Search results for: optimization of composites

Authors: Anita Vidacs, Robert Rajko, Csaba Vagvolgyi, Judit Krisch

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With the optimization of a new disinfectant the number of tests could be decreased and the cost of processing too. Good sanitizers are eco-friendly and allow no resistance evolvement of bacteria. The essential oils (EOs) are natural antimicrobials, and most of them have the Generally Recognized As Safe (GRAS) status. In our study, the effect of the EOs cinnamon, marjoram, and thyme was investigated against mixed species bacterial biofilms of Escherichia coli, Listeria monocytogenes, Pseudomonas putida, and Staphylococcus aureus. The optimal concentration of EOs, disinfection time and level of pH were evaluated with the aid of Response Surface Box-Behnken Design (RSD) on 1 day and 7 days old biofilms on metal, plastic, and wood surfaces. The variable factors were in the range of 1-3 times of minimum bactericide concentration (MBC); 10-110 minutes acting time and 4.5- 7.5 pH. The optimized EO disinfectant was compared to industrial used chemicals (HC-DPE, Hypo). The natural based disinfectants were applicable; the acting time was below 30 minutes. EOs were able to eliminate the biofilm from the used surfaces except from wood. The disinfection effect of the EO based natural solutions was in most cases equivalent or better compared to chemical sanitizers used in food industry.

Keywords: biofilm, Box-Behnken design, disinfectant, essential oil

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Authors: Kasim Görenekli, Ali Gülbağ

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This study presents a comprehensive analysis of water consumption patterns in Kocaeli province, Turkey, utilizing various machine learning approaches. We analyzed data from 5,000 water subscribers across residential, commercial, and official categories over an 80-month period from January 2016 to August 2022, resulting in a total of 400,000 records. The dataset encompasses water consumption records, weather information, weekends and holidays, previous months' consumption, and the influence of the COVID-19 pandemic.We implemented and compared several machine learning models, including Linear Regression, Random Forest, Support Vector Regression (SVR), XGBoost, Artificial Neural Networks (ANN), Long Short-Term Memory (LSTM), and Gated Recurrent Units (GRU). Particle Swarm Optimization (PSO) was applied to optimize hyperparameters for all models.Our results demonstrate varying performance across subscriber types and models. For official subscribers, Random Forest achieved the highest R² of 0.699 with PSO optimization. For commercial subscribers, Linear Regression performed best with an R² of 0.730 with PSO. Residential water usage proved more challenging to predict, with XGBoost achieving the highest R² of 0.572 with PSO.The study identified key factors influencing water consumption, with previous months' consumption, meter diameter, and weather conditions being among the most significant predictors. The impact of the COVID-19 pandemic on consumption patterns was also observed, particularly in residential usage.This research provides valuable insights for effective water resource management in Kocaeli and similar regions, considering Turkey's high water loss rate and below-average per capita water supply. The comparative analysis of different machine learning approaches offers a comprehensive framework for selecting appropriate models for water consumption prediction in urban settings.

Keywords: mMachine learning, water consumption prediction, particle swarm optimization, COVID-19, water resource management

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Authors: Loris Franchi, Daniele Calvi, Sabrina Corpino

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This paper presents a design methodology in which stakeholders are assisted with the exploration of a so-called negotiation space, aiming to the maximization of both group social welfare and single stakeholder’s perceived utility. The outcome results in less design iterations needed for design convergence while obtaining a higher solution effectiveness. During the early stage of a space project, not only the knowledge about the system but also the decision outcomes often are unknown. The scenario is exacerbated by the fact that decisions taken in this stage imply delayed costs associated with them. Hence, it is necessary to have a clear definition of the problem under analysis, especially in the initial definition. This can be obtained thanks to a robust generation and exploration of design alternatives. This process must consider that design usually involves various individuals, who take decisions affecting one another. An effective coordination among these decision-makers is critical. Finding mutual agreement solution will reduce the iterations involved in the design process. To handle this scenario, the paper proposes a design methodology which, aims to speed-up the process of pushing the mission’s concept maturity level. This push up is obtained thanks to a guided negotiation space exploration, which involves autonomously exploration and optimization of trade opportunities among stakeholders via Artificial Intelligence algorithms. The negotiation space is generated via a multidisciplinary collaborative optimization method, infused by game theory and multi-attribute utility theory. In particular, game theory is able to model the negotiation process to reach the equilibria among stakeholder needs. Because of the huge dimension of the negotiation space, a collaborative optimization framework with evolutionary algorithm has been integrated in order to guide the game process to efficiently and rapidly searching for the Pareto equilibria among stakeholders. At last, the concept of utility constituted the mechanism to bridge the language barrier between experts of different backgrounds and differing needs, using the elicited and modeled needs to evaluate a multitude of alternatives. To highlight the benefits of the proposed methodology, the paper presents the design of a CubeSat mission for the observation of lunar radiation environment. The derived solution results able to balance all stakeholders needs and guaranteeing the effectiveness of the selection mission concept thanks to its robustness in valuable changeability. The benefits provided by the proposed design methodology are highlighted, and further development proposed.

Keywords: concurrent engineering, artificial intelligence, negotiation in engineering design, multidisciplinary optimization

Procedia PDF Downloads 136

Authors: Abdulaziz F. Ettir, Ghait Bashir, Tarek S. Duzan

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A proper well planning is very vital to achieve any successful drilling program on the basis of preventing, overcome all drilling problems and minimize cost operations. Since the hydraulic system plays an active role during the drilling operations, that will lead to accelerate the drilling effort and lower the overall well cost. Likewise, an improperly designed hydraulic system can slow drill rate, fail to clean the hole of cuttings, and cause kicks. In most cases, common sense and commercially available computer programs are the only elements required to design the hydraulic system. Drilling optimization is the logical process of analyzing effects and interactions of drilling variables through applied drilling and hydraulic equations and mathematical modeling to achieve maximum drilling efficiency with minimize drilling cost. In this paper, practical software adopted in this paper to define drilling optimization models including four different optimum keys, namely Opti-flow, Opti-clean, Opti-slip and Opti-nozzle that can help to achieve high drilling efficiency with lower cost. The used data in this research from vertical and horizontal wells were recently drilled in Waha Oil Company fields. The input data are: Formation type, Geopressures, Hole Geometry, Bottom hole assembly and Mud reghology. Upon data analysis, all the results from wells show that the proposed program provides a high accuracy than that proposed from the company in terms of hole cleaning efficiency, and cost break down if we consider that the actual data as a reference base for all wells. Finally, it is recommended to use the established Optimization calculations software at drilling design to achieve correct drilling parameters that can provide high drilling efficiency, borehole cleaning and all other hydraulic parameters which assist to minimize hole problems and control drilling operation costs.

Keywords: optimum keys, namely opti-flow, opti-clean, opti-slip and opti-nozzle

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Authors: Chun-Lang Chang, Chun-Kai Liu

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In this study, the patients that have undergone total knee replacement surgery from the 2010 National Health Insurance database were adopted as the study participants. The important factors were screened and selected through literature collection and interviews with physicians. Through the Cross Entropy Method (CE), Genetic Algorithm Logistic Regression (GALR), and Particle Swarm Optimization (PSO), the weights of the factors were obtained. In addition, the weights of the respective algorithms, coupled with the Excel VBA were adopted to construct the Case Based Reasoning (CBR) system. The results through statistical tests show that the GALR and PSO produced no significant differences, and the accuracy of both models were above 97%. Moreover, the area under the curve of ROC for these two models also exceeded 0.87. This study shall serve as a reference for medical staff as an assistance for clinical assessment of infections in order to effectively enhance medical service quality and efficiency, avoid unnecessary medical waste, and substantially contribute to resource allocations in medical institutions.

Keywords: Case Based Reasoning, Cross Entropy Method, Genetic Algorithm Logistic Regression, Particle Swarm Optimization, Total Knee Replacement Surgery

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Authors: E. Manikandan, C. Chilambarasan, M. Sulthan Ariff Rahman, S. Kanagaraj, Abhimanyu Pugazhandhi, V. R. Sanal Kumar

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The designer of any flying car has the major concern on the creation of upward force with low takeoff velocity, with minimum drag, coupled with better stability and control warranting its overall high performance both in road and air. In this paper, 3D numerical simulations of external flow of a Ferrari F430 fitted with different NACA series rectangular wings have been carried out for finding the best aerodynamic design option in road and air. The principle that allows a car to rise off the ground by creating lift using deployable wings with desirable lifting characteristics is the main theme of our paper. Additionally, the car body is streamlined in accordance with the speed range. Further, the rounded and tapered shape of the top of the car is designed to slice through the air and minimize the wind resistance. The 3D SST k-ω turbulence model has been used for capturing the intrinsic flow physics during the take off phase. In the numerical study, a fully implicit finite volume scheme of the compressible, Reynolds-Averaged, Navier-Stokes equations is employed. Through the detailed parametric analytical studies, we have conjectured that Ferrari F430 can be converted into a lucrative flying car with best fit NACA wing through a proper aerodynamic design optimization.

Keywords: aerodynamics of flying car, air taxi, Ferrari F430, roadable airplane

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Authors: Feng Yue, Fei Dai

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With the rapid development of urbanization process in China, its environmental protection pressure is severely tested. So, analyzing and optimizing the landscape pattern is an important measure to ease the pressure on the ecological environment. This paper takes Wuhan Urban Development Zone as the research object, and studies its landscape pattern evolution and quantitative optimization strategy. First, remote sensing image data from 1990 to 2015 were interpreted by using Erdas software. Next, the landscape pattern index of landscape level, class level, and patch level was studied based on Fragstats. Then five indicators of ecological environment based on National Environmental Protection Standard of China were selected to evaluate the impact of landscape pattern evolution on the ecological environment. Besides, the cost distance analysis of ArcGIS was applied to simulate wildlife migration thus indirectly measuring the improvement of ecological environment quality. The result shows that the area of land for construction increased 491%. But the bare land, sparse grassland, forest, farmland, water decreased 82%, 47%, 36%, 25% and 11% respectively. They were mainly converted into construction land. On landscape level, the change of landscape index all showed a downward trend. Number of patches (NP), Landscape shape index (LSI), Connection index (CONNECT), Shannon's diversity index (SHDI), Aggregation index (AI) separately decreased by 2778, 25.7, 0.042, 0.6, 29.2%, all of which indicated that the NP, the degree of aggregation and the landscape connectivity declined. On class level, the construction land and forest, CPLAND, TCA, AI and LSI ascended, but the Distribution Statistics Core Area (CORE_AM) decreased. As for farmland, water, sparse grassland, bare land, CPLAND, TCA and DIVISION, the Patch Density (PD) and LSI descended, yet the patch fragmentation and CORE_AM increased. On patch level, patch area, Patch perimeter, Shape index of water, farmland and bare land continued to decline. The three indexes of forest patches increased overall, sparse grassland decreased as a whole, and construction land increased. It is obvious that the urbanization greatly influenced the landscape evolution. Ecological diversity and landscape heterogeneity of ecological patches clearly dropped. The Habitat Quality Index continuously declined by 14%. Therefore, optimization strategy based on greenway network planning is raised for discussion. This paper contributes to the study of landscape pattern evolution in planning and design and to the research on spatial layout of urbanization.

Keywords: landscape pattern, optimization strategy, ArcGIS, Erdas, landscape metrics, landscape architecture

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Authors: Krutika K. Sawant, Anil Solanki

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The present study deals with the preparation and optimization of ethyl cellulose-containing disopyramide phosphate loaded microspheres using solvent evaporation technique. A central composite design consisting of a two-level full factorial design superimposed on a star design was employed for optimizing the preparation microspheres. The drug:polymer ratio (X1) and speed of the stirrer (X2) were chosen as the independent variables. The cumulative release of the drug at a different time (2, 6, 10, 14, and 18 hr) was selected as the dependent variable. An optimum polynomial equation was generated for the prediction of the response variable at time 10 hr. Based on the results of multiple linear regression analysis and F statistics, it was concluded that sustained action can be obtained when X1 and X2 are kept at high levels. The X1X2 interaction was found to be statistically significant. The drug release pattern fitted the Higuchi model well. The data of a selected batch were subjected to an optimization study using Box-Behnken design, and an optimal formulation was fabricated. Good agreement was observed between the predicted and the observed dissolution profiles of the optimal formulation.

Keywords: disopyramide phosphate, ethyl cellulose, microspheres, controlled release, Box-Behnken design, factorial design

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Authors: Armin Amindari

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Hermetic compressors are used widely for refrigeration, heat pump, and air conditioning applications. With the improvement of energy conservation and environmental protection requirements, inverter compressors that operates at different speeds have become increasingly attractive in the industry. Although speed change capability is more efficient, passing through resonant frequencies may lead to excessive vibrations. In this work, an integrated vibration control approach based on flexible multi-body dynamics theory is used for optimizing the vibration amplitudes of the compressor at different operating speeds. To examine the compressor vibrations, all the forces and moments exerted on the cylinder block were clarified and minimized using balancers attached to the upper and lower ends of the motor rotor and crankshaft. The vibration response of the system was simulated using Motionview™ software. In addition, mass-spring optimization was adopted to shift the resonant frequencies out of the operating speeds. The modal shapes of the system were studied using Optistruct™ solver. Using this approach, the vibrations were reduced up to 56% through dynamic simulations. The results were in high agreement with various experimental test data. In addition, the vibration resonance problem observed at low speeds was solved by shifting the resonant frequencies through optimization studies.

Keywords: vibration, MBD, compressor, hermetic

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Authors: Subodh Kumar, Amit Varde

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Typical on-premises high-performance computing (HPC) environments consist of a fixed number and a fixed set of computing hardware. During the design of the HPC environment, the hardware components, including but not limited to CPU, Memory, GPU, and networking, are carefully chosen from select vendors for optimal performance. High capital cost for building the environment is a prime factor influencing the design environment. A class of software called “Job Schedulers” are critical to maximizing these resources and running multiple workloads to extract the maximum value for the high capital cost. In principle, schedulers work by preventing workloads and users from monopolizing the finite hardware resources by queuing jobs in a workload. A cloud-based HPC environment does not have the limitations of fixed (type of and quantity of) hardware resources. In theory, users and workloads could spin up any number and type of hardware resource. This paper discusses the limitations of using traditional scheduling algorithms for cloud-based HPC workloads. It proposes a new set of features, called “HPC optimizers,” for maximizing the benefits of the elasticity and scalability of the cloud with the goal of cost-performance optimization of the workload.

Keywords: high performance computing, HPC, cloud computing, optimization, schedulers

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Authors: Sanat K. Dash, Rama S. Verma, Sarit K. Das

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A logarithmic microfluidic shear device was designed and fabricated for cellular mechanotransduction studies. The device contains four cell culture chambers in which flow was modulated to achieve a logarithmic increment. Resistance values were optimized to make the device compact. The network of resistances was developed according to a unique combination of series and parallel resistances as found via optimization. Simulation results done in Ansys 16.1 matched the analytical calculations and showed the shear stress distribution at different inlet flow rates. Fabrication of the device was carried out using conventional photolithography and PDMS soft lithography. Flow profile was validated taking DI water as working fluid and measuring the volume collected at all four outlets. Volumes collected at the outlets were in accordance with the simulation results at inlet flow rates ranging from 1 ml/min to 0.1 ml/min. The device can exert fluid shear stresses ranging four orders of magnitude on the culture chamber walls which will cover shear stress values from interstitial flow to blood flow. This will allow studying cell behavior in the long physiological range of shear stress in a single run reducing number of experiments.

Keywords: microfluidics, mechanotransduction, fluid shear stress, physiological shear

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Authors: Elmo Thiago Lins Cöuras Ford, Valentina Alessandra Carvalho do Vale

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Given the unquestionable need of environmental preservation, the natural fibers have been seen as a salutary alternative for production of composites in substitution to the synthetic fibers, vitreous and metallic. In this work, the behavior of a composite was analyzed done with fiber of the peel of the coconut as reinforcement and latex as head office, when submitted the source of heat. The temperature profiles were verified in the internal surfaces and it expresses of the composite as well as the temperature gradient in the same. It was also analyzed the behavior of this composite when submitted to a cold source. As consequence, in function of the answers of the system, conclusions were reached.

Keywords: natural fiber, composite, temperature, latex, gradient

Procedia PDF Downloads 817

Authors: Mohammad Bagher Anvari, Arman Shojaei

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Incremental launching, a widely adopted bridge erection technique, offers numerous advantages for bridge designers. However, accurately simulating and modeling the dynamic behavior of the bridge during each step of the launching process proves to be tedious and time-consuming. The perpetual variation of internal forces within the deck during construction stages adds complexity, exacerbated further by considerations of other load cases, such as support settlements and temperature effects. As a result, there is an urgent need for a reliable, simple, economical, and fast algorithmic solution to model bridge construction stages effectively. This paper presents a novel Finite Element (FE) model that focuses on studying the static behavior of bridges during the launching process. Additionally, a simple method is introduced to normalize all quantities in the problem. The new FE model overcomes the limitations of previous models, enabling the simulation of all stages of launching, which conventional models fail to achieve due to underlying assumptions. By leveraging the results obtained from the new FE model, this study proposes solutions to improve the accuracy of conventional models, particularly for the initial stages of bridge construction that have been neglected in previous research. The research highlights the critical role played by the first span of the bridge during the initial stages, a factor often overlooked in existing studies. Furthermore, a new and simplified model termed the "semi-infinite beam" model, is developed to address this oversight. By utilizing this model alongside a simple optimization approach, optimal values for launching nose specifications are derived. The practical applications of this study extend to optimizing the nose-deck system of incrementally launched bridges, providing valuable insights for practical usage. In conclusion, this paper introduces a comprehensive Finite Element model for studying the static behavior of bridges during incremental launching. The proposed model addresses limitations found in previous approaches and offers practical solutions to enhance accuracy. The study emphasizes the importance of considering the initial stages and introduces the "semi-infinite beam" model. Through the developed model and optimization approach, optimal specifications for launching nose configurations are determined. This research holds significant practical implications and contributes to the optimization of incrementally launched bridges, benefiting both the construction industry and bridge designers.

Keywords: incremental launching, bridge construction, finite element model, optimization

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Authors: Hussein Hakim, Zainab Al-Ramadhan, Ahmed Hashim

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Polymer nano composites of polyvinylpyrrolidone and poly-ethylene glycol with different concentrations of aluminum oxide (Al2O3) nano particles have been prepared by solution cast method. The optical characterizations have been done by analyzing the absorption (A) spectra in the 300–800 nm spectral region. It was found that the optical energy gap decreases with the increasing of Al2O3 nano particles content. The optical constants (refractive index, extinction coefficient, real and imaginary parts of the dielectric constant) are changing with increasing aluminum oxide nano particle concentrations.

Keywords: nanocomposites, polyvinylpyrrolidone, optical constants, polymers, blend

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Authors: Héctor Rivera-Gómez, Eva Selene Hernández-Gress, Oscar Montaño-Arango, Jose Ramon Corona-Armenta

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This research studies the joint production, maintenance and subcontracting control policy for an unreliable deteriorating manufacturing system. Production activities are controlled by a derivation of the Hedging Point Policy, and given that the system is subject to deterioration, it reduces progressively its capacity to satisfy product demand. Multiple deterioration effects are considered, reflected mainly in the quality of the parts produced and the reliability of the machine. Subcontracting is available as support to satisfy product demand; also overhaul maintenance can be conducted to reduce the effects of deterioration. The main objective of the research is to determine simultaneously the production, maintenance and subcontracting rate which minimize the total incurred cost. A stochastic dynamic programming model is developed and solved through a simulation-based approach composed of statistical analysis and optimization with the response surface methodology. The obtained results highlight the strong interactions between production, deterioration and quality which justify the development of an integrated model. A numerical example and a sensitivity analysis are presented to validate our results.

Keywords: subcontracting, optimal control, deterioration, simulation, production planning

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Authors: S. Candamano, A. Iorfida, F. Crea, A. Macario

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Recently, basalt fabric reinforced cementitious composites (FRCM) have attracted great attention because they result to be effective in structural strengthening and cost/environment efficient. In this study, authors investigate their mechanical behavior when an inorganic matrix, belonging to the family of alkali-activated binders, is used. In particular, the matrix has been designed to contain high amounts of industrial by-products and waste, such as Ground Granulated Blast Furnace Slag (GGBFS) and Fly Ash. Fresh state properties, such as workability, mechanical properties and shrinkage behavior of the matrix have been measured, while microstructures and reaction products were analyzed by Scanning Electron Microscopy and X-Ray Diffractometry. Reinforcement is made up of a balanced, coated bidirectional fabric made out of basalt fibres and stainless steel micro-wire, with a mesh size of 8x8 mm and an equivalent design thickness equal to 0.064 mm. Mortars mixes have been prepared by maintaining constant the water/(reactive powders) and sand/(reactive powders) ratios at 0.53 and 2.7 respectively. An appropriate experimental campaign based on direct tensile tests on composite specimens and single-lap shear bond test on brickwork substrate has been thus carried out to investigate their mechanical behavior under tension, the stress-transfer mechanism and failure modes. Tensile tests were carried out on composite specimens of nominal dimensions equal to 500 mm x 50 mm x 10 mm, with 6 embedded rovings in the loading direction. Direct shear tests (DST) were carried out on brickwork substrate using an externally bonded basalt-FRCM composite strip 10 mm thick, 50 mm wide and a bonded length of 300 mm. Mortars exhibit, after 28 days of curing, an average compressive strength of 32 MPa and flexural strength of 5.5 MPa. Main hydration product is a poorly crystalline aluminium-modified calcium silicate hydrate (C-A-S-H) gel. The constitutive behavior of the composite has been identified by means of direct tensile tests, with response curves showing a tri-linear behavior. Test results indicate that the behavior is mainly governed by cracks development (II) and widening (III) up to failure. The ultimate tensile strength and strain were respectively σᵤ = 456 MPa and ɛᵤ= 2.20%. The tensile modulus of elasticity in stage III was EIII= 41 GPa. All single-lap shear test specimens failed due to composite debonding. It occurred at the internal fabric-to-matrix interface, and it was the result of a fracture of the matrix between the fibre bundles. For all specimens, transversal cracks were visible on the external surface of the composite and involved only the external matrix layer. This cracking appears when the interfacial shear stresses increase and slippage of the fabric at the internal matrix layer interface occurs. Since the external matrix layer is bonded to the reinforcement fabric, it translates with the slipped fabric. Average peak load around 945 N, peak stress around 308 MPa and global slip around 6 mm were measured. The preliminary test results allow affirming that Alkali-Activated Materials can be considered a potentially valid alternative to traditional mortars in designing FRCM composites.

Keywords: Alkali-activated binders, Basalt-FRCM composites, direct shear tests, structural strengthening

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Authors: Jitendar Kumar Tiwari, Ajay Mandal, N. Sathish, A. K. Srivastava

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Since the last decade, graphene achieved great attention toward the progress of multifunction metal matrix composites, which are highly demanded in industries to develop energy-efficient systems. This study covers the two advanced aspects of the latest scientific endeavor, i.e., graphene as reinforcement in metallic materials and additive manufacturing (AM) as a processing technology. Herein, high-quality graphene and AlSi10Mg powder mechanically mixed by very low energy ball milling with 0.1 wt. % and 0.2 wt. % graphene. Mixed powder directly subjected to the powder bed fusion process, i.e., an AM technique to produce composite samples along with bare counterpart. The effects of graphene on porosity, microstructure, and mechanical properties were examined in this study. The volumetric distribution of pores was observed under X-ray computed tomography (CT). On the basis of relative density measurement by X-ray CT, it was observed that porosity increases after graphene addition, and pore morphology also transformed from spherical pores to enlarged flaky pores due to improper melting of composite powder. Furthermore, the microstructure suggests the grain refinement after graphene addition. The columnar grains were able to cross the melt pool boundaries in case of the bare sample, unlike composite samples. The smaller columnar grains were formed in composites due to heterogeneous nucleation by graphene platelets during solidification. The tensile properties get affected due to induced porosity irrespective of graphene reinforcement. The optimized tensile properties were achieved at 0.1 wt. % graphene. The increment in yield strength and ultimate tensile strength was 22% and 10%, respectively, for 0.1 wt. % graphene reinforced sample in comparison to bare counterpart while elongation decreases 20% for the same sample. The hardness indentations were taken mostly on the solid region in order to avoid the collapse of the pores. The hardness of the composite was increased progressively with graphene content. Around 30% of increment in hardness was achieved after the addition of 0.2 wt. % graphene. Therefore, it can be concluded that powder bed fusion can be adopted as a suitable technique to develop graphene reinforced AlSi10Mg composite. Though, some further process modification required to avoid the induced porosity after the addition of graphene, which can be addressed in future work.

Keywords: graphene, hardness, porosity, powder bed fusion, tensile properties

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Authors: Gak-Gyu Kim, Won Il Jung

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According to a remarkable development of science and technology, function and role of the system of engineering fields has recently been diversified. The system has become increasingly more complex and precise, and thus, system designers intended to maximize reliability concentrate more effort at the design stage. This study deals with the reliability redundancy optimization problem (RROP) for k-out-of-n: G system configuration with cold standby and warm standby components. This paper further intends to present the optimal mathematical model through which the following three elements of (i) multiple components choices, (ii) redundant components quantity and (iii) the choice of redundancy strategies may be combined in order to maximize the reliability of the system. Therefore, we focus on the following three issues. First, we consider RROP that there exists warm standby state as well as cold standby state of the component. Second, as eliminating an approximation approach of the previous RROP studies, we construct a precise model for system reliability. Third, given transition time when the state of components changes, we present not simply a workable solution but the advanced method. For the wide applicability of RROPs, moreover, we use absorbing continuous time Markov chain and matrix analytic methods in the suggested mathematical model.

Keywords: RROP, matrix analytic methods, k-out-of-n: G system, MTTF, absorbing continuous time Markov Chain

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Authors: Aniket Ganvir, Ritarani Sahu, Suchismita Chinara

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The rapid digitization of various aspects of life is leading to the creation of smart IoT ecosystems, where interconnected devices generate significant amounts of valuable data. However, these IoT devices face constraints such as limited computational resources and bandwidth. Cloud computing emerges as a solution by offering ample resources for offloading tasks efficiently despite introducing latency issues, especially for time-sensitive applications like fog computing. Fog computing (FC) addresses latency concerns by bringing computation and storage closer to the network edge, minimizing data travel distance, and enhancing efficiency. Offloading tasks to fog nodes or the cloud can conserve energy and extend IoT device lifespan. The offloading process is intricate, with tasks categorized as full or partial, and its optimization presents an NP-hard problem. Traditional greedy search methods struggle to address the complexity of task offloading efficiently. To overcome this, the efficient crow search algorithm (ECSA) has been proposed as a meta-heuristic optimization algorithm. ECSA aims to effectively optimize computation offloading, providing solutions to this challenging problem.

Keywords: IoT, fog computing, task offloading, efficient crow search algorithm

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Authors: Djaafar Fatiha, Ghalem Bachir, Hadri Bagdad

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We studied mainly the influence of temperature, thickness, molar fraction and the doping of the various layers (emitter, base, BSF and window) on the performances of a photovoltaic solar cell. In a first stage, we optimized the performances of the InGaP/GaAs dual-junction solar cell while varying its operation temperature from 275°K to 375 °K with an increment of 25°C using a virtual wafer fabrication TCAD Silvaco. The optimization at 300 °K led to the following result: Icc =14.22 mA/cm2, Voc =2.42V, FF=91.32 %, η= 22.76 % which is close with those found in the literature. In a second stage ,we have varied the molar fraction of different layers as well their thickness and the doping of both emitters and bases and we have registered the result of each variation until obtaining an optimal efficiency of the proposed solar cell at 300°K which was of Icc=14.35mA/cm2,Voc=2.47V,FF=91.34,and η=23.33% for In(1-x)Ga(x)P molar fraction( x=0.5).The elimination of a layer BSF on the back face of our cell, enabled us to make a remarkable improvement of the short-circuit current (Icc=14.70 mA/cm2) and a decrease in open circuit voltage Voc and output η which reached 1.46V and 11.97% respectively. Therefore, we could determine the critical parameters of the cell and optimize its various technological parameters to obtain the best performance for a dual junction solar cell .This work opens the way with new prospects in the field of the photovoltaic one. Such structures will thus simplify the manufacturing processes of the cells; will thus reduce the costs while producing high outputs of photovoltaic conversion.

Keywords: modeling, simulation, multijunction, optimization, Silvaco ATLAS

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Authors: Un-Hwan Park, Jun-Hyeok Heo, In-Sung Lee, Seong-Jin Cho, Tae-Hyeon Oh, Dae-Kyu Park

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Sound absorption coefficient is considered important when designing because noise affects emotion quality of car. It is designed with lots of experiment tunings in the field because it is unreliable to predict it for multi-layer material. In this paper, we present the design of sound absorption for automotive interior material with multiple layers using estimation software of sound absorption coefficient for reverberation chamber. Additionally, we introduce the method for estimation of physical properties required to predict sound absorption coefficient of car interior materials with multiple layers too. It is calculated by inverse algorithm. It is very economical to get information about physical properties without expensive equipment. Correlation test is carried out to ensure reliability for accuracy. The data to be used for the correlation is sound absorption coefficient measured in the reverberation chamber. In this way, it is considered economical and efficient to design automotive interior materials. And design optimization for sound absorption coefficient is also easy to implement when it is designed.

Keywords: sound absorption coefficient, optimization design, inverse algorithm, automotive interior material, multiple layers nonwoven, scaled reverberation chamber, sound impedance tubes

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Authors: Hesham Osman

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The challenges facing aging urban infrastructure systems require a more holistic and comprehensive approach to their management. The large number of urban infrastructure renewal activities occurring in cities throughout the world leads to social, economic and environmental impacts on the communities in its vicinity. As such, a coordinated effort is required to streamline these activities. This paper presents a framework to enable temporal (time-based) coordination of water, sewer and road intervention activities. Intervention activities include routine maintenance, renewal, and replacement of physical assets. The coordination framework considers 1) Life-cycle costs, 2) Infrastructure level-of-service, and 3) Risk exposure to system operators. The model enables infrastructure asset managers to trade-off options of delaying versus bringing forward intervention activities of one system in order to be executed in conjunction with another co-located system in the right-of-way. The framework relies on a combination of meta-heuristics and goal-based optimization. In order to demonstrate the applicability of the framework, a case study for a major infrastructure corridor in Cairo, Egypt is taken as an example. Results show that the framework can be scaled-up to include other infrastructure systems located in the right-of-way like electricity, gas and telecom, provided that information can be shared among these entities.

Keywords: infrastructure, rehabilitation, construction, optimization

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Authors: Mohammed Elghazy, Ahmed El Refai, Usama Ebead, Antonio Nanni

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Rehabilitating corrosion-damaged reinforced concrete (RC) structures has been accomplished using various techniques such as steel plating, external post-tensioning, and external bonding of fiber reinforced polymer (FRP) composites. This paper reports on the use of an innovative technique to strengthen corrosion-damaged RC structures using fabric-reinforced cementitious matrix (FRCM) composites. FRCM consists of dry-fiber fabric embedded in cement-based matrix. Twelve large-scale RC beams were constructed and tested in flexural monotonic and fatigue loads. Prior to testing, ten specimens were subjected to accelerated corrosion process for 140 days leading to an average mass loss in the tensile steel bars of 18.8 %. Corrosion was restricted to the main reinforcement located in the middle third of the beam span. Eight corroded specimens were repaired and strengthened while two virgin and two corroded-unrepaired/unstrengthened beams were used as benchmarks for comparison purpose. The test parameters included the FRCM materials (Carbon-FRCM, PBO-FRCM), the number of FRCM plies, the strengthening scheme, and the type of loading (monotonic and fatigue). The effects of the pervious parameters on the flexural response, the mode of failure, and the fatigue life were reported. Test results showed that corrosion reduced the yield and ultimate strength of the beams. The corroded-unrepaired specimen failed to meet the provisions of the ACI-318 code for crack width criteria. The use of FRCM significantly increased the ultimate strength of the corroded specimen by 21% and 65% more than that of the corroded-unrepaired specimen. Corrosion significantly decreased the fatigue life of the corroded-unrepaired beam by 77% of that of the virgin beam. The fatigue life of the FRCM repaired-corroded beams increased to 1.5 to 3.8 times that of the corroded-unrepaired beam but was lower than that of the virgin specimen. The specimens repaired with U-wrapped PBO-FRCM strips showed higher fatigue life than those repaired with the end-anchored bottom strips having similar number of PBO-FRCM-layers. PBO-FRCM was more effective than Carbon-FRCM in restoring the fatigue life of the corroded specimens.

Keywords: corrosion, concrete, fabric-reinforced cementitious matrix (FRCM), fatigue, flexure, repair

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Authors: Cao Bin, Yuan Yi, Wang Qiang, Amor Abdelkader, Ali Reza Kamali, Diogo Montalvão

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The study of the electrodynamic behavior of non-ferrous particles in time-varying magnetic fields is a promising area of research with wide applications, including recycling of non-ferrous metals, mechanical transmission, and space debris. The key technology for recovering non-ferrous metals is eddy current separation (ECS), which utilizes the eddy current force and torque to separate non-ferrous metals. ECS has several advantages, such as low energy consumption, large processing capacity, and no secondary pollution, making it suitable for processing various mixtures like electronic scrap, auto shredder residue, aluminum scrap, and incineration bottom ash. Improving the separation efficiency of mixtures with different particle sizes in ECS can create significant social and economic benefits. Our previous study investigated the influence of particle size on separation efficiency by combining numerical simulations and separation experiments. Pearson correlation analysis found a strong correlation between the eddy current force in simulations and the repulsion distance in experiments, which confirmed the effectiveness of our simulation model. The interaction effects between particle size and material type, rotational speed, and magnetic pole arrangement were examined. It offer valuable insights for the design and optimization of eddy current separators. The underlying mechanism behind the effect of particle size on separation efficiency was discovered by analyzing eddy current and field gradient. The results showed that the magnitude and distribution heterogeneity of eddy current and magnetic field gradient increased with particle size in eddy current separation. Based on this, we further found that increasing the curvature of magnetic field lines within particles could also increase the eddy current force, providing a optimized method to improving the separation efficiency of fine particles. By combining the results of the studies, a more systematic and comprehensive set of optimization guidelines can be proposed for mixtures with different particle size ranges. The separation efficiency of fine particles could be improved by increasing the rotational speed, curvature of magnetic field lines, and electrical conductivity/density of materials, as well as utilizing the eddy current torque. When designing an ECS, the particle size range of the target mixture should be investigated in advance, and the suitable parameters for separating the mixture can be fixed accordingly. In summary, these results can guide the design and optimization of ECS, and also expand the application areas for ECS.

Keywords: eddy current separation, particle size, numerical simulation, metal recovery

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Authors: Farhood Rismanchian, Seong Hyeon Park, Young Hoon Lee

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During the recent years, demand for healthcare services has dramatically increased. As the demand for healthcare services increases, so does the necessity of constructing new healthcare buildings and redesigning and renovating existing ones. Increasing demands necessitate the use of optimization techniques to improve the overall service efficiency in healthcare settings. However, high complexity of care processes remains the major challenge to accomplish this goal. This study proposes a method based on process mining results to address the high complexity of care processes and to find the optimal layout of the various medical centers in an emergency department. ProM framework is used to discover clinical pathway patterns and relationship between activities. Sequence clustering plug-in is used to remove infrequent events and to derive the process model in the form of Markov chain. The process mining results served as an input for the next phase which consists of the development of the optimization model. Comparison of the current ED design with the one obtained from the proposed method indicated that a carefully designed layout can significantly decrease the distances that patients must travel.

Keywords: Mixed Integer programming, Facility layout problem, Process Mining, Healthcare Operation Management

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Authors: Joy Marie Mora, Mark Daniel De Luna, Tsair-Wang Chung

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Transesterification reaction of soybean oil with methanol was carried out to produce fatty acid methyl esters (FAME) using calcined alkali metal (Na and Li) supported by pumice silica as the solid base catalyst. Pumice silica catalyst was activated by loading alkali metal ions to its surface via an ion-exchange method. Response surface methodology (RSM) in combination with Box-Behnken design (BBD) was used to optimize the operating parameters in biodiesel production, namely: reaction temperature, methanol to oil molar ratio, reaction time, and catalyst concentration. Using the optimized sets of parameters, FAME yields using sodium and lithium silicate catalysts were 98.80% and 98.77%, respectively. A pseudo-first order kinetic equation was applied to evaluate the kinetic parameters of the reaction. The prepared catalysts were characterized by several techniques such as X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), Brunauer-Emmett-Teller (BET) sorptometer, and scanning electron microscopy (SEM). In addition, the reusability of the catalysts was successfully tested in two subsequent cycles.

Keywords: alkali metal, biodiesel, Box-Behnken design, heterogeneous catalyst, kinetics, optimization, pumice, transesterification

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Authors: Muhammad Abdul Qyyum, Kinza Qadeer, Moonyong Lee

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Globally, liquefied natural gas (LNG) has drawn interest as a green energy source in comparison with other fossil fuels, mainly because of its ease of transport and low carbon dioxide emissions. It is expected that demand for LNG will grow steadily over the next few decades. In addition, because the demand for clean energy is increasing, LNG production facilities are expanding into new natural gas reserves across the globe. However, LNG production is an energy and cost intensive process because of the huge power requirements for compression and refrigeration. Therefore, one of the major challenges in the LNG industry is to improve the energy efficiency of existing LNG processes through economic and ecological strategies. The advancement in expansion devices such as two-phase cryogenic expander (TPE) and cryogenic hydraulic turbine (HT) were exploited for energy and cost benefits in natural gas liquefaction. Retrofitting the conventional Joule–Thompson (JT) valve with TPE and HT have the potential to improve the energy efficiency of LNG processes. This research investigated the potential feasibility of the retrofitting of a dual mixed refrigerant (DMR) process by replacing the isenthalpic expansion with isentropic expansion corresponding to energy efficient LNG production. To fully take the potential benefit of the proposed process retrofitting, the proposed DMR schemes were optimized by using a Coggins optimization approach, which was implemented in Microsoft Visual Studio (MVS) environment and linked to the rigorous HYSYS® model. The results showed that the required energy of the proposed isentropic expansion based DMR process could be saved up to 26.5% in comparison with the conventional isenthalpic based DMR process using the JT valves. Utilization of the recovered energy into boosting the natural gas feed pressure could further improve the energy efficiency of the LNG process up to 34% as compared to the base case. This work will help the process engineers to overcome the challenges relating to energy efficiency and safety concerns of LNG processes. Furthermore, the proposed retrofitting scheme can also be implemented to improve the energy efficiency of other isenthalpic expansion based energy intensive cryogenic processes.

Keywords: cryogenic liquid turbine, Coggins optimization, dual mixed refrigerant, energy efficient LNG process, two-phase expander

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Authors: Thirasak Panyaphirawat, Pairoj Sapsmarnwong, Teeratas Pornyungyuen

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This paper presents the findings of an experimental investigation of important machining parameters for the horizontal boring tool modified to mouth with a horizontal lathe machine to bore an overlength workpiece. In order to verify a usability of a modified tool, design of experiment based on Taguchi method is performed. The parameters investigated are spindle speed, feed rate, depth of cut and length of workpiece. Taguchi L9 orthogonal array is selected for four factors three level parameters in order to minimize surface roughness (Ra and Rz) of S45C steel tubes. Signal to noise ratio analysis and analysis of variance (ANOVA) is performed to study an effect of said parameters and to optimize the machine setting for best surface finish. The controlled factors with most effect are depth of cut, spindle speed, length of workpiece, and feed rate in order. The confirmation test is performed to test the optimal setting obtained from Taguchi method and the result is satisfactory.

Keywords: design of experiment, Taguchi design, optimization, analysis of variance, machining parameters, horizontal boring tool

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Authors: Zoe Chang, Max Williams, Gautham Das

Abstract:

The purpose of this study is to evaluate the incorporation of hemp fibers (HF) in concrete. Hemp fiber reinforced concrete (HFRC) is becoming more popular as an alternative for regular mix designs. This study was done to evaluate the compressive strength of HFRC regarding mix procedure. Hemp fibers were obtained from the manufacturer and hand-processed to ensure uniformity in width and length. The fibers were added to the concrete as both wet and dry mixes to investigate and optimize the mix design process. Results indicated that the dry mix had a compressive strength of 1157 psi compared to the wet mix of 985 psi. This dry mix compressive strength was within range of the standard mix compressive strength of 1533 psi. The statistical analysis revealed that the mix design process needs further optimization and uniformity concerning the addition of HF. Regression analysis revealed the standard mix design had a coefficient of 0.9 as compared to the dry mix of 0.375, indicating a variation in the mixing process. While completing the dry mix, the addition of plain hemp fibers caused them to intertwine, creating lumps and inconsistency. However, during the wet mixing process, combining water and hemp fibers before incorporation allows the fibers to uniformly disperse within the mix; hence the regression analysis indicated a better coefficient of 0.55. This study concludes that HRFC is a viable alternative to regular mixes; however, more research surrounding its characteristics needs to be conducted.

Keywords: hemp fibers, hemp reinforced concrete, wet & dry, freeze thaw testing, compressive strength

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Authors: Rafi Ullah, Shah Muhammad Emaduddin, Taha Jilani

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Vehicle Adhoc Networks (VANET) belongs to a special class of Mobile Adhoc Network (MANET) with high mobility. Network is created by road side vehicles equipped with communication devices like GPS and Wifi etc. Since the environment is highly dynamic due to difference in speed and high mobility of vehicles and weak stability of the network connection, it is a challenging task to design an efficient routing protocol for such an unstable environment. Our proposed algorithm uses heuristic for the calculation of optimal path for routing the packet efficiently in collaboration with several other parameters like geographical location, speed, priority, the distance among the vehicles, communication range, and networks congestion. We have incorporated probabilistic, heuristic and machine learning based approach inconsistency with the relay function of the memory buffer to keep the packet moving towards the destination. These parameters when used in collaboration provide us a very strong and admissible heuristics. We have mathematically proved that the proposed technique is efficient for the routing of packets, especially in a medical emergency situation. These networks can be used for medical emergency, security, entertainment and routing purposes.

Keywords: heuristics routing, intelligent routing, VANET, route optimization

Procedia PDF Downloads 178