Search results for: fiber optic cable installation optimization

Authors: Nabil Elkhatri, Mohamed Louay Metougui, Ngonidzashe Chirinda

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Mining activities have left a legacy of degraded landscapes, prompting urgent efforts for ecological restoration. Reforestation holds promise as a potent tool to rehabilitate these old mining sites, with the potential to sequester carbon and contribute to climate change mitigation. This study focuses on evaluating the carbon stock and sequestration potential of reforestation species in the context of Morocco's mining areas, employing the DeNitrification-DeComposition (DNDC) model. The research is grounded in recognizing the need to connect theoretical models with practical implementation, ensuring that reforestation efforts are informed by accurate and context-specific data. Field data collection encompasses growth patterns, biomass accumulation, and carbon sequestration rates, establishing an empirical foundation for the study's analyses. By integrating the collected data with the DNDC model, the study aims to provide a comprehensive understanding of carbon dynamics within reforested ecosystems on old mining sites. The major findings reveal varying sequestration rates among different reforestation species, indicating the potential for species-specific optimization of reforestation strategies to enhance carbon capture. This research's significance lies in its potential to contribute to sustainable land management practices and climate change mitigation strategies. By quantifying the carbon stock and sequestration potential of reforestation species, the study serves as a valuable resource for policymakers, land managers, and practitioners involved in ecological restoration and carbon management. Ultimately, the study aligns with global objectives to rejuvenate degraded landscapes while addressing pressing climate challenges.

Keywords: carbon stock, carbon sequestration, DNDC model, ecological restoration, mining sites, Morocco, reforestation, sustainable land management.

Procedia PDF Downloads 55

Authors: Beihai Xiong, Dengke Hua, Wouter Hendriks, Wilbert Pellikaan

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To improve the energy status of dairy cows in the early lactation, lots of jobs have been done on adjusting the starch to fiber ratio in the diet. As a complex ecosystem, the rumen contains a large population of microorganisms which plays a crucial role in feed degradation. Further study on the microbiota alterations and metabolic changes under different dietary energy sources is essential and valuable to better understand the function of the ruminal microorganisms and thereby to optimize the rumen function and enlarge feed efficiency. The present study will focus on the effects of two glucogenic diets (G: ground corn and corn silage; S: steam-flaked corn and corn silage) and a lipogenic diet (L: sugar beet pulp and alfalfa silage) on rumen fermentation, gas production, the ruminal microbiota and metabolome, and also their correlations in vitro. The gas production was recorded consistently, and the gas volume and producing rate at times 6, 12, 24, 48 h were calculated separately. The fermentation end-products were measured after fermenting for 48 h. The ruminal bacteria and archaea communities were determined by 16S RNA sequencing technique, the metabolome profile was tested through LC-MS methods. Compared to the diet G and S, the L diet had a lower dry matter digestibility, propionate production, and ammonia-nitrogen concentration. The two glucogenic diets performed worse in controlling methane and lactic acid production compared to the L diet. The S diet produced the greatest cumulative gas volume at any time points during incubation compared to the G and L diet. The metabolic analysis revealed that the lipid digestion was up-regulated by the diet L than other diets. On the subclass level, most metabolites belonging to the fatty acids and conjugates were higher, but most metabolites belonging to the amino acid, peptides, and analogs were lower in diet L than others. Differences in rumen fermentation characteristics were associated with (or resulting from) changes in the relative abundance of bacterial and archaeal genera. Most highly abundant bacteria were stable or slightly influenced by diets, while several amylolytic and cellulolytic bacteria were sensitive to the dietary changes. The L diet had a significantly higher number of cellulolytic bacteria, including the genera of Ruminococcus, Butyrivibrio, Eubacterium, Lachnospira, unclassified Lachnospiraceae, and unclassified Ruminococcaceae. The relative abundances of amylolytic bacteria genera including Selenomonas_1, Ruminobacter, and Succinivibrionaceae_UCG-002 were higher in diet G and S. These affected bacteria was also proved to have high associations with certain metabolites. The Selenomonas_1 and Succinivibrionaceae_UCG-002 may contribute to the higher propionate production in the diet G and S through enhancing the succinate pathway. The results indicated that the two glucogenic diets had a greater extent of gas production, a higher dry matter digestibility, and produced more propionate than diet L. The steam-flaked corn did not show a better performance on fermentation end-products than ground corn. This study has offered a deeper understanding of ruminal microbial functions which could assistant the improvement in rumen functions and thereby in the ruminant production.

Keywords: gas production, metabolome, microbiota, rumen fermentation

Procedia PDF Downloads 129

Authors: Adel A. Ghoneim

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Desalination using solar energy is an interesting option specifically at regions with abundant solar radiation since such areas normally have scarcity of clean water resources. Desalination is the procedure of eliminating dissolved minerals from seawater or brackish water to generate fresh water. In this work, a simulation program is developed to determine the performance of reverse osmosis (RO) water desalination plant powered by high concentrated photovoltaic (HCPV) panels in Kuwait climate conditions. The objective of such a photovoltaic thermal system is to accomplish a double output, i.e., co-generation of both electricity and fresh water that is applicable for rural regions with high solar irradiation. The suggested plan enables to design an RO plant that does not depend on costly batteries or additional land and significantly reduce the government costs to subsidize the water generation cost. Typical weather conditions for Kuwait is employed as input to the simulation program. The simulation program is utilized to optimize the system efficiency as well as the distillate water production. The areas and slopes of HCPV modules are varied to attain maximum yearly power production. Maximum yearly distillate production and HCPV energy generation are found to correspond to HCPV facing south with tilt of 27° (Kuwait latitude-3°). The power needed to produce 1 l of clean drinking water ranged from 2 to 8 kW h/m³, based on the salinity of the feed water and the system operating conditions. Moreover, adapting HCPV systems achieve an avoided greenhouse gases emission by about 1128 ton CO₂ annually. Present outcomes certainly illustrate environmental advantages of water desalination system powered by high concentrated photovoltaic systems in Kuwait climate conditions.

Keywords: desalination, high concentrated photovoltaic systems, reverse osmosis, solar radiation

Procedia PDF Downloads 120

Authors: Sung-Jun Yoo, Kazuhide Ito

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In this study, a comprehensive computer simulated person (CSP) that integrates computational human model (virtual manikin) and respiratory tract model (virtual airway), was applied for estimation of indoor environmental quality. Moreover, an inclusive prediction method was established by integrating computational fluid dynamics (CFD) analysis with advanced CSP which is combined with physiologically-based pharmacokinetic (PBPK) model, unsteady thermoregulation model for analysis targeting micro-climate around human body and respiratory area with high accuracy. This comprehensive method can estimate not only the contaminant inhalation but also constant interaction in the contaminant transfer between indoor spaces, i.e., a target area for indoor air quality (IAQ) assessment, and respiratory zone for health risk assessment. This study focused on the usage of the CSP as an air/thermal quality sensor in indoors, which means the application of comprehensive model for assessment of IAQ and thermal environmental quality. Demonstrative analysis was performed in order to examine the applicability of the comprehensive model to the heating, ventilation, air conditioning (HVAC) control scheme. CSP was located at the center of the simple model room which has dimension of 3m×3m×3m. Formaldehyde which is generated from floor material was assumed as a target contaminant, and flow field, sensible/latent heat and contaminant transfer analysis in indoor space were conducted by using CFD simulation coupled with CSP. In this analysis, thermal comfort was evaluated by thermoregulatory analysis, and respiratory exposure risks represented by adsorption flux/concentration at airway wall surface were estimated by PBPK-CFD hybrid analysis. These Analysis results concerning IAQ and thermal comfort will be fed back to the HVAC control and could be used to find a suitable ventilation rate and energy requirement for air conditioning system.

Keywords: CFD simulation, computer simulated person, HVAC control, indoor environmental quality

Procedia PDF Downloads 341

Authors: Laure Wiest, Barbara Giroud, Azziz Assoumani, Francois Lestremau, Emmanuelle Vulliet

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Due to their production at high tonnages and their extensive use, surfactants are contaminants among those determined at the highest concentrations in wastewater. However, analytical methods and data regarding their occurrence in river water are scarce and concern only a few families, mainly anionic surfactants. The objective of this study was to develop an analytical method to extract and analyze a wide variety of surfactants in a minimum of steps, with a sensitivity compatible with the detection of ultra-traces in surface waters. 27 substances, from 12 families of surfactants, anionic, cationic and non-ionic were selected for method optimization. Different retention mechanisms for the extraction by solid phase extraction (SPE) were tested and compared in order to improve their detection by liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS). The best results were finally obtained with a C18 grafted silica LC column and a polymer cartridge with hydrophilic lipophilic balance (HLB), and the method developed allows the extraction of the three types of surfactants with satisfactory recoveries. The final analytical method comprised only one extraction and two LC injections. It was validated and applied for the quantification of surfactants in 36 river samples. The method's limits of quantification (LQ), intra- and inter-day precision and accuracy were evaluated, and good performances were obtained for the 27 substances. As these compounds have many areas of application, contaminations of instrument and method blanks were observed and considered for the determination of LQ. Nevertheless, with LQ between 15 and 485 ng/L, and accuracy of over 80%, this method was suitable for monitoring surfactants in surface waters. Application on French river samples revealed the presence of anionic, cationic and non-ionic surfactants with median concentrations ranging from 24 ng/L for octylphenol ethoxylates (OPEO) to 4.6 µg/L for linear alkylbenzenesulfonates (LAS). The analytical method developed in this work will therefore be useful for future monitoring of surfactants in waters. Moreover, this method, which shows good performances for anionic, non-ionic and cationic surfactants, may be easily adapted to other surfactants.

Keywords: anionic surfactant, cationic surfactant, LC-MS/MS, non-ionic surfactant, SPE, surface water

Procedia PDF Downloads 113

Authors: Luiza Melo De Lima, Tito Trindade, Jose M. Oliveira

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The development of thermoplastic-based graphene nanocomposites has been of great interest not only to the scientific community but also to different industrial sectors. Due to the possible improvement of performance and weight reduction, thermoplastic nanocomposites are a great promise as a new class of materials. These nanocomposites are of relevance for the automotive industry, namely because the emission limits of CO2 emissions imposed by the European Commission (EC) regulations can be fulfilled without compromising the car’s performance but by reducing its weight. Thermoplastic polymers have some advantages over thermosetting polymers such as higher productivity, lower density, and recyclability. In the automotive industry, for example, poly(propylene) (PP) is a common thermoplastic polymer, which represents more than half of the polymeric raw material used in automotive parts. Graphene-based materials (GBM) are potential nanofillers that can improve the properties of polymer matrices at very low loading. In comparison to other composites, such as fiber-based composites, weight reduction can positively affect their processing and future applications. However, the properties and performance of GBM/polymer nanocomposites depend on the type of GBM and polymer matrix, the degree of dispersion, and especially the type of interactions between the fillers and the polymer matrix. In order to take advantage of the superior mechanical strength of GBM, strong interfacial strength between GBM and the polymer matrix is required for efficient stress transfer from GBM to the polymer. Thus, chemical compatibilizers and physicochemical modifications have been reported as important tools during the processing of these nanocomposites. In this study, PP-based nanocomposites were obtained by a simple melt blending technique, using a Brabender type mixer machine. Graphene nanoplatelets (GnPs) were applied as structural reinforcement. Two compatibilizers were used to improve the interaction between PP matrix and GnPs: PP graft maleic anhydride (PPgMA) and PPgMA modified with tertiary amine alcohol (PPgDM). The samples for tensile and Charpy impact tests were obtained by injection molding. The results suggested the GnPs presence can increase the mechanical strength of the polymer. However, it was verified that the GnPs presence can promote a decrease of impact resistance, turning the nanocomposites more fragile than neat PP. The compatibilizers’ incorporation increases the impact resistance, suggesting that the compatibilizers can enhance the adhesion between PP and GnPs. Compared to neat PP, Young’s modulus of non-compatibilized nanocomposite increase demonstrated that GnPs incorporation can promote a stiffness improvement of the polymer. This trend can be related to the several physical crosslinking points between the PP matrix and the GnPs. Furthermore, the decrease of strain at a yield of PP/GnPs, together with the enhancement of Young’s modulus, confirms that the GnPs incorporation led to an increase in stiffness but to a decrease in toughness. Moreover, the results demonstrated that incorporation of compatibilizers did not affect Young’s modulus and strain at yield results compared to non-compatibilized nanocomposite. The incorporation of these compatibilizers showed an improvement of nanocomposites’ mechanical properties compared both to those the non-compatibilized nanocomposite and to a PP sample used as reference.

Keywords: graphene nanoplatelets, mechanical properties, melt blending processing, poly(propylene)-based nanocomposites

Procedia PDF Downloads 166

Authors: Chih-Jer Lin, Jian-Hong Hou

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Industry 4.0 is a vision of integrated industry implemented by artificial intelligent computing, software, and Internet technologies. The main goal of industry 4.0 is to deal with the difficulty owing to competitive pressures in the marketplace. For today’s manufacturing factories, the type of production is changed from mass production (high quantity production with low product variety) to medium quantity-high variety production. To offer flexibility, better quality control, and improved productivity, robot manipulators are used to combine material processing, material handling, and part positioning systems into an integrated manufacturing system. To implement the automated system for sheet metal bending operations, motion planning of a 7-degrees of freedom (DOF) robot is studied in this paper. A virtual reality (VR) environment of a bending cell, which consists of the robot and a bending machine, is established using the virtual robot experimentation platform (V-REP) simulator. For sheet metal bending operations, the robot only needs six DOFs for the pick-and-place or tracking tasks. Therefore, this 7 DOF robot has more DOFs than the required to execute a specified task; it can be called a redundant robot. Therefore, this robot has kinematic redundancies to deal with the task-priority problems. For redundant robots, Pseudo-inverse of the Jacobian is the most popular motion planning method, but the pseudo-inverse methods usually lead to a kind of chaotic motion with unpredictable arm configurations as the Jacobian matrix lose ranks. To overcome the above problem, we proposed a method to formulate the motion planning problems as optimization problem. Moreover, a genetic algorithm (GA) based method is proposed to deal with motion planning of the redundant robot. Simulation results validate the proposed method feasible for motion planning of the redundant robot in an automated sheet-metal bending operations.

Keywords: redundant robot, motion planning, genetic algorithm, obstacle avoidance

Procedia PDF Downloads 126

Authors: J. Ritonja, R. Brezovnik, M. Petrun, B. Polajžer

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Many modern synchronous generators in power systems are extremely weakly damped. The reasons are cost optimization of the machine building and introduction of the additional control equipment into power systems. Oscillations of the synchronous generators and related stability problems of the power systems are harmful and can lead to failures in operation and to damages. The only useful solution to increase damping of the unwanted oscillations represents the implementation of the power system stabilizers. Power system stabilizers generate the additional control signal which changes synchronous generator field excitation voltage. Modern power system stabilizers are integrated into static excitation systems of the synchronous generators. Available commercial power system stabilizers are based on linear control theory. Due to the nonlinear dynamics of the synchronous generator, current stabilizers do not assure optimal damping of the synchronous generator’s oscillations in the entire operating range. For that reason the use of the robust power system stabilizers which are convenient for the entire operating range is reasonable. There are numerous robust techniques applicable for the power system stabilizers. In this paper the use of sliding mode control for synchronous generator stability improvement is studied. On the basis of the sliding mode theory, the robust power system stabilizer was developed. The main advantages of the sliding mode controller are simple realization of the control algorithm, robustness to parameter variations and elimination of disturbances. The advantage of the proposed sliding mode controller against conventional linear controller was tested for damping of the synchronous generator oscillations in the entire operating range. Obtained results show the improved damping in the entire operating range of the synchronous generator and the increase of the power system stability. The proposed study contributes to the progress in the development of the advanced stabilizer, which will replace conventional linear stabilizers and improve damping of the synchronous generators.

Keywords: control theory, power system stabilizer, robust control, sliding mode control, stability, synchronous generator

Procedia PDF Downloads 205

Authors: Thamer Alshuwaili, Yonglin Ren, Bob Du, Manjree Agarwal

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The warehouse beetle, Trogoderma variabile Ballion (Coleoptera: Dermestidae), is a major pest of packaged and processed stored products. Warehouse beetle is the common name which was given by Okumura (1972). This pest has been reported to infest 119 different commodities, and it is distributed throughout the tropical and subtropical parts of the world. Also, it is difficult to control because of the insect's ability to stay without food for long times, and it can survive for years under dry conditions and low-moisture food, and it has also developed resistance to many insecticides. The young larvae of these insects can cause damage to seeds, but older larvae prefer to feed on whole grains. The percentage of damage caused by these insects range between 30-70% in the storage. T. variabile is the species most responsible for causing significant damage in grain stores worldwide. Trogoderma spp. is a huge problem for cereal grains, and there are many countries, such as the USA, Australia, China, Kenya, Uganda and Tanzania who have specific quarantine regulations against possible importation. Also, grain stocks can be almost completely destroyed because of the massive populations the insect may develop. However, the purpose of the current research was to optimize conditions to collect volatile organic compound from Trogoderma variabile at different life stages by using headspace solid phase microextraction (SPME) coupled with gas chromatography-mass spectrometry (GC-MS) and flame ionization detection (FID). Using SPME technique to extract volatile from insects is an efficient, straightforward and nondestructive method. Result of the study shows that 15 insects were optimal number for larvae and adults. Selection of the number of insects depend on the height of the peak area and the number of peaks. Sixteen hours were optimized as the best extraction time for larvae and 8 hours was the optimal number of adults.

Keywords: Trogoderma variabile, warehouse beetle , GC-MS, Solid phase microextraction

Procedia PDF Downloads 103

Authors: M. Ghosh, A. Miroux, L. A. I. Kestens

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At molecular or micrometre scale, practically all materials are neither homogeneous nor isotropic. The concept of texture is used to identify the structural features that cause the properties of a material to be anisotropic. For metallic materials, the anisotropy of the mechanical behaviour originates from the crystallographic nature of plastic deformation, and is therefore controlled by the crystallographic texture. Anisotropy in mechanical properties often constitutes a disadvantage in the application of materials, as it is often illustrated by the earing phenomena during drawing. However, advantages may also be attained when considering other properties (e.g. optimization of magnetic behaviour to a specific direction) by controlling texture through thermo-mechanical processing). Nevertheless, in order to have better control over the final properties it is essential to relate texture with materials processing route and subsequently optimise their performance. However, up to date, few studies have been reported about the evolution of texture in 6061 aluminium alloy during warm processing (from room temperature to 250ºC). In present investigation, recrystallized 6061 aluminium alloy samples were subjected to tensile and plane strain compression (PSC) at room and warm temperatures. The gradual change of texture following both deformation modes were measured and discussed. Tensile tests demonstrate the mechanism at low strain while PSC does the same at high strain and eventually simulate the condition of rolling. Cube dominated texture of the initial rolled and recrystallized AA6061 sheets were replaced by domination of S and R components after PSC at room temperature, warm temperature (250ºC) though did not reflect any noticeable deviation from room temperature observation. It was also noticed that temperature has no significant effect on the evolution of grain morphology during PSC. The band contrast map revealed that after 30% deformation the substructure inside the grain is mainly made of series of parallel bands. A tendency for decrease of Cube and increase of Goss was noticed after tensile deformation compared to as-received material. Like PSC, texture does not change after deformation at warm temperature though. n-fibre was noticed for all the three textures from Goss to Cube.

Keywords: AA 6061, deformation, temperature, tensile, PSC, texture

Procedia PDF Downloads 470

Authors: Rajasekar Elangopandian, Anand Shanmugam

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Now-a-days for surveillances unmanned aerial vehicle plays a vital role. Not only for surveillances, aerial photography disaster management and the notice of earth behavior UAV1s envisages meticulously. To reduce the maintenance and fuel nuclear powered Vehicles are greater support. The design consideration is much important for the UAV manufacturing industry and Research and development agency. Eventually design is looking like a pentagon shaped fuselage and black rubber coated paint in order to escape from the enemy radar and other targets. The pentagon shape fuselage has large space to keep the mini nuclear reactor inside and the material is carbon – carbon fiber specially designed by the software called cosmol and hyper mesh 14.2. So the weight consideration will produce the positive result for productivity. The walls of the fuselage are coated with lead and protective shield. A double layer of W/Bi sheet is proposed for radiation protection at the energy range of 70 Kev to 90 Kev. The designed W/bi sheet, only 0.14 mm thick and is 36% light. The properties of the fillers were determined from zeta potential and particle size measurements. The Exposes of the radiation can be attenuated by 3 ways such as minimizing exposure time, Maximizing distance from the radiation source and shielding the whole vehicle. The inside reactor will be switched ON when the UAV starts its cruise. The moderators and the control rods can be inserted by automation technique by newly developed software. The heat generated by the reactor will be used to run the turbine which is fixed inside the UAV called mini turbine with natural rubber composite Shaft radiation shield. Cooling system will be in two mode such as liquid and air cooled. Liquid coolant for the heat regeneration is ordinary water, liquid sodium, helium and the walls are made up of regenerative and radiation protective material. The other components like camera and arms bay will be located at the bottom of the UAV high are specially made products in order to escape from the radiation. They are coated with lead Pb and natural rubber composite material. This technique provides the long rang and endurance for eternal flight mission until we need any changeability of parts or product. This UAV has the special advantage of ` land on String` means it`ll land at electric line to charge the automated electronics. Then the fuel is enriched uranium (< 5% U - 235) contains hundreds of fuel pins. This technique provides eternal duty for surveillances and aerial photography. The landing of the vehicle is ease of operation likewise the takeoff is also easier than any other mechanism which present in nowadays. This UAV gives great immense and immaculate technology for surveillance and target detecting and smashing the target.

Keywords: mini turbine, liquid coolant for the heat regeneration, in order to escape from the radiation, eternal flight mission, it`ll land at electric line

Procedia PDF Downloads 394

Authors: Kehinde Agbele, Longe Olumide, Daniel Ekong, Dele Seluwa, Akintoye Onamade

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One major problem of most existing information retrieval systems (IRS) is that they provide even access and retrieval results to individual users specially based on the query terms user issued to the system. When using IRS, users often present search queries made of ad-hoc keywords. It is then up to IRS to obtain a precise representation of user’s information need, and the context of the information. In effect, the volume and range of the Internet documents is growing exponentially and consequently causes difficulties for a user to obtain information that precisely matches the user interest. Diverse combination techniques are used to achieve the specific goal. This is due, firstly, to the fact that users often do not present queries to IRS that optimally represent the information they want, and secondly, the measure of a document's relevance is highly subjective between diverse users. In this paper, we address the problem by investigating the optimization of IRS to individual information needs in order of relevance. The paper addressed the development of algorithms that optimize the ranking of documents retrieved from IRS. This paper addresses this problem with a two-fold approach in order to retrieve domain-specific documents. Firstly, the design of context of information. The context of a query determines retrieved information relevance using personalization and context-awareness. Thus, executing the same query in diverse contexts often leads to diverse result rankings based on the user preferences. Secondly, the relevant context aspects should be incorporated in a way that supports the knowledge domain representing users’ interests. In this paper, the use of evolutionary algorithms is incorporated to improve the effectiveness of IRS. A context-based information retrieval system that learns individual needs from user-provided relevance feedback is developed whose retrieval effectiveness is evaluated using precision and recall metrics. The results demonstrate how to use attributes from user interaction behavior to improve the IR effectiveness.

Keywords: context, document relevance, information retrieval, personalization, user search behaviors

Procedia PDF Downloads 439

Authors: Chenhao Zhu

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Quantitative mapping is playing a growing role in guiding urban planning, such as using a heat map created by CFX, CFD2000, or Envi-met, to adjust the master plan. However, there is no effective quantitative link between the mappings and planning formation. So, in many cases, the decision-making is still based on the planner's subjective interpretation and understanding of these mappings, which limits the improvement of scientific and accuracy brought by the quantitative mapping. Therefore, in this paper, an effort has been made to give a methodology of building a parametric link between the mapping and planning formation. A parametric planning process based on radiant mapping has been proposed for creating an urban green system. In the first step, a script is written in Grasshopper to build a road network and form the block, while the Ladybug Plug-in is used to conduct a radiant analysis in the form of mapping. Then, the research creatively transforms the radiant mapping from a polygon into a data point matrix, because polygon is hard to engage in the design formation. Next, another script is created to select the main green spaces from the road network based on the criteria of radiant intensity and connect the green spaces' central points to generate a green corridor. After that, a control parameter is introduced to adjust the corridor's form based on the radiant intensity. Finally, a green system containing greenspace and green corridor is generated under the quantitative control of the data matrix. The designer only needs to modify the control parameter according to the relevant research results and actual conditions to realize the optimization of the green system. This method can also be applied to much other mapping-based analysis, such as wind environment analysis, thermal environment analysis, and even environmental sensitivity analysis. The parameterized link between the mapping and planning will bring about a more accurate, objective, and scientific planning.

Keywords: parametric link, mapping, urban green system, radiant intensity, planning strategy, grasshopper

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Authors: Ranjot Kaur, Om P. Katare, Anupama Sharma, Sarah R. Dennison, Kamalinder K. Singh, Bhupinder Singh

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Respiratory microbial infections being among the top leading cause of death worldwide are difficult to treat as the microbes reside deep inside the airways, where only a small fraction of drug can access after traditional oral or parenteral routes. As a result, high doses of drugs are required to maintain drug levels above minimum inhibitory concentrations (MIC) at the infection site, unfortunately leading to severe systemic side-effects. Therefore, delivering antimicrobials directly to the respiratory tract provides an attractive way out in such situations. In this context, current study embarks on the systematic development of lung lia pid-modified chitosan nanoparticles for inhalation of voriconazole. Following the principles of quality by design, the chitosan nanoparticles were prepared by ionic gelation method and further coated with major lung lipid by precipitation method. The factor screening studies were performed by fractional factorial design, followed by optimization of the nanoparticles by Box-Behnken Design. The optimized formulation has a particle size range of 170-180nm, PDI 0.3-0.4, zeta potential 14-17, entrapment efficiency 45-50% and drug loading of 3-5%. The presence of a lipid coating was confirmed by FESEM, FTIR, and X-RD. Furthermore, the nanoparticles were found to be safe upto 40µg/ml on A549 and Calu-3 cell lines. The quantitative and qualitative uptake studies also revealed the uptake of nanoparticles in lung epithelial cells. Moreover, the data from Spraytec and next-generation impactor studies confirmed the deposition of nanoparticles in lower airways. Also, the interaction of nanoparticles with DPPC monolayers signifies its biocompatibility with lungs. Overall, the study describes the methodology and potential of lipid-coated chitosan nanoparticles in futuristic inhalation nanomedicine for the management of pulmonary aspergillosis.

Keywords: dipalmitoylphosphatidylcholine, nebulization, DPPC monolayers, quality-by-design

Procedia PDF Downloads 118

Authors: W. Jahouach-Rabai, J. Aribi, Z. Azzouz-Berriche, R. Lahsni, F. Hosni

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Gamma irradiation applied in removing pharmaceutical contaminants from wastewater is an effective advanced oxidation process (AOP), considered as an alternative to conventional water treatment technologies. In this purpose, the degradation efficiency of several detected contaminants under gamma irradiation was evaluated. In fact, radiolysis of organic pollutants in aqueous solutions produces powerful reactive species, essentially hydroxyl radical ( ·OH), able to destroy recalcitrant pollutants in water. Pharmaceuticals considered in this study are aqueous solutions of paracetamol, ibuprofen, and diclofenac at different concentrations 0.1-1 mmol/L, which were treated with irradiation doses from 3 to 15 kGy. The catalytic oxidation of these compounds by gamma irradiation was investigated using hydrogen peroxide (H₂O₂) as a convenient oxidant. Optimization of the main parameters influencing irradiation process, namely irradiation doses, initial concentration and oxidant volume (H₂O₂) were investigated, in the aim to release high degradation efficiency of considered pharmaceuticals. Significant modifications attributed to these parameters appeared in the variation of degradation efficiency, chemical oxygen demand removal (COD) and concentration of radio-induced radicals, confirming them synergistic effect to attempt total mineralization. Pseudo-first-order reaction kinetics could be used to depict the degradation process of these compounds. A sophisticated analytical study was released to quantify the detected radio-induced radicals (electron paramagnetic resonance spectroscopy (EPR) and high performance liquid chromatography (HPLC)). All results showed that this process is effective for the degradation of many pharmaceutical products in aqueous solutions due to strong oxidative properties of generated radicals mainly hydroxyl radical. Furthermore, the addition of an optimal amount of H₂O₂ was efficient to improve the oxidative degradation and contribute to the high performance of this process at very low doses (0.5 and 1 kGy).

Keywords: AOP, COD, hydroxyl radical, EPR, gamma irradiation, HPLC, pharmaceuticals

Procedia PDF Downloads 151

Authors: S. Gokul Prassad, S. Aakash, K. Malar Mohan

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In the process to cope with the challenges faced by the automobile industry in providing ride comfort, the electronics and control systems play a vital role. The control systems in an automobile monitor various parameters, controls the performances of the systems, thereby providing better handling characteristics. The automobile suspension system is one of the main systems that ensure the safety, stability and comfort of the passengers. The system is solely responsible for the isolation of the entire automobile from harmful road vibrations. Thus, integration of the control systems in the automobile suspension system would enhance its performance. The diverse road conditions of India demand the need of an efficient suspension system which can provide optimum ride comfort in all road conditions. For any passenger vehicle, the design of the suspension system plays a very important role in assuring the ride comfort and handling characteristics. In recent years, the air suspension system is preferred over the conventional suspension systems to ensure ride comfort. In this article, the ride comfort of the adaptive suspension system is compared with that of the passive suspension system. The schema is created in MATLAB/Simulink environment. The system is controlled by a proportional integral differential controller. Tuning of the controller was done with the Particle Swarm Optimization (PSO) algorithm, since it suited the problem best. Ziegler-Nichols and Modified Ziegler-Nichols tuning methods were also tried and compared. Both the static responses and dynamic responses of the systems were calculated. Various random road profiles as per ISO 8608 standard are modelled in the MATLAB environment and their responses plotted. Open-loop and closed loop responses of the random roads, various bumps and pot holes are also plotted. The simulation results of the proposed design are compared with the available passive suspension system. The obtained results show that the proposed adaptive suspension system is efficient in controlling the maximum over shoot and the settling time of the system is reduced enormously.

Keywords: automobile suspension, MATLAB, control system, PID, PSO

Procedia PDF Downloads 274

Authors: Temitope D. Awobusuyi, Eric O. Amonsou, Muthulisi Siwela, Oluwatosin A. Ijabadeniyi

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Provitamin A-biofortified maize has been developed to alleviate Vitamin A deficiency; a major public health problem in developing countries. Amahewu, a non-alcoholic fermented maize based beverage is produced using white maize, which is deficient in Vitamin A. In this study, the suitable processing conditions for the production of amahewu using provitamin A-biofortified maize and the microbial quality of the processed products were evaluated. Provitamin A-biofortified amahewu was produced with reference to traditional processing method. Processing variables were Inoculum types (Malted provitamin A maize, Wheat bran, and lactobacillus mixed starter culture with either malted provitamin A or wheat bran) and concentration (0.5 %, 1 % and 2 %). A total of four provitamin A-biofortified amahewu products after fermentation were subjected to different storage conditions: 4ᴼC, 25ᴼC and 37ᴼC. pH and TTA were monitored throughout the storage period. Sample of provitamin A-biofortified amahewu were plated and observed every day for 5 days to assess the presence of Aerobic and Anaerobic spore formers, E.coli, Lactobacillus and Mould. The addition of starter culture substantially reduced the fermentation time (6 hour, pH 3.3) compared to those with no addition of starter culture (24 hour pH 3.5). It was observed that Lactobacillus were present from day 0 for all the storage temperatures. The presence of aerobic spore former and mould were observed on day 3. E.coli and Anaerobic spore formers were not present throughout the storage period. These microbial growth were minimal at 4ᴼC while 25ᴼC had higher counts of growth with 37ᴼC having the highest colony count. Throughout the storage period, pH of provitamin A-biofortified amahewu was stable. Provitamin A-biofortified amahewu stored under refrigerated condition (4ᴼC) had better storability compared to 25ᴼC and 37ᴼC. The production and microbial quality of provitamin A-biofortified amahewu might be important in combating Vitamin A Deficiency.

Keywords: biofortification, fermentation, maize, vitamin A deficiency

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Authors: Sthanu Mahadev, Wen Chan, Melanie Lim

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Anisotropy dominated continuous-fiber composite materials have garnered attention in numerous mechanical and aerospace structural applications. Tailored mechanical properties in advanced composites can exhibit superiority in terms of stiffness-to-weight ratio, strength-to-weight ratio, low-density characteristics, coupled with significant improvements in fatigue resistance as opposed to metal structure counterparts. Extensive research has demonstrated their core potential as more than just mere lightweight substitutes to conventional materials. Prior work done by Mahadev and Chan focused on formulating a modified composite shell theory based prognosis methodology for investigating the structural response of thin-walled circular cylindrical shell type composite configurations under in-plane mechanical loads respectively. The prime motivation to develop this theory stemmed from its capability to generate simple yet accurate closed-form analytical results that can efficiently characterize circular composite shell construction. It showcased the development of a novel mathematical framework to analytically identify the location of the centroid for thin-walled, open cross-section, curved composite shells that were characterized by circumferential arc angle, thickness-to-mean radius ratio, and total laminate thickness. Ply stress variations for curved cylindrical shells were analytically examined under the application of centric tensile and bending loading. This work presents a cost-effective, small-platform experimental methodology by taking advantage of the full-field measurement capability of digital image correlation (DIC) for an accurate assessment of key mechanical parameters such as in-plane mechanical stresses and strains, centroid location etc. Mechanical property measurement of advanced composite materials can become challenging due to their anisotropy and complex failure mechanisms. Full-field displacement measurements are well suited for characterizing the mechanical properties of composite materials because of the complexity of their deformation. This work encompasses the fabrication of a set of curved cylindrical shell coupons, the design and development of a novel test-fixture design and an innovative experimental methodology that demonstrates the capability to very accurately predict the location of centroid in such curved composite cylindrical strips via employing a DIC based strain measurement technique. Error percentage difference between experimental centroid measurements and previously estimated analytical centroid results are observed to be in good agreement. The developed analytical modified-shell theory provides the capability to understand the fundamental behavior of thin-walled cylindrical shells and offers the potential to generate novel avenues to understand the physics of such structures at a laminate level.

Keywords: anisotropy, composites, curved cylindrical shells, digital image correlation

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Authors: Tuba Zahra, Aakash Parekh

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Hyperspectral remote sensing refers to imaging of objects or materials in narrow conspicuous spectral bands. Hyperspectral images (HSI) enable the extraction of spectral signatures for objects or materials observed. These images contain information about the reflectance of each pixel across the electromagnetic spectrum. It enables the acquisition of data simultaneously in hundreds of spectral bands with narrow bandwidths and can provide detailed contiguous spectral curves that traditional multispectral sensors cannot offer. The contiguous, narrow bandwidth of hyperspectral data facilitates the detailed surveying of Earth's surface features. This would otherwise not be possible with the relatively coarse bandwidths acquired by other types of imaging sensors. Hyperspectral imaging provides significantly higher spectral and spatial resolution. There are several use cases that represent the commercial applications of hyperspectral remote sensing. Each use case represents just one of the ways that hyperspectral satellite imagery can support operational efficiency in the respective vertical. There are some use cases that are specific to VNIR bands, while others are specific to SWIR bands. This paper discusses the different commercially viable use cases that are significant for HSI application areas, such as agriculture, mining, oil and gas, defense, environment, and climate, to name a few. Theoretically, there is n number of use cases for each of the application areas, but an attempt has been made to streamline the use cases depending upon economic feasibility and commercial viability and present a review of literature from this perspective. Some of the specific use cases with respect to agriculture are crop species (sub variety) detection, soil health mapping, pre-symptomatic crop disease detection, invasive species detection, crop condition optimization, yield estimation, and supply chain monitoring at scale. Similarly, each of the industry verticals has a specific commercially viable use case that is discussed in the paper in detail.

Keywords: agriculture, mining, oil and gas, defense, environment and climate, hyperspectral, VNIR, SWIR

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Authors: Zahid Ullah, Atlas Khan

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The rapid advancements in data collection, storage, and processing capabilities have led to an explosion of data in various domains. In this era of big data, mathematical sciences play a crucial role in uncovering valuable insights and driving informed decision-making through data analytics. The purpose of this abstract is to present the latest advances in mathematical sciences and their application in harnessing the power of data analytics. This abstract highlights the interdisciplinary nature of data analytics, showcasing how mathematics intersects with statistics, computer science, and other related fields to develop cutting-edge methodologies. It explores key mathematical techniques such as optimization, mathematical modeling, network analysis, and computational algorithms that underpin effective data analysis and interpretation. The abstract emphasizes the role of mathematical sciences in addressing real-world challenges across different sectors, including finance, healthcare, engineering, social sciences, and beyond. It showcases how mathematical models and statistical methods extract meaningful insights from complex datasets, facilitating evidence-based decision-making and driving innovation. Furthermore, the abstract emphasizes the importance of collaboration and knowledge exchange among researchers, practitioners, and industry professionals. It recognizes the value of interdisciplinary collaborations and the need to bridge the gap between academia and industry to ensure the practical application of mathematical advancements in data analytics. The abstract highlights the significance of ongoing research in mathematical sciences and its impact on data analytics. It emphasizes the need for continued exploration and innovation in mathematical methodologies to tackle emerging challenges in the era of big data and digital transformation. In summary, this abstract sheds light on the advances in mathematical sciences and their pivotal role in unveiling the power of data analytics. It calls for interdisciplinary collaboration, knowledge exchange, and ongoing research to further unlock the potential of mathematical methodologies in addressing complex problems and driving data-driven decision-making in various domains.

Keywords: mathematical sciences, data analytics, advances, unveiling

Procedia PDF Downloads 64

Authors: Bernadett Henn, Katalin Tálos, Éva Kováss Széles

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During the last 50 years, the worldwide permeation of the nuclear techniques induces several new problems in the environmental and in the human life. Nowadays, due to the increasing of the risk of terrorism worldwide, the potential occurrence of terrorist attacks using also weapon of mass destruction containing radioactive or nuclear materials as e.g. dirty bombs, is a real threat. For instance, the uranium pellets are one of the potential nuclear materials which are suitable for making special weapons. The nuclear forensics mainly focuses on the determination of the origin of the confiscated or found nuclear and other radioactive materials, which could be used for making any radioactive dispersive device. One of the most important signatures in nuclear forensics to find the origin of the material is the determination of the rare earth element patterns (REE) in the seized or found radioactive or nuclear samples. The concentration and the normalized pattern of the REE can be used as an evidence of uranium origin. The REE are the fourteen Lanthanides in addition scandium and yttrium what are mostly found together and really low concentration in uranium pellets. The problems of the REE determination using ICP-MS technique are the uranium matrix (high concentration of uranium) and the interferences among Lanthanides. In this work, our aim was to develop an effective chemical sample preparation process using extraction chromatography for separation the uranium matrix and the rare earth elements from each other following some publications can be found in the literature and modified them. Secondly, our purpose was the optimization of the ICP-MS measuring process for REE concentration. During method development, in the first step, a REE model solution was used in two different types of extraction chromatographic resins (LN® and TRU®) and different acidic media for environmental testing the Lanthanides separation. Uranium matrix was added to the model solution and was proved in the same conditions. Methods were tested and validated using REE UOC (uranium ore concentrate) reference materials. Samples were analyzed by sector field mass spectrometer (ICP-SFMS).

Keywords: extraction chromatography, nuclear forensics, rare earth elements, uranium

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Authors: C. Fortin, D. Tokmeninova, O. Ushakova

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Among 500 Russian universities Skolkovo Institute of Science and Technology (Skoltech) is one of the youngest (established in 2011), quite small and vastly international, comprising 20 percent of international students and 70 percent of faculty with significant academic experience at top-100 universities (QS, THE). The institute has emerged from close collaboration with MIT and leading Russian universities. Skoltech is an entirely English speaking environment. Skoltech curriculum plans of ten Master programs are based on the CDIO learning outcomes model. However, despite the Institute’s unique focus on industrial innovations and startups, one of the main challenges has become an evident large proportion of nearly half of MSc graduates entering PhD programs at Skoltech or other universities rather than industry or entrepreneurship. In order to increase the share of students joining the industrial sector after graduation, Skoltech started implementing a number of unique practices with a focus on employers’ expectations incorporated into the curriculum redesign. In this sense, extended knowledge exchange with industrial partners via collaboration in learning activities, industrial projects and assessments became essential for students’ headway into industrial and entrepreneurship pathways. Current academic curriculum includes the following types of components based on extended knowledge exchange with industrial partners: innovation workshop, industrial immersion, special industrial tracks, MSc defenses. Innovation workshop is a 4 week full time diving into the Skoltech vibrant ecosystem designed to foster innovators, focuses on teamwork, group projects, and sparks entrepreneurial instincts from the very first days of study. From 2019 the number of mentors from industry and startups significantly increased to guide students across these sectors’ demands. Industrial immersion is an exclusive part of Skoltech curriculum where students after the first year of study spend 8 weeks in an industrial company carrying out an individual or team project and are guided jointly by both Skoltech and company supervisors. The aim of the industrial immersion is to familiarize students with relevant needs of Russian industry and to prepare graduates for job placement. During the immersion a company plays the role of a challenge provider for students. Skoltech has started a special industrial track comprising deep collaboration with IPG Photonics – a leading R&D company and manufacturer of high-performance fiber lasers and amplifiers for diverse applications. The track is aimed to train a new cohort of engineers and includes a variety of activities for students within the “Photonics” MSc program. It is expected to be a successful story and used as an example for similar initiatives with other Russian high-tech companies. One of the pathways of extended knowledge exchange with industrial partners is an active involvement of potential employers in MSc Defense Committees to review and assess MSc thesis projects and to participate in defense procedures. The paper will evaluate the effect and results of the above undertaken measures.

Keywords: Curriculum redesign, knowledge exchange model, learning outcomes framework, stakeholder engagement

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Authors: Nadeen Felemban, Hamsa Banjer, Rabaah Jaafari

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One of the most common hazards in the pharmaceutical industry is the chemical hazard, which can cause harm or develop occupational health diseases/illnesses due to chronic exposures to hazardous substances. Therefore, a chemical agent management system is required, including hazard identification, risk assessment, controls for specific hazards and inspections, to keep your workplace healthy and safe. However, routine management monitoring is also required to verify the effectiveness of the control measures. Moreover, Betamethasone Valerate and Clobetasol Propionate are some of the APIs (Active Pharmaceutical Ingredients) with highly hazardous classification-Occupational Hazard Category (OHC 4), which requires a full containment (ECA-D) during handling to avoid chemical exposure. According to Safety Data Sheet, those chemicals are reproductive toxicants (reprotoxicant H360D), which may affect female workers’ health and cause fatal damage to an unborn child, or impair fertility. In this study, qualitative (chemical Risk assessment-qCRA) was conducted to assess the chemical exposure during handling of Betamethasone Valerate and Clobetasol Propionate in pharmaceutical laboratories. The outcomes of qCRA identified that there is a risk of potential chemical exposure (risk rating 8 Amber risk). Therefore, immediate actions were taken to ensure interim controls (according to the Hierarchy of controls) are in place and in use to minimize the risk of chemical exposure. No open handlings should be done out of the Steroid Glove Box Isolator (SGB) with the required Personal Protective Equipment (PPEs). The PPEs include coverall, nitrile hand gloves, safety shoes and powered air-purifying respirators (PAPR). Furthermore, a quantitative assessment (personal air sampling) was conducted to verify the effectiveness of the engineering controls (SGB Isolator) and to confirm if there is chemical exposure, as indicated earlier by qCRA. Three personal air samples were collected using an air sampling pump and filter (IOM2 filters, 25mm glass fiber media). The collected samples were analyzed by HPLC in the BV lab, and the measured concentrations were reported in (ug/m3) with reference to Occupation Exposure Limits, 8hr OELs (8hr TWA) for each analytic. The analytical results are needed in 8hr TWA (8hr Time-weighted Average) to be analyzed using Bayesian statistics (IHDataAnalyst). The results of the Bayesian Likelihood Graph indicate (category 0), which means Exposures are de "minimus," trivial, or non-existent Employees have little to no exposure. Also, these results indicate that the 3 samplings are representative samplings with very low variations (SD=0.0014). In conclusion, the engineering controls were effective in protecting the operators from such exposure. However, routine chemical monitoring is required every 3 years unless there is a change in the processor type of chemicals. Also, frequent management monitoring (daily, weekly, and monthly) is required to ensure the control measures are in place and in use. Furthermore, a Similar Exposure Group (SEG) was identified in this activity and included in the annual health surveillance for health monitoring.

Keywords: occupational health and safety, risk assessment, chemical exposure, hierarchy of control, reproductive

Procedia PDF Downloads 155

Authors: Adel Salem Bahakeem, Ahmad Jamal, Mir Md. Maruf Morshed, Elwaleed Awad Khidir

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Direct Current (DC) servo motors, or simply DC motors, play an important role in many industrial applications such as manufacturing of plastics, precise positioning of the equipment, and operating computer-controlled systems where speed of feed control, maintaining the position, and ensuring to have a constantly desired output is very critical. These parameters can be controlled with the help of control systems such as the Proportional Integral Derivative (PID) controller. The aim of the current work is to investigate the effects of Proportional (P) and Integral (I) controllers on the steady state and transient response of the DC motor. The controller gains are varied to observe their effects on the error, damping, and stability of the steady and transient motor response. The current investigation is conducted experimentally on a servo trainer CE 110 using analog PI controller CE 120 and theoretically using Simulink in MATLAB. Both experimental and theoretical work involves varying integral controller gain to obtain the response to a steady-state input, varying, individually, the proportional and integral controller gains to obtain the response to a step input function at a certain frequency, and theoretically obtaining the proportional and integral controller gains for desired values of damping ratio and response frequency. Results reveal that a proportional controller helps reduce the steady-state and transient error between the input signal and output response and makes the system more stable. In addition, it also speeds up the response of the system. On the other hand, the integral controller eliminates the error but tends to make the system unstable with induced oscillations and slow response to eliminate the error. From the current work, it is desired to achieve a stable response of the servo motor in terms of its angular velocity subjected to steady-state and transient input signals by utilizing the strengths of both P and I controllers.

Keywords: DC servo motor, proportional controller, integral controller, controller gain optimization, Simulink

Procedia PDF Downloads 86

Authors: Asma Abdullah, Awais Khan, Reem Al-Ghumlasi, Pritam Kumari, Yasir Nawaz

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Introduction: This study verified the potential applications of two Oblique Wing configurations that were initiated by the Germans Aerodynamicists during the WWII. Due to the end of the war, this project was not completed and in this research is targeting the revival of German Oblique biplane configuration. The research draws upon the use of two Oblique wings mounted on the top and bottom of the fuselage through a single pivot. The wings are capable of sweeping at different angles ranging from 0° at takeoff to 60° at cruising Altitude. The top wing, right half, behaves like a forward swept wing and the left half, behaves like a backward swept wing. Vice Versa applies to the lower wing. This opposite deflection of the top and lower wing cancel out the rotary moment created by each wing and the aircraft remains stable. Problem to better understand or solve: The purpose of this research is to investigate the potential of achieving improved aerodynamic performance and efficiency of flight at a wide range of sweep angles. This will help examine the most accurate value for the sweep angle at which the aircraft will possess both stability and better aerodynamics. Explaining the methods used: The Aircraft configuration is designed using Solidworks after which a series of Aerodynamic prediction are conducted, both in the subsonic and the supersonic flow regime. Computations are carried on Ansys Fluent. The results are then compared to theoretical and flight data of different Supersonic fighter aircraft of the same category (AD-1) and with the Wind tunnel testing model at subsonic speed. Results: At zero sweep angle, the aircraft has an excellent lift coefficient value with almost double that found for fighter jets. In acquiring of supersonic speed the sweep angle is increased to maximum 60 degrees depending on the mission profile. General findings: Oblique biplane can be the future fighter jet aircraft because of its high value performance in terms of aerodynamics, cost, structural design and weight.

Keywords: biplane, oblique wing, sweep angle, supercritical airfoil

Procedia PDF Downloads 254

Authors: Xiaowei Zhang, Min Xu, Saeid Habibi, Fengjun Yan, Ryan Ahmed

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Recently, Electric Vehicles (EVs) have received extensive consideration since they offer a more sustainable and greener transportation alternative compared to fossil-fuel propelled vehicles. Lithium-Ion (Li-ion) batteries are increasingly being deployed in EVs because of their high energy density, high cell-level voltage, and low rate of self-discharge. Since Li-ion batteries represent the most expensive component in the EV powertrain, accurate monitoring and control strategies must be executed to ensure their prolonged lifespan. The Battery Management System (BMS) has to accurately estimate parameters such as the battery State-of-Charge (SOC), State-of-Health (SOH), and Remaining Useful Life (RUL). In order for the BMS to estimate these parameters, an accurate and control-oriented battery model has to work collaboratively with a robust state and parameter estimation strategy. Since battery physical parameters, such as the internal resistance and diffusion coefficient change depending on the battery state-of-life (SOL), the BMS has to be adaptive to accommodate for this change. In this paper, an extensive battery aging study has been conducted over 12-months period on 5.4 Ah, 3.7 V Lithium polymer cells. Instead of using fixed charging/discharging aging cycles at fixed C-rate, a set of real-world driving scenarios have been used to age the cells. The test has been interrupted every 5% capacity degradation by a set of reference performance tests to assess the battery degradation and track model parameters. As battery ages, the combined model parameters are optimized and tracked in an offline mode over the entire batteries lifespan. Based on the optimized model, a state and parameter estimation strategy based on the Extended Kalman Filter (EKF) and the relatively new Smooth Variable Structure Filter (SVSF) have been applied to estimate the SOC at various states of life.

Keywords: lithium-ion batteries, genetic algorithm optimization, battery aging test, parameter identification

Procedia PDF Downloads 246

Authors: Wang Yichen, Haruka Yamashita

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In recent years, in the field of sports, decision making such as member in the game and strategy of the game based on then analysis of the accumulated sports data are widely attempted. In fact, in the NBA basketball league where the world's highest level players gather, to win the games, teams analyze the data using various statistical techniques. However, it is difficult to analyze the game data for each play such as the ball tracking or motion of the players in the game, because the situation of the game changes rapidly, and the structure of the data should be complicated. Therefore, it is considered that the analysis method for real time game play data is proposed. In this research, we propose an analytical model for "determining the optimal lineup composition" using the real time play data, which is considered to be difficult for all coaches. In this study, because replacing the entire lineup is too complicated, and the actual question for the replacement of players is "whether or not the lineup should be changed", and “whether or not Small Ball lineup is adopted”. Therefore, we propose an analytical model for the optimal player selection problem based on Small Ball lineups. In basketball, we can accumulate scoring data for each play, which indicates a player's contribution to the game, and the scoring data can be considered as a time series data. In order to compare the importance of players in different situations and lineups, we combine RNN (Recurrent Neural Network) model, which can analyze time series data, and NN (Neural Network) model, which can analyze the situation on the field, to build the prediction model of score. This model is capable to identify the current optimal lineup for different situations. In this research, we collected all the data of accumulated data of NBA from 2019-2020. Then we apply the method to the actual basketball play data to verify the reliability of the proposed model.

Keywords: recurrent neural network, players lineup, basketball data, decision making model

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Authors: Said Benaissa, David Plets, Emmeric Tanghe, Jens Trogh, Luc Martens, Leen Vandaele, Annelies Van Nuffel, Frank A. M. Tuyttens, Bart Sonck, Wout Joseph

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The herd monitoring and managing - in particular the detection of ‘attention animals’ that require care, treatment or assistance is crucial for effective reproduction status, health, and overall well-being of dairy cows. In large sized farms, traditional methods based on direct observation or analysis of video recordings become labour-intensive and time-consuming. Thus, automatic monitoring systems using sensors have become increasingly important to continuously and accurately track the health status of dairy cows. Wireless sensor networks (WSNs) and internet-of-things (IoT) can be effectively used in health tracking of dairy cows to facilitate herd management and enhance the cow welfare. Since on-cow measuring devices are energy-constrained, a proper characterization of the off-body wireless channel between the on-cow sensor nodes and the back-end base station is required for a power-optimized deployment of these networks in barns. The aim of this study was to characterize the off-body wireless channel in indoor (barns) environment at 868 MHz using LoRa nodes. LoRa is an emerging wireless technology mainly targeted at WSNs and IoT networks. Both large scale fading (i.e., path loss) and temporal fading were investigated. The obtained path loss values as a function of the transmitter-receiver separation were well fitted by a lognormal path loss model. The path loss showed an additional increase of 4 dB when the wireless node was actually worn by the cow. The temporal fading due to movement of other cows was well described by Rician distributions with a K-factor of 8.5 dB. Based on this characterization, network planning and energy consumption optimization of the on-body wireless nodes could be performed, which enables the deployment of reliable dairy cow monitoring systems.

Keywords: channel, channel modelling, cow monitoring, dairy cows, health monitoring, IoT, LoRa, off-body propagation, PLF, propagation

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Authors: Soledad Carinelli, Iñigo Fernández, José Luis González-Mora, Pedro A. Salazar-Carballo

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Mastitis is the most relevant inflammatory disease in cattle, affecting the animal health and causing important economic losses on dairy farms. This disease takes place in the mammary gland or udder when some opportunistic microorganisms, such as Staphylococcus aureus, Streptococcus agalactiae, Corynebacterium bovis, etc., invade the teat canal. According to the severity of the inflammation, mastitis can be classified as sub-clinical, clinical and chronic. Standard methods for mastitis detection include counts of somatic cells, cell culture, electrical conductivity of the milk, and California test (evaluation of “gel-like” matrix consistency after cell lysed with detergents). However, these assays present some limitations for accurate detection of subclinical mastitis. Currently, haptoglobin, an acute phase protein, has been proposed as novel and effective biomarker for mastitis detection. In this work, an electrochemical biosensor based on polydopamine-modified magnetic nanoparticles (MNPs@pDA) for haptoglobin detection is reported. Thus, MNPs@pDA has been synthesized by our group and functionalized with hemoglobin due to its high affinity to haptoglobin protein. The protein was labeled with specific antibodies modified with alkaline phosphatase enzyme for its electrochemical detection using an electroactive substrate (1-naphthyl phosphate) by differential pulse voltammetry. After the optimization of assay parameters, the haptoglobin determination was evaluated in milk. The strategy presented in this work shows a wide range of detection, achieving a limit of detection of 43 ng/mL. The accuracy of the strategy was determined by recovery assays, being of 84 and 94.5% for two Hp levels around the cut off value. Milk real samples were tested and the prediction capacity of the electrochemical biosensor was compared with a Haptoglobin commercial ELISA kit. The performance of the assay has demonstrated this strategy is an excellent and real alternative as screen method for sub-clinical bovine mastitis detection.

Keywords: bovine mastitis, haptoglobin, electrochemistry, magnetic nanoparticles, polydopamine

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Authors: Sujing Wang, Song Wang, Jian Zhang, Qiang Xu

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Flaring emissions during abnormal operating conditions such as plant start-ups, shut-downs, and upsets in chemical process industries (CPI) are usually significant. Flare minimization can help to save raw material and energy for CPI plants, and to improve local environmental sustainability. In this paper, a systematic methodology based on plant-wide dynamic simulation is presented for CPI plant flare minimizations under abnormal operating conditions. Since off-specification emission sources are inevitable during abnormal operating conditions, to significantly reduce flaring emission in a CPI plant, they must be either recycled to the upstream process for online reuse, or stored somewhere temporarily for future reprocessing, when the CPI plant manufacturing returns to stable operation. Thus, the off-spec products could be reused instead of being flared. This can be achieved through the identification of viable design and operational strategies during normal and abnormal operations through plant-wide dynamic scheduling, simulation, and optimization. The proposed study includes three stages of simulation works: (i) developing and validating a steady-state model of a CPI plant; (ii) transiting the obtained steady-state plant model to the dynamic modeling environment; and refining and validating the plant dynamic model; and (iii) developing flare minimization strategies for abnormal operating conditions of a CPI plant via a validated plant-wide dynamic model. This cost-effective methodology has two main merits: (i) employing large-scale dynamic modeling and simulations for industrial flare minimization, which involves various unit models for modeling hundreds of CPI plant facilities; (ii) dealing with critical abnormal operating conditions of CPI plants such as plant start-up and shut-down. Two virtual case studies on flare minimizations for start-up operation (over 50% of emission savings) and shut-down operation (over 70% of emission savings) of an ethylene plant have been employed to demonstrate the efficacy of the proposed study.

Keywords: flare minimization, large-scale modeling and simulation, plant shut-down, plant start-up

Procedia PDF Downloads 298