Search results for: optimization of steel

Authors: Wi Sung Yoo, Seung Woo Lee, Youn Kyoung Hur, Sung Hwan Kim

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Large-scale construction projects are continuously increasing, and the need for tools to monitor and evaluate the project success is emphasized. At the construction industry level, there are limitations in deriving performance evaluation factors that reflect the diversity of construction sites and systems that can objectively evaluate and manage performance. Additionally, there are difficulties in integrating structured and unstructured data generated at construction sites and deriving improvements. In this study, we propose the Key Performance Indicators (KPIs) to enable performance evaluation that reflects the increased diversity of construction sites and the unstructured data generated, and present a model for measuring performance by the derived indicators. The comprehensive performance of a unit construction site is assessed based on 6 areas (Time, Cost, Quality, Safety, Environment, Productivity) and 26 indicators. We collect performance indicator information from 30 construction sites that meet legal standards and have been successfully performed. And We apply data augmentation and optimization techniques into establishing measurement standards for each indicator. In other words, the KPI for construction site performance evaluation presented in this study provides standards for evaluating performance in six areas using institutional requirement data and document data. This can be expanded to establish a performance evaluation system considering the scale and type of construction project. Also, they are expected to be used as a comprehensive indicator of the construction industry and used as basic data for tracking competitiveness at the national level and establishing policies.

Keywords: key performance indicator, performance measurement, structured and unstructured data, data augmentation

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Authors: N. Boontian

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Biological conversion of biomass to methane has received increasing attention in recent years. Grasses have been explored for their potential anaerobic digestion to methane. In this review, extensive literature data have been tabulated and classified. The influences of several parameters on the potential of these feedstocks to produce methane are presented. Lignocellulosic biomass represents a mostly unused source for biogas and ethanol production. Many factors, including lignin content, crystallinity of cellulose, and particle size, limit the digestibility of the hemicellulose and cellulose present in the lignocellulosic biomass. Pretreatments have used to improve the digestibility of the lignocellulosic biomass. Each pretreatment has its own effects on cellulose, hemicellulose and lignin, the three main components of lignocellulosic biomass. Solid-state anaerobic digestion (SS-AD) generally occurs at solid concentrations higher than 15%. In contrast, liquid anaerobic digestion (AD) handles feedstocks with solid concentrations between 0.5% and 15%. Animal manure, sewage sludge, and food waste are generally treated by liquid AD, while organic fractions of municipal solid waste (OFMSW) and lignocellulosic biomass such as crop residues and energy crops can be processed through SS-AD. An increase in operating temperature can improve both the biogas yield and the production efficiency, other practices such as using AD digestate or leachate as an inoculant or decreasing the solid content may increase biogas yield but have negative impact on production efficiency. Focus is placed on substrate pretreatment in anaerobic digestion (AD) as a means of increasing biogas yields using today’s diversified substrate sources.

Keywords: anaerobic digestion, lignocellulosic biomass, methane production, optimization, pretreatment

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Authors: Nicolas Plamondon, Stuart Atkinson, Shuzi Zhou

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The insurance industry is usually not the first topic one has in mind when thinking about applications of data science. However, the use of data science in the finance and insurance industry is growing quickly for several reasons, including an abundance of reliable customer data, ferocious competition requiring more accurate pricing, etc. Among the top use cases of data science, we find pricing optimization, customer segmentation, customer risk assessment, fraud detection, marketing, and triage analytics. The objective of this paper is to present an application of the generalized additive model (GAM) on a commercial automobile insurance product: an individually rated commercial automobile. These are vehicles used for commercial purposes, but for which there is not enough volume to apply pricing to several vehicles at the same time. The GAM model was selected as an improvement over GLM for its ease of use and its wide range of applications. The model was trained using the largest split of the data to determine model parameters. The remaining part of the data was used as testing data to verify the quality of the modeling activity. We used the Gini coefficient to evaluate the performance of the model. For long-term monitoring, commonly used metrics such as RMSE and MAE will be used. Another topic of interest in the insurance industry is to process of producing the model. We will discuss at a high level the interactions between the different teams with an insurance company that needs to work together to produce a model and then monitor the performance of the model over time. Moreover, we will discuss the regulations in place in the insurance industry. Finally, we will discuss the maintenance of the model and the fact that new data does not come constantly and that some metrics can take a long time to become meaningful.

Keywords: insurance, data science, modeling, monitoring, regulation, processes

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Authors: Annalisa Gaetani, Anna Nora Tassetti, Gianna Fabi

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The hydroacoustic technology is an efficient tool to study the sea environment: the most recent advancement in artificial habitat mapping involves acoustic systems to investigate fish abundance, distribution and behavior in specific areas. Along with a detailed high-coverage bathymetric mapping of the seabed, the high-frequency Multibeam Echosounder (MBES) offers the potential of detecting fine-scale distribution of fish aggregation, combining its ability to detect at the same time the seafloor and the water column. Surveying fish schools distribution around artificial structures, MBES allows to evaluate how their presence modifies the biological natural habitat overtime in terms of fish attraction and abundance. In the last years, artificial habitat mapping experiences have been carried out by CNR-ISMAR in the Adriatic sea: fish assemblages aggregating at offshore gas platforms and artificial reefs have been systematically monitored employing different kinds of methodologies. This work focuses on two case studies: a gas extraction platform founded at 80 meters of depth in the central Adriatic sea, 30 miles far from the coast of Ancona, and the concrete and steel artificial reef of Senigallia, deployed by CNR-ISMAR about 1.2 miles offshore at a depth of 11.2 m . Relating the MBES data (metrical dimensions of fish assemblages, shape, depth, density etc.) with the results coming from other methodologies, such as experimental fishing surveys and underwater video camera, it has been possible to investigate the biological assemblage attracted by artificial structures hypothesizing which species populate the investigated area and their spatial dislocation from these artificial structures. Processing MBES bathymetric and water column data, 3D virtual scenes of the artificial habitats have been created, receiving an intuitive-looking depiction of their state and allowing overtime to evaluate their change in terms of dimensional characteristics and depth fish schools’ disposition. These MBES surveys play a leading part in the general multi-year programs carried out by CNR-ISMAR with the aim to assess potential biological changes linked to human activities on.

Keywords: artificial habitat mapping, fish assemblages, hydroacustic technology, multibeam echosounder

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Authors: Yibeltal Chanie Manie, Zebider Asire Munyelet

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5G and 6G technology offers enhanced quality of service with high data transmission rates, which necessitates the implementation of the Internet of Things (IoT) in 5G/6G architecture. In this paper, we proposed the integration of free space optical communication (FSO) with fiber sensor networks for IoT applications. Recently, free-space optical communications (FSO) are gaining popularity as an effective alternative technology to the limited availability of radio frequency (RF) spectrum. FSO is gaining popularity due to flexibility, high achievable optical bandwidth, and low power consumption in several applications of communications, such as disaster recovery, last-mile connectivity, drones, surveillance, backhaul, and satellite communications. Hence, high-speed FSO is an optimal choice for wireless networks to satisfy the full potential of 5G/6G technology, offering 100 Gbit/s or more speed in IoT applications. Moreover, machine learning must be integrated into the design, planning, and optimization of future optical wireless communication networks in order to actualize this vision of intelligent processing and operation. In addition, fiber sensors are important to achieve real-time, accurate, and smart monitoring in IoT applications. Moreover, we proposed deep learning techniques to estimate the strain changes and peak wavelength of multiple Fiber Bragg grating (FBG) sensors using only the spectrum of FBGs obtained from the real experiment.

Keywords: optical sensor, artificial Intelligence, Internet of Things, free-space optics

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Authors: Ndidi F. Amulu, Patrick E. Amulu, Gordian O. Mbah, Callistus N. Ude

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Comparative analysis of the properties of melon seed, coconut fruit and their oil yield were evaluated in this work using standard analytical technique AOAC. The results of the analysis carried out revealed that the moisture contents of the samples studied are 11.15% (melon) and 7.59% (coconut). The crude lipid content are 46.10% (melon) and 55.15% (coconut).The treatment combinations used (leaching time, leaching temperature and solute: solvent ratio) showed significant difference (p < 0.05) in yield between the samples, with melon oil seed flour having a higher percentage range of oil yield (41.30 – 52.90%) and coconut (36.25 – 49.83%). The physical characterization of the extracted oil was also carried out. The values gotten for refractive index are 1.487 (melon seed oil) and 1.361 (coconut oil) and viscosities are 0.008 (melon seed oil) and 0.002 (coconut oil). The chemical analysis of the extracted oils shows acid value of 1.00mg NaOH/g oil (melon oil), 10.050mg NaOH/g oil (coconut oil) and saponification value of 187.00mg/KOH (melon oil) and 183.26mg/KOH (coconut oil). The iodine value of the melon oil gave 75.00mg I2/g and 81.00mg I2/g for coconut oil. A standard statistical package Minitab version 16.0 was used in the regression analysis and analysis of variance (ANOVA). The statistical software mentioned above was also used to optimize the leaching process. Both samples gave high oil yield at the same optimal conditions. The optimal conditions to obtain highest oil yield ≥ 52% (melon seed) and ≥ 48% (coconut seed) are solute - solvent ratio of 40g/ml, leaching time of 2hours and leaching temperature of 50oC. The two samples studied have potential of yielding oil with melon seed giving the higher yield.

Keywords: Coconut, Melon, Optimization, Processing

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Authors: Norica Godja, Andreas Schindel, Luka Payrits, Zsolt Pasztor, Bálint Hegedüs, Petr Homola, Jan Horňas, Jiří Běhal, Roman Ruzek, Martin Holzleitner, Sascha Senck

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In order to reduce fuel consumption and CO₂ emissions in the aviation sector, innovative solutions are being sought to reduce the weight of aircraft, including additive manufacturing (AM). Of particular importance are the excellent mechanical properties that are required for aircraft structures. Ti6Al4V alloys, with their high mechanical properties in relation to weight, can reduce the weight of aircraft structures compared to structures made of steel and aluminium. Currently, conventional processes such as casting and CNC machining are used to obtain the desired structures, resulting in high raw material removal, which in turn leads to higher costs and impacts the environment. Additive manufacturing (AM) offers advantages in terms of weight, lead time, design, and functionality and enables the realisation of alternative geometric shapes with high mechanical properties. However, there are currently technological shortcomings that have led to AM not being approved for structural components with high safety requirements. An assessment of damage tolerance for AM parts is required, and quality control needs to be improved. Pores and other defects cannot be completely avoided at present, but they should be kept to a minimum during manufacture. The mechanical properties of the manufactured parts can be further improved by various treatments. The influence of different treatment methods (heat treatment, CNC milling, electropolishing, chemical polishing) and operating parameters were investigated by scanning electron microscopy with energy dispersive X-ray spectroscopy (SEM/EDX), X-ray diffraction (XRD), electron backscatter diffraction (EBSD) and measurements with a focused ion beam (FIB), taking into account surface roughness, possible anomalies in the chemical composition of the surface and possible cracks. The results of the characterisation of the constructed and treated samples are discussed and presented in this paper. These results were generated within the framework of the 3TANIUM project, which is financed by EU with the contract number 101007830.

Keywords: Ti6Al4V alloys, laser powder bed fusion, damage tolerance, heat treatment, electropolishing, potential cracking

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Authors: Swapnila V. Shinde, Hemant P. Joshi, Sumit R. Dhas, Dhananjaysingh B. Rajput

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The objective of the present study is to develop hydro-dynamically balanced system for atenolol, β-blocker as a single unit floating tablet. Atenolol shows pH dependent solubility resulting into a bioavailability of 36%. Thus, site specific oral controlled release floating drug delivery system was developed. Formulation includes novice use of rate controlling polymer such as locust bean gum (LBG) in combination of HPMC K4M and gas generating agent sodium bicarbonate. Tablet was prepared by direct compression method and evaluated for physico-mechanical properties. The statistical method was utilized to optimize the effect of independent variables, namely amount of HPMC K4M, LBG and three dependent responses such as cumulative drug release, floating lag time, floating time. Graphical and mathematical analysis of the results allowed the identification and quantification of the formulation variables influencing the selected responses. To study the gastrointestinal transit of the optimized gastro-retentive formulation, in vivo gamma scintigraphy was carried out in six healthy rabbits, after radio labeling the formulation with 99mTc. The transit profiles demonstrated that the dosage form was retained in the stomach for more than 5 hrs. The study signifies the potential of the developed system for stomach targeted delivery of atenolol with improved bioavailability.

Keywords: floating tablet, factorial design, gamma scintigraphy, antihypertensive model drug, HPMC, locust bean gum

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Authors: W. Nootcharin, S. Sujittra, K. Mayuso, K. Kornphimol, M. Rawiwan

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Silver has distinct antibacterial properties and has been used as a component of commercial products with many applications. An increasing number of commercial products cause risks of silver effects for human and environment such as the symptoms of Argyria and the release of silver to the environment. Therefore, the detection of silver in the aquatic environment is important. The colorimetric chemosensor is designed by the basic of ligand interactions with a metal ion, leading to the change of signals for the naked-eyes which are very useful method to this application. Dithizone ligand is considered as one of the effective chelating reagents for metal ions due to its high selectivity and sensitivity of a photochromic reaction for silver as well as the linear backbone of dithizone affords the rotation of various isomeric forms. The present study is focused on the conformation and interaction of silver ion and silver nanoparticles (AgNPs) with dithizone using density functional theory (DFT). The interaction parameters were determined in term of binding energy of complexes and the geometry optimization, frequency of the structures and calculation of binding energies using density functional approaches B3LYP and the 6-31G(d,p) basis set. Moreover, the interaction of silver–dithizone complexes was supported by UV–Vis spectroscopy, FT-IR spectrum that was simulated by using B3LYP/6-31G(d,p) and 1H NMR spectra calculation using B3LYP/6-311+G(2d,p) method compared with the experimental data. The results showed the ion exchange interaction between hydrogen of dithizone and silver atom, with minimized binding energies of silver–dithizone interaction. However, the result of AgNPs in the form of complexes with dithizone. Moreover, the AgNPs-dithizone complexes were confirmed by using transmission electron microscope (TEM). Therefore, the results can be the useful information for determination of complex interaction using the analysis of computer simulations.

Keywords: silver nanoparticles, dithizone, DFT, NMR

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Authors: Ashok V. Sutagundar, Sunilkumar S. Manvi

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Energy, delay and bandwidth are the prime issues of wireless sensor network (WSN). Energy usage optimization and efficient bandwidth utilization are important issues in WSN. Event triggered data aggregation facilitates such optimal tasks for event affected area in WSN. Reliable delivery of the critical information to sink node is also a major challenge of WSN. To tackle these issues, we propose an event driven dynamic clustering and data aggregation scheme for WSN that enhances the life time of the network by minimizing redundant data transmission. The proposed scheme operates as follows: (1) Whenever the event is triggered, event triggered node selects the cluster head. (2) Cluster head gathers data from sensor nodes within the cluster. (3) Cluster head node identifies and classifies the events out of the collected data using Bayesian classifier. (4) Aggregation of data is done using statistical method. (5) Cluster head discovers the paths to the sink node using residual energy, path distance and bandwidth. (6) If the aggregated data is critical, cluster head sends the aggregated data over the multipath for reliable data communication. (7) Otherwise aggregated data is transmitted towards sink node over the single path which is having the more bandwidth and residual energy. The performance of the scheme is validated for various WSN scenarios to evaluate the effectiveness of the proposed approach in terms of aggregation time, cluster formation time and energy consumed for aggregation.

Keywords: wireless sensor network, dynamic clustering, data aggregation, wireless communication

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Authors: Sabariah Mohd Yusoff, Qamaruddin Adzeem Muhamad Murad

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This study investigates the impact of car seat design on driver response time, addressing a critical gap in understanding how ergonomic features influence both performance and safety. Controlled driving experiments were conducted with fourteen participants (11 male, 3 female) across three locations chosen for their varying traffic conditions to account for differences in driver alertness. Participants interacted with various seat designs while performing driving tasks, and objective metrics such as braking and steering response times were meticulously recorded. Advanced statistical methods, including regression analysis and t-tests, were employed to identify design factors that significantly affect driver response times. Subjective feedback was gathered through detailed questionnaires—focused on driving experience and knowledge of response time—and in-depth interviews. This qualitative data was analyzed thematically to provide insights into driver comfort and usability preferences. The study aims to identify key seat design features that impact driver response time and to gain a deeper understanding of driver preferences for comfort and usability. The findings are expected to inform evidence-based guidelines for optimizing car seat design, ultimately enhancing driver performance and safety. The research offers valuable implications for automotive manufacturers and designers, contributing to the development of seats that improve driver response time and overall driving safety.

Keywords: car seat design, driver response time, cognitive driving, ergonomics optimization

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Authors: Ana Pego

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Environmental technologies were developed for decades. Clean technologies emerged a few years ago. In these perspectives, the use of cleantech technologies has become very important due the fact of new era of environmental feats. As such, the market itself has become more competitive, more collaborative towards a better use of clean technologies. This paper shows the importance of clean technologies in offshore energy sector in Portuguese market, its localization and its impact on economy. Clean technologies are directly related with renewable cluster and concomitant with economic and social resource optimization criteria, geographic aspects, climate change and soil features. Cleantech is related with regional development, socio-technical transitions in organisations. There are an economical and social combinations which allow specialisation of regions in activities, higher employment, reduce of energy costs, local knowledge spillover and, business collaboration and competitiveness. The methodology used will be quantitative (IO matrix for Portugal 2013) and qualitative (questionnaires to stakeholders). The mix of both methodologies will confirm whether the use of technologies will allow a positive impact on economic and social variables used on this model. It is expected a positive impact on Portuguese economy both in investment and employment taking in account the localization of offshore renewable activities. This means that the importance of offshore renewable investment in Portugal has a few points which should be pointed out: the increase of specialised employment, localization of specific activities in territory, and increase of value added in certain regions. The conclusion will allow researchers and organisation to compare the Portuguese model to other European regions in order to a better use of natural and human resources.

Keywords: cleantech, economic impact, localisation, territory dynamics

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Authors: Lianxue Shi

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Urban waterfront rail transit stations exert a dual impact on both the waterfront and the transit station, resulting in a concentration of development elements in the surrounding space. In order to more effectively develop the space around the station, this study focuses on the perspective of the integration of station, city, and people. Taking Chongqing as an example, based on the Arc GIS platform, it explores the vitality of the site from the three dimensions of crowd activity heat, space facilities heat, and spatial accessibility. It conducts a comprehensive evaluation and interpretation of the vitality surrounding the waterfront rail transit station area in Chongqing. The study found that (1) the spatial vitality in the vicinity of waterfront rail transit stations is correlated with the waterfront's functional zoning and the intensity of development. Stations situated in waterfront residential and public spaces are more likely to experience a convergence of people, whereas those located in waterfront industrial areas exhibit lower levels of vitality. (2) Effective transportation accessibility plays a pivotal role in maintaining a steady flow of passengers and facilitating their movement. However, the three-dimensionality of urban space in mountainous regions is a notable challenge, leading to some stations experiencing limited accessibility. This underscores the importance of enhancing the optimization of walking space, particularly the access routes from the station to the waterfront area. (3) The density of spatial facilities around waterfront stations in old urban areas lags behind the population's needs, indicating a need to strengthen the allocation of relevant land and resources in these areas.

Keywords: rail transit station, waterfront, influence area, spatial vitality, urban vitality

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Authors: Yen-Luan Chen

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Maintenance has a great impact on the capacity of production and on the quality of the products, and therefore, it deserves continuous improvement. Maintenance procedure done before a failure is called preventive maintenance (PM). Sequential PM, which specifies that a system should be maintained at a sequence of intervals with unequal lengths, is one of the commonly used PM policies. This article proposes a generalized sequential PM policy for a system subject to shocks with imperfect maintenance and random working time. The shocks arrive according to a non-homogeneous Poisson process (NHPP) with varied intensity function in each maintenance interval. As a shock occurs, the system suffers two types of failures with number-dependent probabilities: type-I (minor) failure, which is rectified by a minimal repair, and type-II (catastrophic) failure, which is removed by a corrective maintenance (CM). The imperfect maintenance is carried out to improve the system failure characteristic due to the altered shock process. The sequential preventive maintenance-last (PML) policy is defined as that the system is maintained before any CM occurs at a planned time Ti or at the completion of a working time in the i-th maintenance interval, whichever occurs last. At the N-th maintenance, the system is replaced rather than maintained. This article first takes up the sequential PML policy with random working time and imperfect maintenance in reliability engineering. The optimal preventive maintenance schedule that minimizes the mean cost rate of a replacement cycle is derived analytically and determined in terms of its existence and uniqueness. The proposed models provide a general framework for analyzing the maintenance policies in reliability theory.

Keywords: optimization, preventive maintenance, random working time, minimal repair, replacement, reliability

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Authors: Bita Payami-Shabestari, Dariush Eslami

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The purpose of this paper is to develop a multi-product economic production quantity model under vendor management inventory policy and restrictions including limited warehouse space, budget, and number of orders, average shortage time and maximum permissible shortage. Since the “costs” cannot be predicted with certainty, it is assumed that data behave under uncertain environment. The problem is first formulated into the framework of a bi-objective of multi-product economic production quantity model. Then, the problem is solved with three multi-objective decision-making (MODM) methods. Then following this, three methods had been compared on information on the optimal value of the two objective functions and the central processing unit (CPU) time with the statistical analysis method and the multi-attribute decision-making (MADM). The results are compared with statistical analysis method and the MADM. The results of the study demonstrate that augmented-constraint in terms of optimal value of the two objective functions and the CPU time perform better than global criteria, and goal programming. Sensitivity analysis is done to illustrate the effect of parameter variations on the optimal solution. The contribution of this research is the use of random costs data in developing a multi-product economic production quantity model under vendor management inventory policy with several constraints.

Keywords: economic production quantity, random cost, supply chain management, vendor-managed inventory

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Authors: Hyeonkyeong Yang, Minseok Son, Taekbeom Yoo, Woojin Park

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Human error is the most salient contributing factor to railway accidents. To reduce the frequency of human errors, many researchers and train designers have adopted ergonomic design principles for designing display-control layout in rail cab. There exist a number of approaches for designing the display control layout based on optimization methods. However, the ergonomically optimized layout design may not be the best design for train drivers, since the drivers have their own mental models based on their experiences. Consequently, the drivers may prefer the existing display-control layout design over the optimal design, and even show better driving performance using the existing design compared to that using the optimal design. Thus, in addition to ergonomic design principles, train drivers’ mental models also need to be considered for designing display-control layout in rail cab. This paper developed an ergonomic assessment system of display-control layout design, and an interactive layout design system that can generate design alternatives and calculate ergonomic assessment score in real-time. The design alternatives generated from the interactive layout design system may not include the optimal design from the ergonomics point of view. However, the system’s strength is that it considers train drivers’ mental models, which can help generate alternatives that are more friendly and easier to use for train drivers. Also, with the developed system, non-experts in ergonomics, such as train drivers, can refine the design alternatives and improve ergonomic assessment score in real-time.

Keywords: display-control layout design, interactive layout design system, mental model, train drivers

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Authors: Gaurav Kumar Sinha

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The oil refining industry, significant in its energy consumption and carbon emissions, faces increasing pressure to reduce its environmental footprint. This article explores the application of energy efficiency and sustainability analytics as crucial tools for reducing carbon emissions in oil refineries. Through a comprehensive review of current practices and technologies, this study highlights innovative analytical approaches that can significantly enhance energy efficiency. We focus on the integration of advanced data analytics, including machine learning and predictive modeling, to optimize process controls and energy use. These technologies are examined for their potential to not only lower energy consumption but also reduce greenhouse gas emissions. Additionally, the article discusses the implementation of sustainability analytics to monitor and improve environmental performance across various operational facets of oil refineries. We explore case studies where predictive analytics have successfully identified opportunities for reducing energy use and emissions, providing a template for industry-wide application. The challenges associated with deploying these analytics, such as data integration and the need for skilled personnel, are also addressed. The paper concludes with strategic recommendations for oil refineries aiming to enhance their sustainability practices through the adoption of targeted analytics. By implementing these measures, refineries can achieve significant reductions in carbon emissions, aligning with global environmental goals and regulatory requirements.

Keywords: energy efficiency, sustainability analytics, carbon emissions, oil refineries, data analytics, machine learning, predictive modeling, process optimization, greenhouse gas reduction, environmental performance

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Authors: Jingyi Li, Laurence Stamford, Alejandro Gallego-Schmid

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Renewable electricity has become an indispensable contributor to achieving net-zero by the mid-century to tackle climate change. Unlike solar, wind, or hydro, geothermal was stagnant in its electricity production development for decades. However, with the significant breakthrough made in recent years, especially the implementation of enhanced geothermal systems (EGS) in various regions globally, geothermal electricity could play a pivotal role in alleviating greenhouse gas emissions. Life cycle assessment has been applied to analyze specific geothermal power generation technologies, which proposed suggestions to optimize its environmental performance. For instance, selecting a high heat gradient region enables a higher flow rate from the production well and extends the technical lifespan. Although such process-level improvements have been made, the significance of geothermal power generation technologies so far has not explicitly displayed its competitiveness on a broader horizon. Therefore, this review-based study integrates a circular economy framework into life cycle assessment, clarifying the underlying added values for geothermal power plants to complete the sustainability profile. The derived results have provided an enlarged platform to discuss geothermal power generation technologies: (i) recover the heat and electricity from the process to reduce the fossil fuel requirements; (ii) recycle the construction materials, such as copper, steel, and aluminum for future projects; (iii) extract the lithium ions from geothermal brine and make geothermal reservoir become a potential supplier of the lithium battery industry; (iv) repurpose the abandoned oil and gas wells to build geothermal power plants; (v) integrate geothermal energy with other available renewable energies (e.g., solar and wind) to provide heat and electricity as a hybrid system at different weather; (vi) rethink the fluids used in stimulation process (EGS only), replace water with CO2 to achieve negative emissions from the system. These results provided a new perspective to the researchers, investors, and policymakers to rethink the role of geothermal in the energy supply network.

Keywords: climate, renewable energy, R strategies, sustainability

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Authors: Marta Błażkiewicz-Mazurek, Adam Konefał

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The project can be divided into three main parts: i. modeling the Cf-252 neutron source and conducting an experiment to verify the correctness of the obtained results, ii. design of the BNCT system infrastructure, iii. analysis of the results from the logical detector. Modeling of the Cf-252 source included designing the shape and size of the source as well as the energy and spatial distribution of emitted neutrons. Two options were considered: a point source and a cylindrical spatial source. The energy distribution corresponded to various spectra taken from specialized literature. Directionally isotropic neutron emission was simulated. The simulation results were compared with experimental values determined using the activation detector method using indium foils and cadmium shields. The relative fluence rate of thermal and resonance neutrons was compared in the chosen places in the vicinity of the source. The second part of the project related to the modeling of the BNCT infrastructure consisted of developing a simulation program taking into account all the essential components of this system. Materials with moderating, absorbing, and backscattering properties of neutrons were adopted into the project. Additionally, a gamma radiation filter was introduced into the beam output system. The analysis of the simulation results obtained using a logical detector located at the beam exit from the BNCT infrastructure included neutron energy and their spatial distribution. Optimization of the system involved changing the size and materials of the system to obtain a suitable collimated beam of thermal neutrons.

Keywords: BNCT, Monte Carlo, neutrons, simulation, modeling

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Authors: Amaia Martinez Martinez, Martin Turek, Carlos Ventura, Jay Drew

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This study aims to assess the seismic performance of arch and dome structural systems made from easy to assemble precast blocks of recycled concrete. These systems have been developed by Lock Block Ltd. Company from Vancouver, Canada, as an extension of their currently used retaining wall system. The characterization of the seismic behavior of these structures is performed by a combination of experimental static and dynamic testing, and analytical modeling. For the experimental testing, several tilt tests, as well as a program of shake table testing were undertaken using small scale arch models. A suite of earthquakes with different characteristics from important past events are chosen and scaled properly for the dynamic testing. Shake table testing applying the ground motions in just one direction (in the weak direction of the arch) and in the three directions were conducted and compared. The models were tested with increasing intensity until collapse occurred; which determines the failure level for each earthquake. Since the failure intensity varied with type of earthquake, a sensitivity analysis of the different parameters was performed, being impulses the dominant factor. For all cases, the arches exhibited the typical four-hinge failure mechanism, which was also shown in the analytical model. Experimental testing was also performed reinforcing the arches using a steel band over the structures anchored at both ends of the arch. The models were tested with different pretension levels. The bands were instrumented with strain gauges to measure the force produced by the shaking. These forces were used to develop engineering guidelines for the design of the reinforcement needed for these systems. In addition, an analytical discrete element model was created using 3DEC software. The blocks were designed as rigid blocks, assigning all the properties to the joints including also the contribution of the interlocking shear key between blocks. The model is calibrated to the experimental static tests and validated with the obtained results from the dynamic tests. Then the model can be used to scale up the results to the full scale structure and expanding it to different configurations and boundary conditions.

Keywords: arch, discrete element model, seismic assessment, shake-table testing

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Authors: Umme Hani, Mohammed Rahmatulla, Mohammed Ghazwani, Ali Alqahtani, Yahya Alhamhoom

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Background and introduction: Neratinib is a potent anticancer drug used for the treatment of breast cancer. It is poorly soluble at higher pH, which tends to minimize the therapeutic effects in the lower gastrointestinal tract (GIT) leading to poor bioavailability. An attempt has been made to prepare and develop a gastro-retentive system of Neratinib to improve the drug bioavailability in the GIT by enhancing the gastric retention time. Materials and methods: In the present study a three-factor at two-level (23) factorial design based optimization was used to inspect the effects of three independent variables (factors) such as sodium alginate (A), sodium bicarbonate (B) and sodium citrate (C) on the dependent variables like in vitro gelation, in vitro floating, water uptake and percentage drug release. Results: All the formulations showed pH in the range 6.7 ±0.25 to 7.4 ±0.24, percentage drug content was observed to be 96.3±0.27 to 99.5 ±0.28%, in vitro gelation observed as gelation immediate remains for an extended period. Percentage of water uptake was in the range between 9.01±0.15 to 31.01±0.25%, floating lag time was estimated form 7±0.39 to 57±0.36 sec. F4 and F5 showed floating even after 12hrs. All formulations showed a release of around 90% drug release within 12hr. It was observed that the selected independent variables affect the dependent variables. Conclusion: The developed system may be a promising and alternative approach to augment gastric retention of drugs and enhances the therapeutic efficacy of the drug.

Keywords: neratinib, 2³ factorial design, sodium alginate, floating, in situ gelling system

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Authors: Shahbaz Abbas, Lin Han Chiang Hsieh

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The significant population growth and climate change issues have contributed to the natural resources depletion and their sustainability in the future. Manufacturing industries have a substantial impact on every country’s economy, but the sustainability of the industrial resources is challenging, and the policymakers have been developing the possible solutions to manage the sustainability of industrial resources such as raw material, energy, water, and industrial supply chain. In order to address these challenges, nexus approach is one of the optimization and modelling techniques in the recent sustainable environmental research. The interactions between the nexus components acknowledge that all components are dependent upon each other, and they are interrelated; therefore, their sustainability is also associated with each other. In addition, the nexus concept does not only provide the resources sustainability but also environmental sustainability can be achieved through nexus approach by utilizing the industrial waste as a resource for the industrial processes. Based on energy-water nexus, this study has developed a resource-energy-water for the sugar industry to understand the interactions between sugarcane, energy, and water towards the sustainable sugar industry. In particular, the focus of the research is the Taiwanese sugar industry; however, the same approach can be adapted worldwide to optimize the sustainability of sugar industries. It has been concluded that there are significant interactions between sugarcane, energy consumption, and water consumption in the sugar industry to manage the scarcity of resources in the future. The interactions between sugarcane and energy also deliver a mechanism to reuse the sugar industrial waste as a source of energy, consequently validating industrial and environmental sustainability. The desired outcomes from the nexus can be achieved with the modifications in the policy and regulations of Taiwanese industrial sector.

Keywords: energy-water nexus, environmental sustainability, industrial sustainability, natural resource management

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Authors: R. O. Osaseri, A. R. Usiobaifo

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The power transformer which is responsible for the voltage transformation is of great relevance in the power system and oil-immerse transformer is widely used all over the world. A prompt and proper maintenance of the transformer is of utmost importance. The dissolved gasses content in power transformer, oil is of enormous importance in detecting incipient fault of the transformer. There is a need for accurate prediction of the incipient fault in transformer oil in order to facilitate the prompt maintenance and reducing the cost and error minimization. Study on fault prediction and diagnostic has been the center of many researchers and many previous works have been reported on the use of artificial intelligence to predict incipient failure of transformer faults. In this study machine learning technique was employed by using gradient decent algorithms and Support Vector Machine (SVM) in predicting incipient fault diagnosis of transformer. The method focuses on creating a system that improves its performance on previous result and historical data. The system design approach is basically in two phases; training and testing phase. The gradient decent algorithm is trained with a training dataset while the learned algorithm is applied to a set of new data. This two dataset is used to prove the accuracy of the proposed model. In this study a transformer fault diagnostic model based on Support Vector Machine (SVM) and gradient decent algorithms has been presented with a satisfactory diagnostic capability with high percentage in predicting incipient failure of transformer faults than existing diagnostic methods.

Keywords: diagnostic model, gradient decent, machine learning, support vector machine (SVM), transformer fault

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Authors: Idris Garba, Aisha Rabiu Abdullahi, Mansur Yahuza, Akintade Dare

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Background: CT urography (CTU) is efficient radiological examination for the evaluation of the urinary system disorders. However, patients are exposed to a significant radiation dose which is in a way associated with increased cancer risks. Objectives: To determine Computed Tomography Dose Index following CTU, and to evaluate organs equivalent doses. Materials and Methods: A prospective cohort study was carried at a tertiary institution located in Kano northwestern. Ethical clearance was sought and obtained from the research ethics board of the institution. Demographic, scan parameters and CT radiation dose data were obtained from patients that had CTU procedure. Effective dose, organ equivalent doses, and cancer risks were estimated using SPSS statistical software version 16 and CT dose calculator software. Result: A total of 56 patients were included in the study, consisting of 29 males and 27 females. The common indication for CTU examination was found to be renal cyst seen commonly among young adults (15-44yrs). CT radiation dose values in DLP, CTDI and effective dose for CTU were 2320 mGy cm, CTDIw 9.67 mGy and 35.04 mSv respectively. The probability of cancer risks was estimated to be 600 per a million CTU examinations. Conclusion: In this study, the radiation dose for CTU is considered significantly high, with increase in cancer risks probability. Wide radiation dose variations between patient doses suggest that optimization is not fulfilled yet. Patient radiation dose estimate should be taken into consideration when imaging protocols are established for CT urography.

Keywords: CT urography, cancer risks, effective dose, radiation exposure

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Authors: Eric Mxolisi Mkhondo

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Geometrical deviations and interaction of mechanical parts influences the performance of miniature systems.These deviations tend to cause costly problems during assembly due to imperfections of components, which are invisible to a naked eye.They also tend to cause unsatisfactory performance during operation due to deformation cause by environmental conditions.One of the effective tools to manage the deviations and interaction of parts in the system is tolerance analysis.This is a quantitative tool for predicting the tolerance variations which are defined during the design process.Traditional tolerance analysis assumes that the assembly is static and the deviations come from the manufacturing discrepancies, overlooking the functionality of the whole system and deformation of parts due to effect of environmental conditions. This paper presents an integrated tolerance analysis approach for miniature system in operation.In this approach, a computer-aided design (CAD) model is developed from system’s specification.The CAD model is then used to specify the geometrical and dimensional tolerance limits (upper and lower limits) that vary component’s geometries and sizes while conforming to functional requirements.Worst-case tolerances are analyzed to determine the influenced of dimensional changes due to effects of operating temperatures.The method is used to evaluate the nominal conditions, and worse case conditions in maximum and minimum dimensions of assembled components.These three conditions will be evaluated under specific operating temperatures (-40°C,-18°C, 4°C, 26°C, 48°C, and 70°C). A case study on the mechanism of a zoom lens system is used to illustrate the effectiveness of the methodology.

Keywords: geometric dimensioning, tolerance analysis, worst-case analysis, zoom lens mechanism

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Authors: L. A. Bosnea, T. Moschakis, C. Biliaderis

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Two probiotic strains of Lactobacillus paracasei subsp. paracasei (E6) and Lactobacillus paraplantarum (B1), isolated from traditional Greek dairy products, were microencapsulated by complex coacervation using whey protein isolate (WPI, 3% w/v) and gum arabic (GA, 3% w/v) solutions mixed at different polymer ratio (1:1, 2:1 and 4:1). The effect of total biopolymer concentration on cell viability was assessed using WPI and GA solutions of 1, 3 and 6% w/v at a constant ratio of 2:1. Also, several parameters were examined for optimization of the microcapsule formation, such as inoculum concentration and the effect of ionic strength. The viability of the bacterial cells during heat treatment and under simulated gut conditions was also evaluated. Among the different WPI/GA weight ratios tested (1:1, 2:1, and 4:1), the highest survival rate was observed for the coacervate structures made with the ratio of 2:1. The protection efficiency at low pH values is influenced by both concentration and the ratio of the added biopolymers. Moreover, the inoculum concentration seems to affect the efficiency of microcapsules to entrap the bacterial cells since an optimum level was noted at less than 8 log cfu/ml. Generally, entrapment of lactobacilli in the complex coacervate structure enhanced the viability of the microorganisms when exposed to a low pH environment (pH 2.0). Both encapsulated strains retained high viability in simulated gastric juice (>73%), especially in comparison with non-encapsulated (free) cells (<19%). The encapsulated lactobacilli also exhibited enhanced viability after 10–30 min of heat treatment (65oC) as well as at different NaCl concentrations (pH 4.0). Overall, the results of this study suggest that complex coacervation with WPI/GA has a potential to deliver live probiotics in low pH food systems and fermented dairy products; the complexes can dissolve at pH 7.0 (gut environment), releasing the microbial cells.

Keywords: probiotic, complex coacervation, whey, encapsulation

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Authors: R. F. Vieira, S. A. Figueiredo, O. M. Freitas, V. F. Domingues, C. Delerue-Matos

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The presence of sulphur compounds like hydrogen sulphide and mercaptans is one of the reasons for waste-water treatment and waste management being associated with odour emissions. In this context having a quantifying method for these compounds helps in the optimization of treatment with the goal of their elimination, namely biofiltration processes. The aim of this study was the development of a method for quantification of odorous gases in waste treatment plants air samples. A method based on head space solid phase microextraction (HS-SPME) coupled with gas chromatography - flame photometric detector (GC-FPD) was used to analyse H2S and Metil Mercaptan (MM). The extraction was carried out with a 75-μm Carboxen-polydimethylsiloxane fiber coating at 22 ºC for 20 min, and analysed by a GC 2010 Plus A from Shimadzu with a sulphur filter detector: splitless mode (0.3 min), the column temperature program was from 60 ºC, increased by 15 ºC/min to 100 ºC (2 min). The injector temperature was held at 250 ºC, and the detector at 260 ºC. For calibration curve a gas diluter equipment (digital Hovagas G2 - Multi Component Gas Mixer) was used to do the standards. This unit had two input connections, one for a stream of the dilute gas and another for a stream of nitrogen and an output connected to a glass bulb. A 40 ppm H2S and a 50 ppm MM cylinders were used. The equipment was programmed to the selected concentration, and it automatically carried out the dilution to the glass bulb. The mixture was left flowing through the glass bulb for 5 min and then the extremities were closed. This method allowed the calibration between 1-20 ppm for H2S and 0.02-0.1 ppm and 1-3.5 ppm for MM. Several quantifications of air samples from inlet and outlet of a biofilter operating in a waste management facility in the north of Portugal allowed the evaluation the biofilters performance.

Keywords: biofiltration, hydrogen sulphide, mercaptans, quantification

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Authors: Adel Mohamed El-Baghdady, Walid Sayed Abdulgalil, Ahmad Asran, Ibrahim Nosier

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This paper studies the effectiveness of applying value engineering to actual concrete mixtures. The study was conducted in the State of Qatar on a number of strategic construction projects with international engineering specifications for the 2022 World Cup projects. The study examined the concrete mixtures of Doha Metro project and the development of KAHRAMAA’s (Qatar Electricity and Water Company) Abu Funtas Strategic Desalination Plant, in order to generally improve the quality and productivity of ready-mixed concrete used in construction and hydraulic projects. The application of value engineering to such concrete mixtures resulted in the following: i) improving the quality of concrete mixtures and increasing the durability of buildings in which they are used; ii) reducing the waste of excess materials of concrete mixture, optimizing the use of resources, and enhancing sustainability; iii) reducing the use of cement, thus reducing CO₂ emissions which ensures the protection of environment and public health; iv) reducing actual costs of concrete mixtures and, in turn, reducing the costs of construction projects; and v) increasing the market share and competitiveness of concrete producers. This research shows that applying the methodology of value engineering to ready-mixed concrete is an effective way to save around 5% of the total cost of concrete mixtures supplied to construction and hydraulic projects, improve the quality according to the technical requirements and as per the standards and specifications for ready-mixed concrete, improve the environmental impact, and promote sustainability.

Keywords: value management, cost of concrete, performance, optimization, sustainability, environmental impact

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Authors: Chabungbam Niranjit Khuman, Makarand Madhao Ghangrekar, Arunabha Mitra

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The cost of aeration is one of the limiting factors in the upscaling of microbial fuel cells (MFC) for field-scale applications. Wetland macrophytes have the ability to release oxygen into the water to maintain aerobic conditions in their root zone. In this experiment, the efficacy of rhizospheric oxygen release of wetland macrophytes as a source of oxygen in the cathodic chamber of MFC was conducted. The experiment was conducted in an MFC consisting of a three-liter anodic chamber made of ceramic cylinder and a 27 L cathodic chamber. Untreated carbon felts were used as electrodes (i.e., anode and cathode) and connected to an external load of 100 Ω using stainless steel wire. Wetland macrophytes (Canna indica) were grown in the cathodic chamber of the MFC in a hydroponic fashion using a styrofoam sheet (termed as macrophytes assisted-microbial fuel cell, M-MFC). The catholyte (i.e., water) in the M-MFC had negligible contact with atmospheric air due to the styrofoam sheet used for maintaining the hydroponic condition. There was no mixing of the catholyte in the M-MFC. Sucrose based synthetic wastewater having chemical oxygen demand (COD) of 3000 mg/L was fed into the anodic chamber of the MFC in fed-batch mode with a liquid retention time of four days. The C. indica thrived well throughout the duration of the experiment without much care. The average dissolved oxygen (DO) concentration and pH value in the M-MFC were 3.25 mg/L and 7.07, respectively, in the catholyte. Since the catholyte was not in contact with air, the DO in the catholyte might be considered as solely liberated from the rhizospheric oxygen release of C. indica. The maximum COD removal efficiency of M-MFC observed during the experiment was 76.9%. The inadequacy of terminal electron acceptor in the cathodic chamber in M-MFC might have hampered the electron transfer, which in turn, led to slower specific microbial activity, thereby resulting in lower COD removal efficiency than the traditional MFC with aerated catholyte. The average operating voltage (OV) and open-circuit voltage (OCV) of 294 mV and 594 mV, respectively, were observed in M-MFC. The maximum power density observed during polarization was 381 mW/m³, and the maximum sustainable power density observed during the experiment was 397 mW/m³ in M-MFC. The maximum normalized energy recovery and coulombic efficiency of 38.09 Wh/m³ and 1.27%, respectively, were observed. Therefore, it was evidenced that rhizospheric oxygen release of wetland macrophytes (C. indica) was capable of sustaining the cathodic reaction in MFC for field-scale applications.

Keywords: hydroponic, microbial fuel cell, rhizospheric oxygen release, wetland macrophytes

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Authors: Sergio Rapagnà, Alessandro Antonio Papa, Armando Vitale, Andre Di Carlo

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In recent years the world population has enormously increased the use of plastic products for their living needs, in particular for transporting and storing consumer goods such as food and beverage. Plastics are widely used in the automotive industry, in construction of electronic equipment, clothing and home furnishings. Over the last 70 years, the annual production of plastic products has increased from 2 million tons to 460 million tons. About 20% of the last quantity is mismanaged as waste. The consequence of this mismanagement is the release of plastic waste into the terrestrial and marine environments which represents a danger to human health and the ecosystem. Recycling all plastics is difficult because they are often made with mixtures of polymers that are incompatible with each other and contain different additives. The products obtained are always of lower quality and after two/three recycling cycles they must be eliminated either by thermal treatment to produce heat or disposed of in landfill. An alternative to these current solutions is to obtain a mixture of gases rich in H₂, CO and CO₂ suitable for being profitably used for the production of chemicals with consequent savings fossil sources. Obtaining a hydrogen-rich syngas can be achieved by gasification process using the fluidized bed reactor, in presence of steam as the fluidization medium. The fluidized bed reactor allows the gasification process of plastics to be carried out at a constant temperature and allows the use of different plastics with different compositions and different grain sizes. Furthermore, during the gasification process the use of steam increase the gasification of char produced by the first pyrolysis/devolatilization process of the plastic particles. The bed inventory can be made with particles having catalytic properties such as olivine, capable to catalyse the steam reforming reactions of heavy hydrocarbons normally called tars, with a consequent increase in the quantity of gases produced. The plant is composed of a fluidized bed reactor made of AISI 310 steel, having an internal diameter of 0.1 m, containing 3 kg of olivine particles as a bed inventory. The reactor is externally heated by an oven up to 1000 °C. The hot producer gases that exit the reactor, after being cooled, are quantified using a mass flow meter. Gas analyzers are present to measure instantly the volumetric composition of H₂, CO, CO₂, CH₄ and NH₃. At the conference, the results obtained from the continuous gasification of polypropylene (PP) particles in a steam atmosphere at temperatures of 840-860 °C will be presented.

Keywords: gasification, fluidized bed, hydrogen, olivine, polypropyle

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