from hazards devastation may make the system more fragile and push the system to an ultimate collapse. Following the quantum, the current research hypothesizes that a hazardous event starts its journey as an emergency, and the system’s internal vulnerability and response capacity determine its destination. Connectivity and interdependency among the urban critical infrastructures during this stage may transform its vulnerabilities into dynamic damaging force. An emergency may turn into a disaster in the absence of effective management; similarly, mismanagement or lack of management may lead the situation towards a catastrophe. Situation awareness and factual decision-making is the key to win a battle. The current research proposed a contextual decision support system for an urban critical infrastructure system while integrating three different models: 1) Damage cascade model which demonstrates damage propagation among the infrastructures through their connectivity and interdependency, 2) Restoration model, a dynamic restoration process of individual infrastructure, which is based on facility damage state and overall disruptions in surrounding support environment, and 3) Optimization model that ensures optimized utilization and distribution of available resources in and among the facilities. All three models are tightly connected, mutually interdependent, and together can assess the situation and forecast the dynamic outputs of every input. Moreover, this integrated model will hold disaster managers and decision makers responsible when it comes to checking all the alternative decision before any implementation, and support to produce maximum possible outputs from the available limited inputs. This proposed model will not only support to reduce the extent of damage cascade but will ensure priority restoration and optimize resource utilization through adaptive and collaborative management. Complex systems predictably fail but in unpredictable ways. System understanding, situation awareness, and factual decisions may significantly help urban system to survive and sustain.

Keywords: disaster prevention, decision support system, emergency response, urban critical infrastructure system

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Authors: Ramesh P., Aby Joseph

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Micro Inverters provide Module Embedded Solution for harvesting energy from small-scale solar photovoltaic (PV) panels. In addition to higher modularity & reliability (25 years of life), the MicroInverter has inherent advantages such as avoidance of long DC cables, eliminates module mismatch losses, minimizes partial shading effect, improves safety and flexibility in installations etc. Due to the above-stated benefits, the renewable energy technology with Solar Photovoltaic (PV) Micro Inverter becomes more widespread in Village Nano Grid application ensuring grid independence for rural communities and areas without access to electricity. While the primary objective of this paper is to discuss the problems related to rural electrification, this concept can also be extended to urban installation with grid connectivity. This work presents a comprehensive analysis of the power circuit design, control methodologies and prototyping of 300Wₚ Single Phase PV Micro Inverter. This paper investigates two different topologies for PV Micro Inverters, based on the first hand on Single Stage Flyback/ Forward PV Micro-Inverter configuration and the other hand on the Double stage configuration including DC-DC converter, H bridge DC-AC Inverter. This work covers Power Decoupling techniques to reduce the input filter capacitor size to buffer double line (100 Hz) ripple energy and eliminates the use of electrolytic capacitors. The propagation of the double line oscillation reflected back to PV module will affect the Maximum Power Point Tracking (MPPT) performance. Also, the grid current will be distorted. To mitigate this issue, an independent MPPT control algorithm is developed in this work to reject the propagation of this double line ripple oscillation to PV side to improve the MPPT performance and grid side to improve current quality. Here, the power hardware topology accepts wide input voltage variation and consists of suitably rated MOSFET switches, Galvanically Isolated gate drivers, high-frequency magnetics and Film capacitors with a long lifespan. The digital controller hardware platform inbuilt with the external peripheral interface is developed using floating point microcontroller TMS320F2806x from Texas Instruments. The firmware governing the operation of the PV Micro Inverter is written in C language and was developed using code composer studio Integrated Development Environment (IDE). In this work, the prototype hardware for the Single Phase Photovoltaic Micro Inverter with Double stage configuration was developed and the comparative analysis between the above mentioned configurations with experimental results will be presented.

Keywords: double line oscillation, micro inverter, MPPT, nano grid, power decoupling

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Authors: Svetlana Petrikova, Alexander Yu Kostinskiy

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Management of research evaluation in the Higher School of Economics (HSE) originates from the HSE Academic Fund created in 2004 to facilitate and support academic research and presents its results to international academic community. As the means to inspire the applicants, science projects went through competitive selection process evaluated by the group of experts. Drastic development of HSE, quantity of applied projects for each Academic Fund competition and the need to coordinate the conduct of expert evaluation resulted in founding of the Office for Research Evaluation in 2013. The Office’s primary objective is management of research evaluation of science projects. The standards to conduct the evaluation are defined as follows: - The exercise of the process approach, the unification of the functioning of department. - The uniformity of regulatory, organizational and methodological framework. - The development of proper on-line evaluation system. - The broad involvement of external Russian and international experts, the renouncement of the usage of own employees. - The development of an algorithm to make a correspondence between experts and science projects. - The methodical usage of opened/closed international and Russian databases to extend the expert database. - The transparency of evaluation results – free access to assessment while keeping experts confidentiality. The management of research evaluation of projects is based on the sole standard, organization and financing. The standard way of conducting research evaluation at HSE is based upon Regulations on basic principles for research evaluation at HSE. These Regulations have been developed from the moment of establishment of the Office for Research Evaluation and are based on conventional corporate standards for regulatory document management. The management system of research evaluation is implemented on the process approach basis. Process approach means deployment of work as a process, which is the aggregation of interrelated and interacting activities processing inputs into outputs. Inputs are firstly client asking for the assessment to be conducted, defining the conditions for organizing and carrying of the assessment and secondly the applicant with proper for the competition application; output is assessment given to the client. While exercising process approach to clarify interrelation and interacting main parties or subjects of the assessment are determined and the way for interaction between them forms up. Parties to expert assessment are: - Ordering Party – The department of the university taking the decision to subject a project to expert assessment; - Providing Party – The department of the university authorized to provide such assessment by the Ordering Party; - Performing Party – The legal and natural entities that have expertise in the area of research evaluation. Experts assess projects in accordance with criteria and states of expert opinions approved by the Ordering Party. Objects of assessment generally are applications or HSE competition project reports. Mainly assessments are deployed for internal needs, i.e. the most ordering parties are HSE branches and departments, but assessment can also be conducted for external clients. The financing of research evaluation at HSE is based on the established corporate culture and traditions of HSE.

Keywords: expert assessment, management of research evaluation, process approach, research evaluation

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Authors: Andrey Cherdantsev, Mikhail Cherdantsev, Sergey Isaenkov, Dmitriy Markovich

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In annular gas-liquid flow, liquid flows as a film along pipe walls sheared by high-velocity gas stream. Film surface is covered by large-scale disturbance waves which affect pressure drop and heat transfer in the system and are necessary for entrainment of liquid droplets from film surface into the core of gas stream. Disturbance waves are a highly complex and their properties are affected by numerous parameters. One of such aspects is flow development, i.e., change of flow properties with the distance from the inlet. In the present work, this question is studied using brightness-based laser-induced fluorescence (BBLIF) technique. This method enables one to perform simultaneous measurements of local film thickness in large number of points with high sampling frequency. In the present experiments first 50 cm of upward and downward annular flow in a vertical pipe of 11.7 mm i.d. is studied with temporal resolution of 10 kHz and spatial resolution of 0.5 mm. Thus, spatiotemporal evolution of film surface can be investigated, including scenarios of formation, acceleration and coalescence of disturbance waves. The behaviour of disturbance waves' velocity depending on phases flow rates and downstream distance was investigated. Besides measuring the waves properties, the goal of the work was to investigate the interrelation between disturbance waves properties and integral characteristics of the flow such as interfacial shear stress and flow rate of dispersed phase. In particular, it was shown that the initial acceleration of disturbance waves, defined by the value of shear stress, linearly decays with downstream distance. This lack of acceleration which may even lead to deceleration is related to liquid entrainment. Flow rate of disperse phase linearly grows with downstream distance. During entrainment events, liquid is extracted directly from disturbance waves, reducing their mass, area of interaction to the gas shear and, hence, velocity. Passing frequency of disturbance waves at each downstream position was measured automatically with a new algorithm of identification of characteristic lines of individual disturbance waves. Scenarios of coalescence of individual disturbance waves were identified. Transition from initial high-frequency Kelvin-Helmholtz waves appearing at the inlet to highly nonlinear disturbance waves with lower frequency was studied near the inlet using 3D realisation of BBLIF method in the same cylindrical channel and in a rectangular duct with cross-section of 5 mm by 50 mm. It was shown that the initial waves are generally two-dimensional but are promptly broken into localised three-dimensional wavelets. Coalescence of these wavelets leads to formation of quasi two-dimensional disturbance waves. Using cross-correlation analysis, loss and restoration of two-dimensionality of film surface with downstream distance were studied quantitatively. It was shown that all the processes occur closer to the inlet at higher gas velocities.

Keywords: annular flow, disturbance waves, entrainment, flow development

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Authors: D. Bianco, A. Sollazzo, M. Barbarino, G. Elia, A. Smoraldi, N. Favaloro

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The activities, described in the present paper, have been conducted in the framework of the HYPROB-New Program, carried out by the Italian Aerospace Research Centre (CIRA) promoted and funded by the Italian Ministry of University and Research (MIUR) in order to improve the National background on rocket engine systems for space applications. The Program has the strategic objective to improve National system and technology capabilities in the field of liquid rocket engines (LRE) for future Space Propulsion Systems applications, with specific regard to LOX/LCH4 technology. The main purpose of the HYPROB program is to design and build a Propulsion Test Facility (HIMP) allowing test activities on Liquid Thrusters. The development of skills in liquid rocket propulsion can only pass through extensive test campaign. Following its mission, CIRA has planned the development of new testing facilities and infrastructures for space propulsion characterized by adequate sizes and instrumentation. The IMP test cell is devoted to testing articles representative of small combustion chambers, fed with oxygen and methane, both in liquid and gaseous phase. This article describes the activities that have been carried out for the evaluation of the acoustic impact, and its consequent mitigation. The impact of the simulated acoustic disturbance has been evaluated, first, using an approximated method based on experimental data by Baumann and Coney, included in “Noise and Vibration Control Engineering” edited by Vér and Beranek. This methodology, used to evaluate the free-field radiation of jet in ideal acoustical medium, analyzes in details the jet noise and assumes sources acting at the same time. It considers as principal radiation sources the jet mixing noise, caused by the turbulent mixing of jet gas and the ambient medium. Empirical models, allowing a direct calculation of the Sound Pressure Level, are commonly used for rocket noise simulation. The model named after K. Eldred is probably one of the most exploited in this area. In this paper, an improvement of the Eldred Standard model has been used for a detailed investigation of the acoustical impact of the Hyprob facility. This new formulation contains an explicit expression for the acoustic pressure of each equivalent noise source, in terms of amplitude and phase, allowing the investigation of the sources correlation effects and their propagation through wave equations. In order to enhance the evaluation of the facility acoustic impact, including an assessment of the mitigation strategies to be set in place, a more advanced simulation campaign has been conducted using both an in-house code for noise propagation and scattering, and a commercial code for industrial noise environmental impact, CadnaA. The noise prediction obtained with the revised Eldred-based model has then been used for formulating an empirical/BEM (Boundary Element Method) hybrid approach allowing the evaluation of the barrier mitigation effect, at the design. This approach has been compared with the analogous empirical/ray-acoustics approach, implemented within CadnaA using a customized definition of sources and directivity factor. The resulting impact evaluation study is reported here, along with the design-level barrier optimization for noise mitigation.

Keywords: acoustic impact, industrial noise, mitigation, rocket noise

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Authors: Simon Komesker, Achim Wagner, Martin Ruskowski

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In times of volatile markets with fluctuating demand and the uncertainty of global supply chains, flexible production systems are the key to an efficient implementation of a desired production program. In this publication, the authors present a holistic information concept taking into account various influencing factors for operating towards the global optimum. Therefore, a strategy for the implementation of multi-level planning for a flexible, reconfigurable production system with an alternative production concept in the automotive industry is developed. The main contribution of this work is a system structure mixing central and decentral planning and control evaluated in a simulation framework. The information system structure in current production systems in the automotive industry is rigidly hierarchically organized in monolithic systems. The production program is created rule-based with the premise of achieving uniform cycle time. This program then provides the information basis for execution in subsystems at the station and process execution level. In today's era of mixed-(car-)model factories, complex conditions and conflicts arise in achieving logistics, quality, and production goals. There is no provision for feedback loops of results from the process execution level (resources) and process supporting (quality and logistics) systems and reconsideration in the planning systems. To enable a robust production flow, the complexity of production system control is artificially reduced by the line structure and results, for example in material-intensive processes (buffers and safety stocks - two container principle also for different variants). The limited degrees of freedom of line production have produced the principle of progress figure control, which results in one-time sequencing, sequential order release, and relatively inflexible capacity control. As a result, modularly structured production systems such as modular production according to known approaches with more degrees of freedom are currently difficult to represent in terms of information technology. The remedy is an information concept that supports cross-system and cross-level information processing for centralized and decentralized decision-making. Through an architecture of hierarchically organized but decoupled subsystems, the paradigm of hybrid control is used, and a holonic manufacturing system is offered, which enables flexible information provisioning and processing support. In this way, the influences from quality, logistics, and production processes can be linked holistically with the advantages of mixed centralized and decentralized planning and control. Modular production systems also require modularly networked information systems with semi-autonomous optimization for a robust production flow. Dynamic prioritization of different key figures between subsystems should lead the production system to an overall optimum. The tasks and goals of quality, logistics, process, resource, and product areas in a cyber-physical production system are designed as an interconnected multi-agent-system. The result is an alternative system structure that executes centralized process planning and decentralized processing. An agent-based manufacturing control is used to enable different flexibility and reconfigurability states and manufacturing strategies in order to find optimal partial solutions of subsystems, that lead to a near global optimum for hybrid planning. This allows a robust near to plan execution with integrated quality control and intralogistics.

Keywords: holonic manufacturing system, modular production system, planning, and control, system structure

Procedia PDF Downloads 149