Search results for: robust optimization

Authors: Omar Pillaca-Pullo, Arturo Alejandro-Paredes, Carol Flores-Fernandez, Marijuly Sayuri Kina, Amparo Iris Zavaleta

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Aqueous two-phase system (ATPS) is an interesting alternative for separating industrial enzymes due to it is easy to scale-up and low cost. Polyethylene glycol (PEG) mixed with potassium phosphate or magnesium sulfate is one of the most frequently polymer/salt ATPS used, but the consequences of its use is a high concentration of phosphates and sulfates in wastewater causing environmental issues. Citrate could replace these inorganic salts due to it is biodegradable and does not produce toxic compounds. On the other hand, statistical design of experiments is widely used for ATPS optimization and it allows to study the effects of the involved variables in the purification, and to estimate their significant effects on selected responses and interactions. The 24 factorial design with four central points (20 experiments) was employed to study the partition and purification of proteases produced by Pseudomonas sp. in PEG/citrate ATPS system. ATPS was prepared with different sodium citrate concentrations [14, 16 and 18% (w/w)], pH values (7, 8 and 9), PEG molecular weight (2,000; 4,000 and 6,000 g/mol) and PEG concentrations [18, 20 and 22 % (w/w)]. All system components were mixed with 15% (w/w) of the fermented broth and deionized water was added to a final weight of 12.5 g. Then, the systems were mixed and kept at room temperature until to reach two-phases separation. Volumes of the top and bottom phases were measured, and aliquots from both phases were collected for subsequent proteolytic activity and total protein determination. Influence of variables such as PEG molar mass (MPEG), PEG concentration (CPEG), citrate concentration (CSal) and pH were evaluated on the following responses: purification factor (PF), activity yield (Y), partition coefficient (K) and selectivity (S). STATISTICA program version 10 was used for the analysis. According to the obtained results, higher levels of CPEG and MPEG had a positive effect on extraction, while pH did not influence on the process. On the other hand, the CSal could be related with low values of Y because of the citrate ions have a negative effect on solubility and enzymatic structure. The optimum values of Y (66.4 %), PF (1.8), K (5.5) and S (4.3) were obtained at CSal (18%), MPEG (6,000 g/mol), CPEG (22%) and pH 9. These results indicated that the PEG/citrate system is accurate to purify these Pseudomonas sp. proteases from fermented broth as a first purification step.

Keywords: citrate, polyethylene glycol, protease, Pseudomonas sp

Procedia PDF Downloads 171

Authors: William Kelly, Sorelle Veigne, Xianhua Li, Zuyi Huang, Shyamsundar Subramanian, Eugene Schaefer

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The ambr15™ bioreactor is a single-use microbioreactor for cell line development and process optimization. The ambr system offers fully automatic liquid handling with the possibility of fed-batch operation and automatic control of pH and oxygen delivery. With operating conditions for large scale biopharmaceutical production properly scaled down, micro bioreactors such as the ambr15™ can potentially be used to predict the effect of process changes such as modified media or different cell lines. In this study, gassing rates and dilution rates were varied for a semi-continuous cell culture system in the ambr15™ bioreactor. The corresponding changes to metabolite production and consumption, as well as cell growth rate and therapeutic protein production were measured. Conditions were identified in the ambr15™ bioreactor that produced metabolic shifts and specific metabolic and protein production rates also seen in the corresponding larger (5 liter) scale perfusion process. A Dynamic Flux Balance model was employed to understand and predict the metabolic changes observed. The DFB model-predicted trends observed experimentally, including lower specific glucose consumption when CO₂ was maintained at higher levels (i.e. 100 mm Hg) in the broth. A Computational Fluid Dynamic (CFD) model of the ambr15™ was also developed, to understand transfer of O₂ and CO₂ to the liquid. This CFD model predicted gas-liquid flow in the bioreactor using the ANSYS software. The two-phase flow equations were solved via an Eulerian method, with population balance equations tracking the size of the gas bubbles resulting from breakage and coalescence. Reasonable results were obtained in that the Carbon Dioxide mass transfer coefficient (kLa) and the air hold up increased with higher gas flow rate. Volume-averaged kLa values at 500 RPM increased as the gas flow rate was doubled and matched experimentally determined values. These results form a solid basis for optimizing the ambr15™, using both CFD and FBA modelling approaches together, for use in microscale simulations of larger scale cell culture processes.

Keywords: cell culture, computational fluid dynamics, dynamic flux balance analysis, microbioreactor

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Authors: Amarasinghe Shashikala, Pramudika Hansini, Fernando Tajan, Rathnayake Piyumi

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This study investigates the prominence of the social entrepreneurship (SE) model over the sustainable entrepreneurship model among Sri Lankan exporters in the small and medium enterprise (SME) sector. The primary objective of this study is to explore how the unique socio-economic contextual nuances of the country influence this behavior. The study employs a multiple-case study approach, collecting data from thirteen SEs in the SME sector. The findings reveal a significant alignment between SE and the lifestyle of the people in Sri Lanka, attributed largely to its deep-rooted religious setting and cultural norms. A crucial factor driving the prominence of SE is the predominantly labor-intensive nature of production processes within the exporters of the SME sector. These processes inherently lend themselves to SE, providing employment opportunities and fostering community engagement. Further, SE initiatives substantially resonate with community-centric practices, making them more appealing and accessible to the local populace. In contrast, the findings highlight a dilemma between cost-effectiveness and sustainable entrepreneurship. Transitioning to sustainable export products and production processes is demanded by foreign buyers and acknowledged as essential for environmental stewardship, which often requires capital-intensive makeovers. This investment inevitably raises the overall cost of the export product, making it less competitive in the global market. Interestingly, the study notes a disparity between international demand for sustainable products and the willingness of buyers to pay a premium for them. Despite the growing global preference for eco-friendly options, the findings suggest that the additional costs associated with sustainable entrepreneurship are not adequately reflected in the purchasing behavior of international buyers. The abundance of natural resources coupled with a minimal occurrence of natural catastrophes renders exporters less environmentally sensitive. The absence of robust policy support for environmental preservation exacerbates this inclination. Consequently, exporters exhibit a diminished motivation to incorporate environmental sustainability into their business decisions. Instead, attention is redirected towards factors such as the local population's minimum standards of living, prevalent social issues, governmental corruption and inefficiency, and rural poverty. These elements impel exporters to prioritize social well-being when making business decisions. Notably, the emphasis on social impact, rather than environmental impact, appears to be a generational trend, perpetuating a focus on societal aspects in the realm of business. In conclusion, the manifestation of entrepreneurial behavior within developing nations is notably contingent upon contextual nuances. This investigation contributes to a deeper understanding of the dynamics shaping the prevalence of SE over sustainable entrepreneurship among Sri Lankan exporters in the SME sector. The insights generated have implications for policymakers, industry stakeholders, and academics seeking to navigate the delicate balance between socio-cultural values, economic feasibility, and environmental sustainability in the pursuit of responsible business practices within the export sector.

Keywords: small and medium enterprises, social entrepreneurship, Sri Lanka, sustainable entrepreneurship

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Authors: Zhiwu Zheng, Prakhar Kumar, Sigurd Wagner, Naveen Verma, James C. Sturm

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Soft robots have drawn great interest recently due to a rich range of possible shapes and motions they can take on to address new applications, compared to traditional rigid robots. Large-area electronics (LAE) provides a unique platform for creating soft robots by leveraging thin-film technology to enable the integration of a large number of actuators, sensors, and control circuits on flexible sheets. However, the rich shapes and motions possible, especially when interacting with complex environments, pose significant challenges to forming well-generalized and robust models necessary for robot design and control. In this work, we describe an analytical model for predicting the shape and locomotion of a flexible (steel-foil-based) piezoelectric-actuated 2D robot based on Euler-Bernoulli beam theory. It is nominally (unpowered) lying flat on the ground, and when powered, its shape is controlled by an array of piezoelectric thin-film actuators. Key features of the models are its ability to incorporate the significant effects of gravity on the shape and to precisely predict the spatial distribution of friction against the contacting surfaces, necessary for determining inchworm-type motion. We verified the model by developing a distributed discrete element representation of a continuous piezoelectric actuator and by comparing its analytical predictions to discrete-element robot simulations using PyBullet. Without gravity, predicting the shape of a sheet with a linear array of piezoelectric actuators at arbitrary voltages is straightforward. However, gravity significantly distorts the shape of the sheet, causing some segments to flatten against the ground. Our work includes the following contributions: (i) A self-consistent approach was developed to exactly determine which parts of the soft robot are lifted off the ground, and the exact shape of these sections, for an arbitrary array of piezoelectric voltages and configurations. (ii) Inchworm-type motion relies on controlling the relative friction with the ground surface in different sections of the robot. By adding torque-balance to our model and analyzing shear forces, the model can then determine the exact spatial distribution of the vertical force that the ground is exerting on the soft robot. Through this, the spatial distribution of friction forces between ground and robot can be determined. (iii) By combining this spatial friction distribution with the shape of the soft robot, in the function of time as piezoelectric actuator voltages are changed, the inchworm-type locomotion of the robot can be determined. As a practical example, we calculated the performance of a 5-actuator system on a 50-µm thick steel foil. Piezoelectric properties of commercially available thin-film piezoelectric actuators were assumed. The model predicted inchworm motion of up to 200 µm per step. For independent verification, we also modelled the system using PyBullet, a discrete-element robot simulator. To model a continuous thin-film piezoelectric actuator, we broke each actuator into multiple segments, each of which consisted of two rigid arms with appropriate mass connected with a 'motor' whose torque was set by the applied actuator voltage. Excellent agreement between our analytical model and the discrete-element simulator was shown for both for the full deformation shape and motion of the robot.

Keywords: analytical modeling, piezoelectric actuators, soft robot locomotion, thin-film technology

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Authors: Moustafa Osman Mohammed

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Construction industry, as one of the main contributor in depletion of natural resources, influences climate change. This paper discusses incremental and evolutionary development of the proposed models for optimization of a life-cycle analysis to explicit strategy for evaluation systems. The main categories are virtually irresistible for introducing uncertainties, uptake composite structure model (CSM) as environmental management systems (EMSs) in a practice science of evaluation small and medium-sized enterprises (SMEs). The model simplified complex systems to reflect nature systems’ input, output and outcomes mode influence “framework measures” and give a maximum likelihood estimation of how elements are simulated over the composite structure. The traditional knowledge of modeling is based on physical dynamic and static patterns regarding parameters influence environment. It unified methods to demonstrate how construction systems ecology interrelated from management prospective in procedure reflects the effect of the effects of engineering systems to ecology as ultimately unified technologies in extensive range beyond constructions impact so as, - energy systems. Sustainability broadens socioeconomic parameters to practice science that meets recovery performance, engineering reflects the generic control of protective systems. When the environmental model employed properly, management decision process in governments or corporations could address policy for accomplishment strategic plans precisely. The management and engineering limitation focuses on autocatalytic control as a close cellular system to naturally balance anthropogenic insertions or aggregation structure systems to pound equilibrium as steady stable conditions. Thereby, construction systems ecology incorporates engineering and management scheme, as a midpoint stage between biotic and abiotic components to predict constructions impact. The later outcomes’ theory of environmental obligation suggests either a procedures of method or technique that is achieved in sustainability impact of construction system ecology (SICSE), as a relative mitigation measure of deviation control, ultimately.

Keywords: sustainability, environmental impact assessment, environemtal management, construction ecology

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Authors: June Keeling, Christina Athanasiades, Vaiva Hendrixson, Delyth Wyndham

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Recognition and education in violence, abuse, and neglect for medical and healthcare practitioners (REVAMP) is a trans-European project aiming to introduce a training programme that has been specifically developed by partners across seven European countries to meet the needs of medical and healthcare practitioners. Amalgamating the knowledge and experience of clinicians, researchers, and educators from interdisciplinary and multi-professional backgrounds, REVAMP has tackled the under-resourced and underdeveloped area of domestic violence and abuse. The team designed an online training programme to support medical and healthcare practitioners to recognise and respond appropriately to survivors of domestic violence and abuse at their point of contact with a health provider. The REVAMP partner countries include Europe: France, Lithuania, Germany, Greece, Iceland, Norway, and the UK. The training is delivered through a series of interactive online modules, adapting evidence-based pedagogical approaches to learning. Capturing and addressing the complexities of the project impacted the methodological decisions and approaches to evaluation. The challenge was to find an evaluation methodology that captured valid data across all partner languages to demonstrate the extent of the change in knowledge and understanding. Co-development by all team members was a lengthy iterative process, challenged by a lack of consistency in terminology. A mixed methods approach enabled both qualitative and quantitative data to be collected, at the start, during, and at the conclusion of the training for the purposes of evaluation. The module content and evaluation instrument were accessible in each partner country's language. Collecting both types of data provided a high-level snapshot of attainment via the quantitative dataset and an in-depth understanding of the impact of the training from the qualitative dataset. The analysis was mixed methods, with integration at multiple interfaces. The primary focus of the analysis was to support the overall project evaluation for the funding agency. A key project outcome was identifying that the trans-European approach posed several challenges. Firstly, the project partners did not share a first language or a legal or professional approach to domestic abuse and neglect. This was negotiated through complex, systematic, and iterative interaction between team members so that consensus could be achieved. Secondly, the context of the data collection in several different cultural, educational, and healthcare systems across Europe challenged the development of a robust evaluation. The participants in the pilot evaluation shared that the training was contemporary, well-designed, and of great relevance to inform practice. Initial results from the evaluation indicated that the participants were drawn from more than eight partner countries due to the online nature of the training. The primary results indicated a high level of engagement with the content and achievement through the online assessment. The main finding was that the participants perceived the impact of domestic abuse and neglect in very different ways in their individual professional contexts. Most significantly, the participants recognised the need for the training and the gap that existed previously. It is notable that a mixed-methods evaluation of a trans-European project is unusual at this scale.

Keywords: domestic violence, e-learning, health professionals, trans-European

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Authors: Jessica Gu, Yu Chen

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Knowledge Management (KM) is undoubtable crucial to organizational value creation, learning, and adaptation. Although the rapidly growing KM domain has been fueled with full-fledged methodologies and technologies, studies on KM evolution that bridge the organizational performance and adaptation to the organizational environment are still rarely attempted. In particular, creation (or generation) and diffusion (or share/exchange) of knowledge are of the organizational primary concerns on the problem-solving perspective, however, the optimized distribution of knowledge creation and diffusion endeavors are still unknown to knowledge workers. This research proposed an agent-based model of knowledge creation and diffusion in an organization, aiming at elucidating how the intertwining knowledge flows at microscopic level lead to optimized organizational performance at macroscopic level through evolution, and exploring what exogenous interventions by the policy maker and endogenous adjustments of the knowledge workers can better cope with different environmental conditions. With the developed model, a series of simulation experiments are conducted. Both long-term steady-state and time-dependent developmental results on organizational performance, network and structure, social interaction and learning among individuals, knowledge audit and stocktaking, and the likelihood of choosing knowledge creation and diffusion by the knowledge workers are obtained. One of the interesting findings reveals a non-monotonic phenomenon on organizational performance under turbulent environment while a monotonic phenomenon on organizational performance under a stable environment. Hence, whether the environmental condition is turbulence or stable, the most suitable exogenous KM policy and endogenous knowledge creation and diffusion choice adjustments can be identified for achieving the optimized organizational performance. Additional influential variables are further discussed and future work directions are finally elaborated. The proposed agent-based model generates evidence on how knowledge worker strategically allocates efforts on knowledge creation and diffusion, how the bottom-up interactions among individuals lead to emerged structure and optimized performance, and how environmental conditions bring in challenges to the organization system. Meanwhile, it serves as a roadmap and offers great macro and long-term insights to policy makers without interrupting the real organizational operation, sacrificing huge overhead cost, or introducing undesired panic to employees.

Keywords: knowledge creation, knowledge diffusion, agent-based modeling, organizational performance, decision making evolution

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Authors: Sung-Hee Nam, Kwang-Gill Lee, You-Young Jo, HaeYong Kweon

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Entomopathogenic fungi is a Cordyceps species that is isolated from dead silkworm and cicada. Fungi on cicadas were described in old Chinese medicinal books and From ancient times, vegetable wasps and plant worms were widely known to have active substance and have been studied for pharmacological use. Among many fungi belonging to the genus Cordyceps, Cordyceps sinensis have been demonstrated to yield natural products possessing various biological activities and many bioactive components. Generally, It is commonly used to replenish the kidney and soothe the lung, and for the treatment of fatigue. Due to their commercial and economic importance, the demand for Cordyceps has been rapidly increased. However, a supply of Cordyceps specimen could not meet the increasing demand because of their sole dependence on field collection and habitat destruction. Because it is difficult to obtain many insect hosts in nature and the edibility of host insect needs to be verified in a pharmacological aspect. Recently, this setback was overcome that P. tenuipes was able to be cultivated in a large scale using silkworm as host. Pharmacological effects of P. tenuipes cultured on silkworm such as strengthening immune function, anti-fatigue, anti-tumor activity and controlling liver etc have been proved. They are widely commercialized. In this study, we attempted to establish a method for stable growth inhibition of P. tenuipes on silkworm hosts and an optimal condition for synnemata formation. To determine optimum culturing conditions, temperature and light conditions were varied. The length and number of synnemata was highest at 25℃ temperature and 100~300 lux illumination. On an average, the synnemata of wild P. tenuipes measures 70 ㎜ in length and 20 in number; those of the cultured strain were relatively shorter and more in number. The number of synnemata may have increased as a result of inoculating the host with highly concentrated conidia, while the length may have decreased due to limited nutrition per individual. It is not able that changes in light illumination cause morphological variations in the synnemata. However, regulation of only light and temperature could not produce stromata like perithecia, asci, and ascospores. Yamanaka reported that although a complete fruiting body can be produced under optimal culture conditions, it should be regarded as synnemata because it does not develop into an ascoma bearing ascospores.

Keywords: paecilomyces tenuipes, entomopathogenic fungi, silkworm larva, bombyx mori

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Authors: Sancho-Esper Franco, Rodríguez Sánchez Carla, Sánchez Carolina, Orús-Sanclemente Carlos

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Water scarcity is a reality that affects many regions of the world and is aggravated by climate change and population growth. Saving water has become an urgent need to ensure the sustainability of the planet and the survival of many communities, where youth and social networks play a key role in promoting responsible practices and adopting habits that contribute to environmental preservation. This study analyzes the persuasion capacity of messages designed to promote pro-environmental behaviors among youth. Specifically, it studies how the efficacy (effectiveness) of the response (personal response efficacy/effectiveness) and the perception of distance from the source of the message influence the water-saving behavior of the audience. To do so, two communication frameworks are combined. First, the Construal Level Theory, which is based on the concept of "psychological distance", that is, people, objects or events can be perceived as psychologically near or far, and this subjective distance (i.e., social, temporal, or spatial) determines their attitudes, emotions, and actions. This perceived distance can be social, temporal, or spatial. This research focuses on studying the spatial distance and social distance generated by cultural differences between influencers and their audience to understand how cultural distance can influence the persuasiveness of a message. Research on the effects of psychological distance between influencers-followers in the pro-environmental field is very limited, being relevant because people could learn specific behaviors suggested by opinion leaders such as influencers in social networks. Second, different approaches to behavioral change suggest that the perceived efficacy of a behavior can explain individual pro-environmental actions. People will be more likely to adopt a new behavior if they perceive that they are capable of performing it (efficacy belief) and that their behavior will effectively contribute to solving that problem (personal response efficacy). It is also important to study the different actors (social and individual) that are perceived as responsible for addressing environmental problems. Specifically, we analyze to what extent the belief individual’s water-saving actions are effective in solving the problem can influence water-saving behavior since this individual effectiveness increases people's sense of obligation and responsibility with the problem. However, in this regard, empirical evidence presents mixed results. Our study addresses the call for experimental studies manipulating different subtypes of response effectiveness to generate robust causal evidence. Based on all the above, this research analyzes whether cultural distance (local vs. international influencer) and the perception of effectiveness of behavior (personal response efficacy) (personal/individual vs. collective) affect the actual behavior and the intention to conserve water of social network users. An experiment of 2 (local influencer vs. international influencer) x 2 (effectiveness of individual vs. collective response) is designed and estimated. The results show that a message from a local influencer appealing to individual responsibility exerts greater influence on intention and actual water-saving behavior, given the cultural closeness between influencer-follower, and the appeal to individual responsibility increases the feeling of obligation to participate in pro-environmental actions. These results offer important implications for social marketing campaigns that seek to promote water conservation.

Keywords: social marketing, influencer, message framing, experiment, personal response efficacy, water saving

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Authors: Surinder Pal, Ajay Gupta, Johny Khajuria

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Casting simulation helps visualize mold filling and casting solidification; predict related defects like cold shut, shrinkage porosity and hard spots; and optimize the casting design to achieve the desired quality with high yield. Flow and solidification of molten metals are, however, a very complex phenomenon that is difficult to simulate correctly by conventional computational techniques, especially when the part geometry is intricate and the required inputs (like thermo-physical properties and heat transfer coefficients) are not available. Simulation software is based on the process of modeling a real phenomenon with a set of mathematical formulas. It is, essentially, a program that allows the user to observe an operation through simulation without actually performing that operation. Simulation software is used widely to design equipment so that the final product will be as close to design specs as possible without expensive in process modification. Simulation software with real-time response is often used in gaming, but it also has important industrial applications. When the penalty for improper operation is costly, such as airplane pilots, nuclear power plant operators, or chemical plant operators, a mockup of the actual control panel is connected to a real-time simulation of the physical response, giving valuable training experience without fear of a disastrous outcome. The all casting simulation software has own requirements, like magma cast has only best for crack simulation. The latest generation software Auto CAST developed at IIT Bombay provides a host of functions to support method engineers, including part thickness visualization, core design, multi-cavity mold design with common gating and feeding, application of various feed aids (feeder sleeves, chills, padding, etc.), simulation of mold filling and casting solidification, automatic optimization of feeders and gating driven by the desired quality level, and what-if cost analysis. IIT Bombay has developed a set of applications for the foundry industry to improve casting yield and quality. Casting simulation is a fast and efficient solution for process for advanced tool which is the result of more than 20 years of collaboration with major industrial partners and academic institutions around the world. In this paper the process of casting simulation is studied.

Keywords: casting simulation software’s, simulation technique’s, casting simulation, processes

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Authors: Hamzeh Alipour, Masoumeh Bagheri, Abbasali Raz, Javad Dadgar Pakdel, Kourosh Azizi, Aboozar Soltani, Mohammad Djaefar Moemenbellah-Fard

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Background: Maggot debridement therapy is an appropriate, effective, and controlled method using sterilized larvae of Luciliasericata (L.sericata) to treat wounds. Netrin-A is an enzyme in the Laminins family which secreted from salivary gland of L.sericata with a central role in neural regeneration and angiogenesis. This study aimed to production of new recombinant Netrin-A protein of Luciliasericata larvae by baculovirus expression vector system (BEVS) in SF9. Material and methods: In the first step, gene structure was subjected to the in silico studies, which were include determination of Antibacterial activity, Prion formation risk, homology modeling, Molecular docking analysis, and Optimization of recombinant protein. In the second step, the Netrin-A gene was cloned and amplified in pTG19 vector. After digestion with BamH1 and EcoR1 restriction enzymes, it was cloned in pFastBac HTA vector. It was then transformed into DH10Bac competent cells, and the recombinant Bacmid was subsequently transfected into insect Sf9 cells. The expressed recombinant Netrin-A was thus purified in the Ni-NTA agarose. This protein evaluation was done using SDS-PAGE and western blot, respectively. Finally, its concentration was calculated with the Bradford assay method. Results: The Bacmid vector structure with Netrin-A was successfully constructed and then expressed as Netrin-A protein in the Sf9 cell lane. The molecular weight of this protein was 52 kDa with 404 amino acids. In the in silico studies, fortunately, we predicted that recombinant LSNetrin-A have Antibacterial activity and without any prion formation risk.This molecule hasa high binding affinity to the Neogenin and a lower affinity to the DCC-specific receptors. Signal peptide located between amino acids 24 and 25. The concentration of Netrin-A recombinant protein was calculated to be 48.8 μg/ml. it was confirmed that the characterized gene in our previous study codes L. sericata Netrin-A enzyme. Conclusions: Successful generation of the recombinant Netrin-A, a secreted protein in L.sericata salivary glands, and because Luciliasericata larvae are used in larval therapy. Therefore, the findings of the present study could be useful to researchers in future studies on wound healing.

Keywords: blowfly, BEVS, gene, immature insect, recombinant protein, Sf9

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Authors: Qingqing Feng, S. Thomas Ng, Frank J. Xu, Jiduo Xing

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Faced with unprecedented challenges including aging assets, lack of maintenance budget, overtaxed and inefficient usage, and outcry for better service quality from the society, today’s infrastructure systems has become the main focus of many metropolises to pursue sustainable urban development and improve resilience. Digital twin, being one of the most innovative enabling technologies nowadays, may open up new ways for tackling various infrastructure asset management (IAM) problems. Digital twin application for IAM, as its name indicated, represents an evolving digital model of intended infrastructure that possesses functions including real-time monitoring; what-if events simulation; and scheduling, maintenance, and management optimization based on technologies like IoT, big data and AI. Up to now, there are already vast quantities of global initiatives of digital twin applications like 'Virtual Singapore' and 'Digital Built Britain'. With digital twin technology permeating the IAM field progressively, it is necessary to consider the maturity of the application and how those institutional or industrial digital twin application processes will evolve in future. In order to deal with the gap of lacking such kind of benchmark, a draft maturity model is developed for digital twin application in the IAM field. Firstly, an overview of current smart cities maturity models is given, based on which the draft Maturity Model of Digital Twin Application for Infrastructure Asset Management (MM-DTIAM) is developed for multi-stakeholders to evaluate and derive informed decision. The process of development follows a systematic approach with four major procedures, namely scoping, designing, populating and testing. Through in-depth literature review, interview and focus group meeting, the key domain areas are populated, defined and iteratively tuned. Finally, the case study of several digital twin projects is conducted for self-verification. The findings of the research reveal that: (i) the developed maturity model outlines five maturing levels leading to an optimised digital twin application from the aspects of strategic intent, data, technology, governance, and stakeholders’ engagement; (ii) based on the case study, levels 1 to 3 are already partially implemented in some initiatives while level 4 is on the way; and (iii) more practices are still needed to refine the draft to be mutually exclusive and collectively exhaustive in key domain areas.

Keywords: digital twin, infrastructure asset management, maturity model, smart city

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Authors: Ahmed Slami, Med El Amine Brixi Nigassa, Nassima Labdelli, Sofiane Soulimane, Arnaud Pothier

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Many people suffer from diabetes, a disease marked by abnormal levels of sugar in the blood; 285 million people have diabetes, 6.6% of the world adult population (in 2010), according to the International Diabetes Federation. Insulin medicament is invented to be injected into the body. Generally, the injection requires the patient to do it manually. However, in many cases he will be unable to inject the drug, saw that among the side effects of hyperglycemia is the weakness of the whole body. The researchers designed a medical device that injects insulin too autonomously by using micro-pumps. Many micro-pumps of concepts have been investigated during the last two decades for injecting molecules in blood or in the body. However, all these micro-pumps are intended for slow infusion of drug (injection of few microliters by minute). Now, the challenge is to develop micro-pumps for fast injections (1 microliter in 10 seconds) with accuracy of the order of microliter. Recently, studies have shown that only piezoelectric actuators can achieve this performance, knowing that few systems at the microscopic level were presented. These reasons lead us to design new smart microsystems injection drugs. Therefore, many technological advances are still to achieve the improvement of materials to their uses, while going through their characterization and modeling action mechanisms themselves. Moreover, it remains to study the integration of the piezoelectric micro-pump in the microfluidic platform features to explore and evaluate the performance of these new micro devices. In this work, we propose a new micro-pump model based on piezoelectric actuation with a new design. Here, we use a finite element model with Comsol software. Our device is composed of two pumping chambers, two diaphragms and two actuators (piezoelectric disks). The latter parts will apply a mechanical force on the membrane in a periodic manner. The membrane deformation allows the fluid pumping, the suction and discharge of the liquid. In this study, we present the modeling results as function as device geometry properties, films thickness, and materials properties. Here, we demonstrate that we can achieve fast injection. The results of these simulations will provide quantitative performance of our micro-pumps. Concern the spatial actuation, fluid rate and allows optimization of the fabrication process in terms of materials and integration steps.

Keywords: COMSOL software, piezoelectric, micro-pump, microfluidic

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Authors: Amna Tariq Shah

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Amid the pandemic, the contemporary landscape has experienced accelerated growth in small business activities and an expanding digital marketplace, further exacerbating the issue of non-compliance among self-employed individuals through aggressive tax planning and evasion. This research seeks to address these challenges by developing strategic tax policies that promote voluntary compliance and improve taxpayer facilitation. The study employs the innovative MINDSPACE framework to examine three psychosocial factors—tax communication, tax literacy, and shaming—to optimize policy responses, address administrative shortcomings, and ensure adequate revenue collection for public goods and services. Preliminary findings suggest that incomprehensible communication from tax authorities drives individuals to seek alternative, potentially biased sources of tax information, thereby exacerbating non-compliance. Furthermore, the study reveals low tax literacy among Australian and Pakistani respondents, with many struggling to navigate complex tax processes and comprehend tax laws. Consequently, policy recommendations include simplifying tax return filing and enhancing pre-populated tax returns. In terms of shaming, the research indicates that Australians, being an individualistic society, may not respond well to shaming techniques due to privacy concerns. In contrast, Pakistanis, as a collectivistic society, may be more receptive to naming and shaming approaches. The study employs a mixed-method approach, utilizing interviews and surveys to analyze the issue in both jurisdictions. The use of mixed methods allows for a more comprehensive understanding of tax compliance behavior, combining the depth of qualitative insights with the generalizability of quantitative data, ultimately leading to more robust and well-informed policy recommendations. By examining evidence from opposite jurisdictions, namely a developed country (Australia) and a developing country (Pakistan), the study's applicability is enhanced, providing perspectives from two disparate contexts that offer insights from opposite ends of the economic, cultural, and social spectra. The non-comparative case study methodology offers valuable insights into human behavior, which can be applied to other jurisdictions as well. The application of the MINDSPACE framework in this research is particularly significant, as it introduces a novel approach to tax compliance behavior analysis. By integrating insights from behavioral economics, the framework enables a comprehensive understanding of the psychological and social factors influencing taxpayer decision-making, facilitating the development of targeted and effective policy interventions. This research carries substantial importance as it addresses critical challenges in tax compliance and administration, with far-reaching implications for revenue collection and the provision of public goods and services. By investigating the psychosocial factors that influence taxpayer behavior and utilizing the MINDSPACE framework, the study contributes invaluable insights to the field of tax policy. These insights can inform policymakers and tax administrators in developing more effective tax policies that enhance taxpayer facilitation, address administrative obstacles, promote a more equitable and efficient tax system, and foster voluntary compliance, ultimately strengthening the financial foundation of governments and communities.

Keywords: individual tax compliance behavior, psychosocial factors, tax non-compliance, tax policy

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Authors: Bharti Verma, Chandrajit Balomajumder

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Water pollution is escalated owing to industrialization and random ejection of one or more toxic heavy metal ions from the semiconductor industry, electroplating, metallurgical, mining, chemical manufacturing, tannery industries, etc., In semiconductor industry various kinds of chemicals in wafers preparation are used . Fluoride, toxic solvent, heavy metals, dyes and salts, suspended solids and chelating agents may be found in wastewater effluent of semiconductor manufacturing industry. Also in the chrome plating, in the electroplating industry, the effluent contains heavy amounts of Chromium. Since Cr(VI) is highly toxic, its exposure poses an acute risk of health. Also, its chronic exposure can even lead to mutagenesis and carcinogenesis. On the contrary, Cr (III) which is naturally occurring, is much less toxic than Cr(VI). Discharge limit of hexavalent chromium and trivalent chromium are 0.05 mg/L and 5 mg/L, respectively. There are numerous methods such as adsorption, chemical precipitation, membrane filtration, ion exchange, and electrochemical methods for the heavy metal removal. The present study focuses on the removal of Chromium ions by using flat sheet UF5kDa membrane. The Ultra filtration membrane process is operated above micro filtration membrane process. Thus separation achieved may be influenced due to the effect of Sieving and Donnan effect. Ultrafiltration is a promising method for the rejection of heavy metals like chromium, fluoride, cadmium, nickel, arsenic, etc. from effluent water. Benefits behind ultrafiltration process are that the operation is quite simple, the removal efficiency is high as compared to some other methods of removal and it is reliable. Polyamide membranes have been selected for the present study on rejection of Cr(VI) from feed solution. The objective of the current work is to examine the rejection of Cr(VI) from aqueous feed solutions by flat sheet UF5kDa membranes with different parameters such as pressure, feed concentration and pH of the feed. The experiments revealed that with increasing pressure, the removal efficiency of Cr(VI) is increased. Also, the effect of pH of feed solution, the initial dosage of chromium in the feed solution has been studied. The membrane has been characterized by FTIR, SEM and AFM before and after the run. The mass transfer coefficients have been estimated. Membrane transport parameters have been calculated and have been found to be in a good correlation with the applied model.

Keywords: heavy metal removal, membrane process, waste water treatment, ultrafiltration

Procedia PDF Downloads 113

Authors: Mohammad R. Aghakashkooli, Milutin G. Jovanovic

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The brushless doubly-fed reluctance generator (BDFRG) is an emerging, medium-speed alternative to a conventional wound rotor slip-ring doubly-fed induction generator (DFIG) in wind energy conversion systems (WECS). It can provide competitive overall performance and similar low failure rates of a typically 30% rated back-to-back power electronics converter in 2:1 speed ranges but with the following important reliability and cost advantages over DFIG: the maintenance-free operation afforded by its brushless structure, 50% synchronous speed with the same number of rotor poles (allowing the use of a more compact, and more efficient two-stage gearbox instead of a vulnerable three-stage one), and superior grid integration properties including simpler protection for the low voltage ride through compliance of the fractional converter due to the comparatively higher leakage inductances and lower fault currents. Vector controlled pulse-width-modulated converters generally feature a much lower total harmonic distortion relative to hysteresis counterparts with variable switching rates and as such have been a predominant choice for BDFRG (and DFIG) wind turbines. Eliminating a shaft position sensor, which is often required for control implementation in this case, would be desirable to address the associated reliability issues. This fact has largely motivated the recent growing research of sensorless methods and developments of various rotor position and/or speed estimation techniques for this purpose. The main limitation of all the observer-based control approaches for grid-connected wind power applications of the BDFRG reported in the open literature is the requirement for pre-commissioning procedures and prior knowledge of the machine inductances, which are usually difficult to accurately identify by off-line testing. A model reference adaptive system (MRAS) based sensor-less vector control scheme to be presented will overcome this shortcoming. The true machine parameter independence of the proposed field-oriented algorithm, offering robust, inherently decoupled real and reactive power control of the grid-connected winding, is achieved by on-line estimation of the inductance ratio, the underlying rotor angular velocity and position MRAS observer being reliant upon. Such an observer configuration will be more practical to implement and clearly preferable to the existing machine parameter dependent solutions, and especially bearing in mind that with very little modifications it can be adapted for commercial DFIGs with immediately obvious further industrial benefits and prospects of this work. The excellent encoder-less controller performance with maximum power point tracking in the base speed region will be demonstrated by realistic simulation studies using large-scale BDFRG design data and verified by experimental results on a small laboratory prototype of the WECS emulation facility.

Keywords: brushless doubly fed reluctance generator, model reference adaptive system, sensorless vector control, wind energy conversion

Procedia PDF Downloads 38

Authors: Ana-Carolina Feltrin, Daniel Hedman, Farid Akhtar

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High entropy ceramic (HEC) materials are characterized by their compositional disorder due to different metallic element atoms occupying the cation position and non-metal elements occupying the anion position. Several studies have focused on the processing and characterization of high entropy carbides and high entropy borides, as these HECs present interesting mechanical and chemical properties. A few studies have been published on HECs containing two non-metallic elements in the composition. Dual-phase high entropy (Ti₀.₂₅V₀.₂₅Zr₀.₂₅Hf₀.₂₅)BxCy ceramics with different amounts of x and y, (0.25 HfC + 0.25 ZrC + 0.25 VC + 0.25 TiB₂), (0.25 HfC + 0.25 ZrC + 0.25 VB2 + 0.25 TiB₂) and (0.25 HfC + 0.25 ZrB2 + 0.25 VB2 + 0.25 TiB₂) were sintered from boride and carbide precursor powders using SPS at 2000°C with holding time of 10 min, uniaxial pressure of 50 MPa and under Ar atmosphere. The sintered specimens formed two HEC phases: a Zr-Hf rich FCC phase and a Ti-V HCP phase, and both phases contained all the metallic elements from 5-50 at%. Phase quantification analysis of XRD data revealed that the molar amount of hexagonal phase increased with increased mole fraction of borides in the starting powders, whereas cubic FCC phase increased with increased carbide in the starting powders. SPS consolidated (Ti₀.₂₅V₀.₂₅Zr₀.₂₅Hf₀.₂₅)BC0.5 and (Ti₀.₂₅V₀.₂₅Zr₀.₂₅Hf₀.₂₅)B1.5C0.25 had respectively 94.74% and 88.56% relative density. (Ti₀.₂₅V₀.₂₅Zr₀.₂₅Hf₀.₂₅)B0.5C0.75 presented the highest relative density of 95.99%, with Vickers hardness of 26.58±1.2 GPa for the borides phase and 18.29±0.8 GPa for the carbides phase, which exceeded the reported hardness values reported in the literature for high entropy ceramics. The SPS sintered specimens containing lower boron and higher carbon presented superior properties even though the metallic composition in each phase was similar to other compositions investigated. Dual-phase high entropy (Ti₀.₂₅V₀.₂₅Zr₀.₂₅H₀.₂₅)BxCy ceramics were successfully fabricated in a boride-carbide solid solution and the amount of boron and carbon was shown to influence the phase fraction, hardness of phases, and density of the consolidated HECs. The microstructure and phase formation was highly dependent on the amount of non-metallic elements in the composition and not only the molar ratio between metals when producing high entropy ceramics with more than one anion in the sublattice. These findings show the importance of further studies about the optimization of the ratio between C and B for further improvements in the properties of dual-phase high entropy ceramics.

Keywords: high-entropy ceramics, borides, carbides, dual-phase

Procedia PDF Downloads 141

Authors: Ainura Tursunalieva, Irene Hudson

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Continuous improvement of both the quality and safety of health care is an important goal in Australia and internationally. The intensive care unit (ICU) receives patients with a wide variety of and severity of illnesses. Accurately identifying patients at risk of developing complications or dying is crucial to increasing healthcare efficiency. Thus, it is essential for clinicians and researchers to have a robust framework capable of evaluating the risk profile of a patient. ICU scoring systems provide such a framework. The Acute Physiology and Chronic Health Evaluation III and the Simplified Acute Physiology Score II are ICU scoring systems frequently used for assessing the severity of acute illness. These scoring systems collect multiple risk factors for each patient including physiological measurements then render the assessment outcomes of individual risk factors into a single numerical value. A higher score is related to a more severe patient condition. Furthermore, the Mortality Probability Model II uses logistic regression based on independent risk factors to predict a patient’s probability of mortality. An important overlooked limitation of SAPS II and MPM II is that they do not, to date, include interaction terms between a patient’s vital signs. This is a prominent oversight as it is likely there is an interplay among vital signs. The co-existence of certain conditions may pose a greater health risk than when these conditions exist independently. One barrier to including such interaction terms in predictive models is the dimensionality issue as it becomes difficult to use variable selection. We propose an innovative scoring system which takes into account a dependence structure among patient’s vital signs, such as systolic and diastolic blood pressures, heart rate, pulse interval, and peripheral oxygen saturation. Copulas will capture the dependence among normally distributed and skewed variables as some of the vital sign distributions are skewed. The estimated dependence parameter will then be incorporated into the traditional scoring systems to adjust the points allocated for the individual vital sign measurements. The same dependence parameter will also be used to create an alternative copula-based model for predicting a patient’s probability of mortality. The new copula-based approach will accommodate not only a patient’s trajectories of vital signs but also the joint dependence probabilities among the vital signs. We hypothesise that this approach will produce more stable assessments and lead to more time efficient and accurate predictions. We will use two data sets: (1) 250 ICU patients admitted once to the Chui Regional Hospital (Kyrgyzstan) and (2) 37 ICU patients’ agitation-sedation profiles collected by the Hunter Medical Research Institute (Australia). Both the traditional scoring approach and our copula-based approach will be evaluated using the Brier score to indicate overall model performance, the concordance (or c) statistic to indicate the discriminative ability (or area under the receiver operating characteristic (ROC) curve), and goodness-of-fit statistics for calibration. We will also report discrimination and calibration values and establish visualization of the copulas and high dimensional regions of risk interrelating two or three vital signs in so-called higher dimensional ROCs.

Keywords: copula, intensive unit scoring system, ROC curves, vital sign dependence

Procedia PDF Downloads 129

Authors: V. Keim, J. Spachtholz, J. Hammer

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The importance of fibre reinforced plastics continually increases due to the excellent mechanical properties, low material and manufacturing costs combined with significant weight reduction. Today, components are usually designed and calculated numerically by using finite element methods (FEM) to avoid expensive laboratory tests. These programs are based on material models including material specific deformation characteristics. In this research project, material models for short glass fibre reinforced plastics are presented to simulate the visco-elasto-plastic deformation behaviour. Prior to modelling specimens of the material EMS Grivory HTV-5H1, consisting of a Polyphthalamide matrix reinforced by 50wt.-% of short glass fibres, are characterized experimentally in terms of the highly time dependent deformation behaviour of the matrix material. To minimize the experimental effort, the cyclic deformation behaviour under tensile and compressive loading (R = −1) is characterized by isothermal complex low cycle fatigue (CLCF) tests. Combining cycles under two strain amplitudes and strain rates within three orders of magnitude and relaxation intervals into one experiment the visco-elastic deformation is characterized. To identify visco-plastic deformation monotonous tensile tests either displacement controlled or strain controlled (CERT) are compared. All relevant modelling parameters for this complex superposition of simultaneously varying mechanical loadings are quantified by these experiments. Subsequently, two different material models are compared with respect to their accuracy describing the visco-elasto-plastic deformation behaviour. First, based on Chaboche an extended 12 parameter model (EVP-KV2) is used to model cyclic visco-elasto-plasticity at two time scales. The parameters of the model including a total separation of elastic and plastic deformation are obtained by computational optimization using an evolutionary algorithm based on a fitness function called genetic algorithm. Second, the 12 parameter visco-elasto-plastic material model by Launay is used. In detail, the model contains a different type of a flow function based on the definition of the visco-plastic deformation as a part of the overall deformation. The accuracy of the models is verified by corresponding experimental LCF testing.

Keywords: complex low cycle fatigue, material modelling, short glass fibre reinforced polyphthalamides, visco-elasto-plastic deformation

Procedia PDF Downloads 190

Authors: Kuhorfah Emmanuel Mawuli

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Generally, for firms to enhance their operational efficiency of logistics, it is imperative to assess the logistics function. The cost of logistics conventionally represents a key consideration in the pricing decisions of firms, which suggests that cost efficiency in logistics can go a long way to improve margins. Warehousing, which is a key part of logistics operations, has the prospect of influencing operational efficiency in logistics management as well as customer value, but this potential has often not been recognized. It has been found that there is a paucity of research that evaluates the efficiency of warehouses. Indeed, limited research has been conducted to examine potential barriers to effective warehousing management. Due to this paucity of research, there is limited knowledge on how to address the obstacles associated with warehousing management. In order for warehousing management to become profitable, there is the need to integrate, balance, and manage the economic inputs and outputs of the entire warehouse operations, something that many firms tend to ignore. Management of warehousing is not solely related to storage functions. Instead, effective warehousing management requires such practices as maximum possible mechanization and automation of operations, optimal use of space and capacity of storage facilities, organization through "continuous flow" of goods, a planned system of storage operations, and safety of goods. For example, there is an important need for space utilization of the warehouse surface as it is a good way to evaluate the storing operation and pick items per hour. In the setting of Mantrac Ghana, not much knowledge regarding the management of the warehouses exists. The researcher has personally observed many gaps in the management of the warehouse facilities in the case organization Mantrac Ghana. It is important, therefore, to assess the warehouse facility management of the case company with the objective of identifying weaknesses for improvement. The study employs an in-depth qualitative research approach using interviews as a mode of data collection. Respondents in the study mainly comprised warehouse facility managers in the studied company. A total of 10 participants were selected for the study using a purposive sampling strategy. Results emanating from the study demonstrate limited warehousing effectiveness in the case company. Findings further reveal that the major barriers to effective warehousing facility management comprise poor layout, poor picking optimization, labour costs, and inaccurate orders; policy implications of the study findings are finally outlined.

Keywords: assessing, warehousing, facility, management

Procedia PDF Downloads 35

Authors: Ibtisam A. Abbas Al-Darkazly

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In this study, the mechanical properties of alginate hydrogel material for self-standing 3D scaffold architecture with proper shape fidelity are investigated. In-lab built 3D bio-printer extrusion-based technology is utilized to fabricate 3D alginate scaffold constructs. The pressure, needle speed and stage speed are varied using a computer-controlled system. The experimental result indicates that the concentration of alginate solution, calcium chloride (CaCl₂) cross-linking concentration and cross-linking ratios lead to the formation of alginate hydrogel with various gelation states. Besides, the gelling conditions, such as cross-linking reaction time and temperature also have a significant effect on the mechanical properties of alginate hydrogel. Various experimental tests such as the material gelation, the material spreading and the printability test for filament collapse as well as the swelling test were conducted to evaluate the fabricated 3D scaffold constructs. The result indicates that the fabricated 3D scaffold from composition of 3.5% wt alginate solution, that is prepared in DI water and 1% wt CaCl₂ solution with cross-linking ratios of 7:3 show good printability and sustain good shape fidelity for more than 20 days, compared to alginate hydrogel that is prepared in a phosphate buffered saline (PBS). The fabricated self-standing 3D scaffold constructs measured 30 mm × 30 mm and consisted of 4 layers (n = 4) show good pore geometry and clear grid structure after printing. In addition, the percentage change of swelling degree exhibits high swelling capability with respect to time. The swelling test shows that the geometry of 3D alginate-scaffold construct and of the macro-pore are rarely changed, which indicates the capability of holding the shape fidelity during the incubation period. This study demonstrated that the mechanical and physical properties of alginate hydrogel could be tuned for a 3D bio-printing extrusion-based system to fabricate self-standing 3D scaffold soft structures. This 3D bioengineered scaffold provides a natural microenvironment present in the extracellular matrix of the tissue, which could be seeded with the biological cells to generate the desired 3D live tissue model for in vitro and in vivo tissue engineering applications.

Keywords: biomaterial, calcium chloride, 3D bio-printing, extrusion, scaffold, sodium alginate, tissue engineering

Procedia PDF Downloads 90

Authors: Ramon Omar Rosales-Espinoza

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Pile-to-pile mechanical connections are used if the depth of the soil layers with sufficient bearing strength exceeds the original (“leading”) pile length, with the additional pile segment being termed “extension” pile. Mechanical connectors permit a safe transmission of forces from leading to extension pile while meeting strength and serviceability requirements. Common types of connectors consist of an assembly of sleeve-type external couplers, bolts, pins, and other mechanical interlock devices that ensure the transmission of compressive, tensile, torsional and bending stresses between leading and extension pile segments. While welded connections allow for a relatively simple structural design, mechanical connections are advantageous over welded connections because they lead to shorter installation times and significant cost reductions since specialized workmanship and inspection activities are not required. However, common practices followed to design mechanical connectors neglect important aspects of the assembly response, such as stress concentration around pin/bolt holes, torsional stresses from the installation process, and interaction between the forces at the installation (torsion), service (compression/tension-bending), and removal stages (torsion). This translates into potentially unsatisfactory designs in terms of the ultimate and service limit states, exhibiting either reduced strength or excessive deformations. In this study, the experimental response under compressive forces of a type of mechanical connector is presented, in terms of strength, deformation and failure modes. The tests revealed that the type of connector used can safely transmit forces from pile to pile. Using the results from the compressive tests, an analysis model was developed using the finite element (FE) method to study the interaction of forces under installation and service stages of a typical mechanical connector. The response of the analysis model is used to identify potential areas for design optimization, including size, gap between leading and extension piles, number of pin/bolts, hole sizes, and material properties. The results show the design of mechanical connectors should take into account the interaction of forces present at every stage of their life cycle, and that the torsional stresses occurring during installation are critical for the safety of the assembly.

Keywords: piles, FEA, steel, mechanical connector

Procedia PDF Downloads 242

Authors: Yangzhi Li

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Network transfer of information and performance customization is now a viable method of digital industrial production in the era of Industry 4.0. Robot platforms and network platforms have grown more important in digital design and construction. The pressing need for novel building techniques is driven by the growing labor scarcity problem and increased awareness of construction safety. Robotic approaches in construction research are regarded as an extension of operational and production tools. Several technological theories related to robot autonomous recognition, which include high-performance computing, physical system modeling, extensive sensor coordination, and dataset deep learning, have not been explored using intelligent construction. Relevant transdisciplinary theory and practice research still has specific gaps. Optimizing high-performance computing and autonomous recognition visual guidance technologies improves the robot's grasp of the scene and capacity for autonomous operation. Intelligent vision guidance technology for industrial robots has a serious issue with camera calibration, and the use of intelligent visual guiding and identification technologies for industrial robots in industrial production has strict accuracy requirements. It can be considered that visual recognition systems have challenges with precision issues. In such a situation, it will directly impact the effectiveness and standard of industrial production, necessitating a strengthening of the visual guiding study on positioning precision in recognition technology. To best facilitate the handling of complicated components, an approach for the visual recognition of parts utilizing machine learning algorithms is proposed. This study will identify the position of target components by detecting the information at the boundary and corner of a dense point cloud and determining the aspect ratio in accordance with the guidelines for the modularization of building components. To collect and use components, operational processing systems assign them to the same coordinate system based on their locations and postures. The RGB image's inclination detection and the depth image's verification will be used to determine the component's present posture. Finally, a virtual environment model for the robot's obstacle-avoidance route will be constructed using the point cloud information.

Keywords: robotic construction, robotic assembly, visual guidance, machine learning

Procedia PDF Downloads 56

Authors: Calister Wingang Makebe, Wilson Ambindei Agwanande, Emmanuel Jong Nso, P. Nisha

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Traditional liquid-state fermentation processes of Annona muricata L. juice can result in fluctuating product quality and quantity due to difficulties in control and scale up. This work describes a laboratory-scale batch fermentation process to produce a probiotic Annona muricata L. enzymatically extracted juice, which was modeled using the Doehlert design with independent extraction factors being incubation time, temperature, and enzyme concentration. It aimed at a better understanding of the traditional process as an initial step for future optimization. Annona muricata L. juice was fermented with L. acidophilus (NCDC 291) (LA), L. casei (NCDC 17) (LC), and a blend of LA and LC (LCA) for 72 h at 37 °C. Experimental data were fitted into mathematical models (Monod, Logistic and Luedeking and Piret models) using MATLAB software, to describe biomass growth, sugar utilization, and organic acid production. The optimal fermentation time was obtained based on cell viability, which was 24 h for LC and 36 h for LA and LCA. The model was particularly effective in estimating biomass growth, reducing sugar consumption, and lactic acid production. The values of the determination coefficient, R2, were 0.9946, 0.9913 and 0.9946, while the residual sum of square error, SSE, was 0.2876, 0.1738 and 0.1589 for LC, LA and LCA, respectively. The growth kinetic parameters included the maximum specific growth rate, µm, which was 0.2876 h-1, 0.1738 h-1 and 0.1589 h-1 as well as the substrate saturation, Ks, with 9.0680 g/L, 9.9337 g/L and 9.0709 g/L respectively for LC, LA and LCA. For the stoichiometric parameters, the yield of biomass based on utilized substrate (YXS) was 50.7932, 3.3940 and 61.0202, and the yield of product based on utilized substrate (YPS) was 2.4524, 0.2307 and 0.7415 for LC, LA, and LCA, respectively. In addition, the maintenance energy parameter (ms) was 0.0128, 0.0001 and 0.0004 with respect to LC, LA and LCA. With the kinetic model proposed by Luedeking and Piret for lactic acid production rate, the growth associated, and non-growth associated coefficients were determined as 1.0028 and 0.0109, respectively. The model was demonstrated for batch growth of LA, LC, and LCA in Annona muricata L. juice. The present investigation validates the potential of Annona muricata L. based medium for heightened economical production of a probiotic medium.

Keywords: L. acidophilus, L. casei, fermentation, modelling, kinetics

Procedia PDF Downloads 47

Authors: Jing Jin

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The incorporation of artificial intelligence (AI) and machine learning (ML) in aircraft manufacturing and aerospace supply chains leads to the generation of a substantial amount of data among various tiers of suppliers and OEMs. Identifying the high-quality information challenges decision-makers. The application of AI/ML models necessitates access to 'high-quality' information to yield desired outputs. However, the process of information sharing introduces complexities, including distortion through various communication channels and biases introduced by both human and AI entities. This phenomenon significantly influences the quality of information, impacting decision-makers engaged in configuring supply chain systems. Traditionally, distorted information is categorized as 'low-quality'; however, this study challenges this perception, positing that distorted information, contributing to stakeholder goals, can be deemed high-quality within supply chains. The main aim of this study is to identify and evaluate the dimensions of information quality crucial to the UK aerospace supply chain. Guided by a central research question, "What information quality dimensions are considered when defining information quality in the UK aerospace supply chain?" the study delves into the intricate dynamics of information quality in the aerospace industry. Additionally, the research explores the nuanced impact of information distortion on stakeholders' decision-making processes, addressing the question, "How does the information distortion phenomenon influence stakeholders’ decisions regarding information quality in the UK aerospace supply chain system?" This study employs deductive methodologies rooted in positivism, utilizing a cross-sectional approach and a mono-quantitative method -a questionnaire survey. Data is systematically collected from diverse tiers of supply chain stakeholders, encompassing end-customers, OEMs, Tier 0.5, Tier 1, and Tier 2 suppliers. Employing robust statistical data analysis methods, including mean values, mode values, standard deviation, one-way analysis of variance (ANOVA), and Pearson’s correlation analysis, the study interprets and extracts meaningful insights from the gathered data. Initial analyses challenge conventional notions, revealing that information distortion positively influences the definition of information quality, disrupting the established perception of distorted information as inherently low-quality. Further exploration through correlation analysis unveils the varied perspectives of different stakeholder tiers on the impact of information distortion on specific information quality dimensions. For instance, Tier 2 suppliers demonstrate strong positive correlations between information distortion and dimensions like access security, accuracy, interpretability, and timeliness. Conversely, Tier 1 suppliers emphasise strong negative influences on the security of accessing information and negligible impact on information timeliness. Tier 0.5 suppliers showcase very strong positive correlations with dimensions like conciseness and completeness, while OEMs exhibit limited interest in considering information distortion within the supply chain. Introducing social network analysis (SNA) provides a structural understanding of the relationships between information distortion and quality dimensions. The moderately high density of ‘information distortion-by-information quality’ underscores the interconnected nature of these factors. In conclusion, this study offers a nuanced exploration of information quality dimensions in the UK aerospace supply chain, highlighting the significance of individual perspectives across different tiers. The positive influence of information distortion challenges prevailing assumptions, fostering a more nuanced understanding of information's role in the Industry 4.0 landscape.

Keywords: information distortion, information quality, supply chain configuration, UK aerospace industry

Procedia PDF Downloads 26

Authors: Gianmaria Califano, Júlio Augusto Lucena Maciel, Olfa Zarrouk, Miguel Damasio, Jose Silvestre, Ana Margarida Fortes

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Global warming, with rapid and sudden changes in meteorological conditions, is one of the major constraints to ensuring agricultural and crop resilience in the Mediterranean regions. Several strategies are being adopted to reduce the pressure of drought stress on grapevines at regional and local scales: improvements in the irrigation systems, adoption of interline cover crops, and adaptation of pruning techniques. However, still, more can be achieved if also microbial compartments associated with plants are considered in crop management. It is known that the microbial community change according to several factors such as latitude, plant variety, age, rootstock, soil composition and agricultural management system. Considering the increasing pressure of the biotic and abiotic stresses, it is of utmost necessity to also evaluate the effects of drought on the microbiome associated with the grapevine, which is a commercially important crop worldwide. In this study, we characterize the diversity and the structure of the microbial community under three long-term irrigation levels (100% ETc, 50% ETc and rain-fed) in a drought-tolerant grapevine cultivar present worldwide, Syrah. To avoid the limitations of culture-dependent methods, amplicon sequencing with target primers for bacteria and fungi was applied to the same soil samples. The use of the DNeasy PowerSoil (Qiagen) extraction kit required further optimization with the use of lytic enzymes and heating steps to improve DNA yield and quality systematically across biological treatments. Target regions (16S rRNA and ITS genes) of our samples are being sequenced with Illumina technology. With bioinformatic pipelines, it will be possible to obtain a characterization of the bacterial and fungal diversity, structure and composition. Further, the microbial communities will be assessed for their functional activity, which remains an important metric considering the strong inter-kingdom interactions existing between plants and their associated microbiome. The results of this study will lay the basis for biotechnological applications: in combination with the establishment of a bacterial library, it will be possible to explore the possibility of testing synthetic microbial communities to support plant resistance to water scarcity.

Keywords: microbiome, metabarcoding, soil, vinegrape, syrah, global warming, crop sustainability

Procedia PDF Downloads 85

Authors: Nurhafizah Md. Disa, Nurhayati Binti Abdullah, Muhammad Rabie Bin Omar

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This research intends to identify the existing knowledge gap because of the lack of substantial studies to fabricate and characterize bio-graphene created from Oil Palm Shell (OPS) through the means of pre-treatment and slow pyrolysis. By fabricating bio-graphene through OPS, a novel material can be found to procure and used for graphene-based research. The characterization of produced bio-graphene is intended to possess a unique hexagonal graphene pattern and graphene properties in comparison to other previously fabricated graphene. The OPS will be fabricated by pre-treatment of zinc chloride (ZnCl₂) and iron (III) chloride (FeCl3), which then induced the bio-graphene thermally by slow pyrolysis. The pyrolizer's final temperature and resident time will be set at 550 °C, 5/min, and 1 hour respectively. Finally, the charred product will be washed with hydrochloric acid (HCL) to remove metal residue. The obtained bio-graphene will undergo different analyses to investigate the physicochemical properties of the two-dimensional layer of carbon atoms with sp2 hybridization hexagonal lattice structure. The analysis that will be taking place is Raman Spectroscopy (RAMAN), UV-visible spectroscopy (UV-VIS), Transmission Electron Microscopy (TEM), Scanning Electron Microscopy (SEM), and X-Ray Diffraction (XRD). In retrospect, RAMAN is used to analyze three key peaks found in graphene, namely D, G, and 2D peaks, which will evaluate the quality of the bio-graphene structure and the number of layers generated. To compare and strengthen graphene layer resolves, UV-VIS may be used to establish similar results of graphene layer from last layer analysis and also characterize the types of graphene procured. A clear physical image of graphene can be obtained by analyzation of TEM in order to study structural quality and layers condition and SEM in order to study the surface quality and repeating porosity pattern. Lastly, establishing the crystallinity of the produced bio-graphene, simultaneously as an oxygen contamination factor and thus pristineness of the graphene can be done by XRD. In the conclusion of this paper, this study is able to obtain bio-graphene through OPS as a novel material in pre-treatment by chloride ZnCl₂ and FeCl3 and slow pyrolization to provide a characterization analysis related to bio-graphene that will be beneficial for future graphene-related applications. The characterization should yield similar findings to previous papers as to confirm graphene quality.

Keywords: oil palm shell, bio-graphene, pre-treatment, slow pyrolysis

Procedia PDF Downloads 57

Authors: Furkan Ozkan, M. Selcuk Arslan, Hatice Mercan

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Electric vehicles are becoming increasingly popular asa sustainable alternative to traditional combustion engine vehicles. However, to fully realize the potential of EVs in reducing environmental impact and energy consumption, efficient control strategies are essential. This study explores the application of green wave control using model predictive control for electric vehicles, coupled with energy consumption modeling using neural networks. The use of MPC allows for real-time optimization of the vehicles’ energy consumption while considering dynamic traffic conditions. By leveraging neural networks for energy consumption modeling, the EV's performance can be further enhanced through accurate predictions and adaptive control. The integration of these advanced control and modeling techniques aims to maximize energy efficiency and range while navigating urban traffic scenarios. The findings of this research offer valuable insights into the potential of green wave control for electric vehicles and demonstrate the significance of integrating MPC and neural network modeling for optimizing energy consumption. This work contributes to the advancement of sustainable transportation systems and the widespread adoption of electric vehicles. To evaluate the effectiveness of the green wave control strategy in real-world urban environments, extensive simulations were conducted using a high-fidelity vehicle model and realistic traffic scenarios. The results indicate that the integration of model predictive control and energy consumption modeling with neural networks had a significant impact on the energy efficiency and range of electric vehicles. Through the use of MPC, the electric vehicle was able to adapt its speed and acceleration profile in realtime to optimize energy consumption while maintaining travel time objectives. The neural network-based energy consumption modeling provided accurate predictions, enabling the vehicle to anticipate and respond to variations in traffic flow, further enhancing energy efficiency and range. Furthermore, the study revealed that the green wave control strategy not only reduced energy consumption but also improved the overall driving experience by minimizing abrupt acceleration and deceleration, leading to a smoother and more comfortable ride for passengers. These results demonstrate the potential for green wave control to revolutionize urban transportation by enhancing the performance of electric vehicles and contributing to a more sustainable and efficient mobility ecosystem.

Keywords: electric vehicles, energy efficiency, green wave control, model predictive control, neural networks

Procedia PDF Downloads 20

Authors: Asli Tiktas, Huseyin Gunerhan, Arif Hepbasli

Abstract:

Solar energy, with its abundant and clean features, is one of the prominent renewable energy sources in multigeneration energy systems where various outputs, especially power generation, are produced together. In the literature, concentrated solar energy systems, which are an expensive technology, are mostly used in solar power plants where medium-high capacity production outputs are achieved. In addition, although different methods have been developed and proposed for solar energy-supported integrated power generation systems by different investigators, absorption technology, which is one of the key points of the present study, has been used extensively in cooling systems in these studies. Unlike these common uses mentioned in the literature, this study designs a system in which a flat plate solar collector (FPSC), Rankine cycle, absorption heat transformer (AHT), and cooling systems (ACS) are integrated. The system proposed within the scope of this study aims to produce medium-high-capacity electricity, heating, and cooling outputs using a technique different from the literature, with lower production costs than existing systems. With the proposed integrated system design, the average production costs based on electricity, heating, and cooling load production for similar scale systems are 5-10% of the average production costs of 0.685 USD/kWh, 0.247 USD/kWh, and 0.342 USD/kWh. In the proposed integrated system design, this will be achieved by increasing the outlet temperature of the AHT and FPSC system first, expanding the high-temperature steam coming out of the absorber of the AHT system in the turbine up to the condenser temperature of the ACS system, and next directly integrating it into the evaporator of this system and then completing the AHT cycle. Through this proposed system, heating and cooling will be carried out by completing the AHT and ACS cycles, respectively, while power generation will be provided because of the expansion of the turbine. Using only a single generator in the production of these three outputs together, the costs of additional boilers and the need for a heat source are also saved. In order to demonstrate that the system proposed in this study offers a more optimum solution, the techno-economic parameters obtained based on energy, exergy, economic, and environmental analysis were compared with the parameters of similar scale systems in the literature. The design parameters of the proposed system were determined through a parametric optimization study to exceed the maximum efficiency and effectiveness and reduce the production cost rate values of the compared systems.

Keywords: solar energy, absorption technology, Rankine cycle, multigeneration energy system

Procedia PDF Downloads 26

Authors: Saad Mohamed Elsaid, Nabil Anwar, Mahmoud Rushdi

Abstract:

One of the reasons for the intensive use of pesticides is to protect agricultural crops and orchards from pests or agricultural worms. The period of time that pesticides stay inside the soil is estimated at about (2) to (12) weeks. Perhaps the most important reason that led to groundwater pollution is the easy leakage of these harmful pesticides from the soil into the aquifers. This research aims to find the best ways to use traded activated charcoal with gold nitrate solution; for removing the deadly pesticides from the aqueous solution by adsorption phenomenon. The most used pesticides in Egypt were selected, such as Malathion, Methomyl Abamectin and, Thiamethoxam. Activated charcoal doped with gold ions was prepared by applying chemical and thermal treatments to activated charcoal using gold nitrate solution. Adsorption of studied pesticide onto activated carbon /Au was mainly by chemical adsorption, forming a complex with the gold metal immobilized on activated carbon surfaces. In addition, the gold atom was considered as a catalyst to cracking the pesticide molecule. Gold activated charcoal is a low cost material due to the use of very low concentrations of gold nitrate solution. its notice the great ability of activated charcoal in removing selected pesticides due to the presence of the positive charge of the gold ion, in addition to other active groups such as functional oxygen and lignin cellulose. The presence of pores of different sizes on the surface of activated charcoal is the driving force for the good adsorption efficiency for the removal of the pesticides under study The surface area of the prepared char as well as the active groups, were determined using infrared spectroscopy and scanning electron microscopy. Some factors affecting the ability of activated charcoal were applied in order to reach the highest adsorption capacity of activated charcoal, such as the weight of the charcoal, the concentration of the pesticide solution, the time of the experiment, and the pH. Experiments showed that the maximum limit revealed by the batch adsorption study for the adsorption of selected insecticides was in contact time (80) minutes at pH (7.70). These promising results were confirmed, and by establishing the practical application of the developed system, the effect of various operating factors with equilibrium, kinetic and thermodynamic studies is evident, using the Langmuir application on the effectiveness of the absorbent material with absorption capacities higher than most other adsorbents.

Keywords: waste water, pesticides pollution, adsorption, activated carbon

Procedia PDF Downloads 47