Search results for: cost-based structural optimization
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 7138

Search results for: cost-based structural optimization

6478 Structural Analysis of Hydro-Turbine Head Cover Using Ansys

Authors: Surjit Angra, Manisha Kumari, Vinod Kumar

Abstract:

The objective of the Hydro Turbine Head Cover is to support the guide bearing, guide vane regulating mechanism and even in some design for generator thrust bearing support. Mechanical design of head cover deals with high static as well as fluctuating load acting on the structure. In the present work structural analysis of hydro turbine Head-cover using ANSYS software is carried out. Finite element method is used to calculate stresses on head cover. These calculations were done for the maximum possible loading under operating condition “LCI Quick Shut Down”. The results for equivalent Von-Mises stress, total deformation and directional deformation have been plotted and compared with the existing results whether the design is safe or not.

Keywords: ANSYS, head cover, hydro-turbine, structural analysis, total deformation, Von-Mises stress

Procedia PDF Downloads 511
6477 Local Directional Encoded Derivative Binary Pattern Based Coral Image Classification Using Weighted Distance Gray Wolf Optimization Algorithm

Authors: Annalakshmi G., Sakthivel Murugan S.

Abstract:

This paper presents a local directional encoded derivative binary pattern (LDEDBP) feature extraction method that can be applied for the classification of submarine coral reef images. The classification of coral reef images using texture features is difficult due to the dissimilarities in class samples. In coral reef image classification, texture features are extracted using the proposed method called local directional encoded derivative binary pattern (LDEDBP). The proposed approach extracts the complete structural arrangement of the local region using local binary batten (LBP) and also extracts the edge information using local directional pattern (LDP) from the edge response available in a particular region, thereby achieving extra discriminative feature value. Typically the LDP extracts the edge details in all eight directions. The process of integrating edge responses along with the local binary pattern achieves a more robust texture descriptor than the other descriptors used in texture feature extraction methods. Finally, the proposed technique is applied to an extreme learning machine (ELM) method with a meta-heuristic algorithm known as weighted distance grey wolf optimizer (GWO) to optimize the input weight and biases of single-hidden-layer feed-forward neural networks (SLFN). In the empirical results, ELM-WDGWO demonstrated their better performance in terms of accuracy on all coral datasets, namely RSMAS, EILAT, EILAT2, and MLC, compared with other state-of-the-art algorithms. The proposed method achieves the highest overall classification accuracy of 94% compared to the other state of art methods.

Keywords: feature extraction, local directional pattern, ELM classifier, GWO optimization

Procedia PDF Downloads 147
6476 Design an Intelligent Fire Detection System Based on Neural Network and Particle Swarm Optimization

Authors: Majid Arvan, Peyman Beygi, Sina Rokhsati

Abstract:

In-time detection of fire in buildings is of great importance. Employing intelligent methods in data processing in fire detection systems leads to a significant reduction of fire damage at lowest cost. In this paper, the raw data obtained from the fire detection sensor networks in buildings is processed by using intelligent methods based on neural networks and the likelihood of fire happening is predicted. In order to enhance the quality of system, the noise in the sensor data is reduced by analyzing wavelets and applying SVD technique. Meanwhile, the proposed neural network is trained using particle swarm optimization (PSO). In the simulation work, the data is collected from sensor network inside the room and applied to the proposed network. Then the outputs are compared with conventional MLP network. The simulation results represent the superiority of the proposed method over the conventional one.

Keywords: intelligent fire detection, neural network, particle swarm optimization, fire sensor network

Procedia PDF Downloads 368
6475 Evaluation of Soil Stiffness and Strength for Quality Control of Compacted Earthwork

Authors: A. Sawangsuriya, T. B. Edil

Abstract:

Microstructure and fabric of soils play an important role on structural properties e.g. stiffness and strength of compacted earthwork. Traditional quality control monitoring based on moisture-density tests neither reflects the variability of soil microstructure nor provides a direct assessment of structural property, which is the ultimate objective of the earthwork quality control. Since stiffness and strength are sensitive to soil microstructure and fabric, any independent test methods that provide simple, rapid, and direct measurement of stiffness and strength are anticipated to provide an effective assessment of compacted earthen materials’ uniformity. In this study, the soil stiffness gauge (SSG) and the dynamic cone penetrometer (DCP) were respectively utilized to measure and monitor the stiffness and strength in companion with traditional moisture-density measurements of various earthen materials used in Thailand road construction projects. The practical earthwork quality control criteria are presented herein in order to assure proper earthwork quality control and uniform structural property of compacted earthworks.

Keywords: dynamic cone penetrometer, moisture content, quality control, relative compaction, soil stiffness gauge, structural properties

Procedia PDF Downloads 342
6474 Impacts of Low-Density Polyethylene (Plastic Shopping Bags) on Structural Strength and Permeability of Hot-Mix-Asphalt Pavements

Authors: Chayanon Boonyuid

Abstract:

This paper experiments the effects of low-density polyethylene (LDPE) on the structural strength and permeability of hot-mix-asphalt (HMA) pavements. Different proportions of bitumen (4%, 4.5%, 5%, 5.5% and 6% of total aggregates) and plastic (5%, 10% and 15% of bitumen) contents in HMA mixtures were investigated to estimate the optimum mixture of bitumen and plastic in HMA pavement with long-term performance. Marshall Tests and Falling Head Tests were performed to experiment the structure strength and permeability of HMA mixtures with different percentages of plastic materials and bitumen. The laboratory results show that the optimum binder content was 5.5% by weight of aggregates with higher contents of plastic materials, increase structural stability, reduce permanent deformation, increase ductility, and improve fatigue life of HMA pavements. The use of recycled plastic shopping bags can reduce the use of bitumen content by 0.5% - 1% in HMA mixtures resulting in cheaper material costs with better long-term performance. The plastic materials increase the impermeability of HMA pavements. This study has two-fold contributions: optimum contents of both bitumen and plastic materials in HMA mixtures and the impacts of plastic materials on the permeability of HMA pavements.

Keywords: plastic bags, bitumen, structural strength, permeability

Procedia PDF Downloads 135
6473 A Novel Approach of NPSO on Flexible Logistic (S-Shaped) Model for Software Reliability Prediction

Authors: Pooja Rani, G. S. Mahapatra, S. K. Pandey

Abstract:

In this paper, we propose a novel approach of Neural Network and Particle Swarm Optimization methods for software reliability prediction. We first explain how to apply compound function in neural network so that we can derive a Flexible Logistic (S-shaped) Growth Curve (FLGC) model. This model mathematically represents software failure as a random process and can be used to evaluate software development status during testing. To avoid trapping in local minima, we have applied Particle Swarm Optimization method to train proposed model using failure test data sets. We drive our proposed model using computational based intelligence modeling. Thus, proposed model becomes Neuro-Particle Swarm Optimization (NPSO) model. We do test result with different inertia weight to update particle and update velocity. We obtain result based on best inertia weight compare along with Personal based oriented PSO (pPSO) help to choose local best in network neighborhood. The applicability of proposed model is demonstrated through real time test data failure set. The results obtained from experiments show that the proposed model has a fairly accurate prediction capability in software reliability.

Keywords: software reliability, flexible logistic growth curve model, software cumulative failure prediction, neural network, particle swarm optimization

Procedia PDF Downloads 332
6472 Optimal Design of Linear Generator to Recharge the Smartphone Battery

Authors: Jin Ho Kim, Yujeong Shin, Seong-Jin Cho, Dong-Jin Kim, U-Syn Ha

Abstract:

Due to the development of the information industry and technologies, cellular phones have must not only function to communicate, but also have functions such as the Internet, e-banking, entertainment, etc. These phones are called smartphones. The performance of smartphones has improved, because of the various functions of smartphones, and the capacity of the battery has been increased gradually. Recently, linear generators have been embedded in smartphones in order to recharge the smartphone's battery. In this study, optimization is performed and an array change of permanent magnets is examined in order to increase efficiency. We propose an optimal design using design of experiments (DOE) to maximize the generated induced voltage. The thickness of the poleshoe and permanent magnet (PM), the height of the poleshoe and PM, and the thickness of the coil are determined to be design variables. We made 25 sampling points using an orthogonal array according to four design variables. We performed electromagnetic finite element analysis to predict the generated induced voltage using the commercial electromagnetic analysis software ANSYS Maxwell. Then, we made an approximate model using the Kriging algorithm, and derived optimal values of the design variables using an evolutionary algorithm. The commercial optimization software PIAnO (Process Integration, Automation, and Optimization) was used with these algorithms. The result of the optimization shows that the generated induced voltage is improved.

Keywords: smartphone, linear generator, design of experiment, approximate model, optimal design

Procedia PDF Downloads 333
6471 Evaluation of Expected Annual Loss Probabilities of RC Moment Resisting Frames

Authors: Saemee Jun, Dong-Hyeon Shin, Tae-Sang Ahn, Hyung-Joon Kim

Abstract:

Building loss estimation methodologies which have been advanced considerably in recent decades are usually used to estimate socio and economic impacts resulting from seismic structural damage. In accordance with these methods, this paper presents the evaluation of an annual loss probability of a reinforced concrete moment resisting frame designed according to Korean Building Code. The annual loss probability is defined by (1) a fragility curve obtained from a capacity spectrum method which is similar to a method adopted from HAZUS, and (2) a seismic hazard curve derived from annual frequencies of exceedance per peak ground acceleration. Seismic fragilities are computed to calculate the annual loss probability of a certain structure using functions depending on structural capacity, seismic demand, structural response and the probability of exceeding damage state thresholds. This study carried out a nonlinear static analysis to obtain the capacity of a RC moment resisting frame selected as a prototype building. The analysis results show that the probability of being extensive structural damage in the prototype building is expected to 0.004% in a year.

Keywords: expected annual loss, loss estimation, RC structure, fragility analysis

Procedia PDF Downloads 387
6470 Mechanistic Structural Insights into the UV Induced Apoptosis via Bcl-2 proteins

Authors: Akash Bera, Suraj Singh, Jacinta Dsouza, Ramakrishna V. Hosur, Pushpa Mishra

Abstract:

Ultraviolet C (UVC) radiation induces apoptosis in mammalian cells and it is suggested that the mechanism by which this occurs is the mitochondrial pathway of apoptosis through the release of cytochrome c from the mitochondria into the cytosol. The Bcl-2 family of proteins pro-and anti-apoptotic is the regulators of the mitochondrial pathway of apoptosis. Upon UVC irradiation, the proliferation of apoptosis is enhanced through the downregulation of the anti-apoptotic protein Bcl-xl and up-regulation of Bax. Although the participation of the Bcl-2 family of proteins in apoptosis appears responsive to UVC radiation, to the author's best knowledge, it is unknown how the structure and, effectively, the function of these proteins are directly impacted by UVC exposure. In this background, we present here a structural rationale for the effect of UVC irradiation in restoring apoptosis using two of the relevant proteins, namely, Bid-FL and Bcl-xl ΔC, whose solution structures have been reported previously. Using a variety of biophysical tools such as circular dichroism, fluorescence and NMR spectroscopy, we show that following UVC irradiation, the structures of Bcl-xlΔC and Bid-FL are irreversibly altered. Bcl-xLΔC is found to be more sensitive to UV exposure than Bid-FL. From the NMR data, dramatic structural perturbations (α-helix to β-sheet) are seen to occur in the BH3 binding region, a crucial segment of Bcl-xlΔC which impacts the efficacy of its interactions with pro-apoptotic tBid. These results explain the regulation of apoptosis by UVC irradiation. Our results on irradiation dosage dependence of the structural changes have therapeutic potential for the treatment of cancer.

Keywords: Bid, Bcl-xl, UVC, apoptosis

Procedia PDF Downloads 108
6469 Sparsity-Based Unsupervised Unmixing of Hyperspectral Imaging Data Using Basis Pursuit

Authors: Ahmed Elrewainy

Abstract:

Mixing in the hyperspectral imaging occurs due to the low spatial resolutions of the used cameras. The existing pure materials “endmembers” in the scene share the spectra pixels with different amounts called “abundances”. Unmixing of the data cube is an important task to know the present endmembers in the cube for the analysis of these images. Unsupervised unmixing is done with no information about the given data cube. Sparsity is one of the recent approaches used in the source recovery or unmixing techniques. The l1-norm optimization problem “basis pursuit” could be used as a sparsity-based approach to solve this unmixing problem where the endmembers is assumed to be sparse in an appropriate domain known as dictionary. This optimization problem is solved using proximal method “iterative thresholding”. The l1-norm basis pursuit optimization problem as a sparsity-based unmixing technique was used to unmix real and synthetic hyperspectral data cubes.

Keywords: basis pursuit, blind source separation, hyperspectral imaging, spectral unmixing, wavelets

Procedia PDF Downloads 183
6468 Spatial Optimization of Riverfront Street Based on Inclusive Design

Authors: Lianxue Shi

Abstract:

Riverside Street has the dual characteristics of street space and waterfront space, which is not only a vital place for residents to travel and communicate but also a high-frequency space for people's leisure and entertainment. However, under the development of cities and towns pursuing efficiency, riverfront streets appear to have a variety of problems, such as a lack of multifunctionality, insufficient facilities, and loss of characteristics, which fail to meet the needs of various groups of people, and their inclusiveness is facing a great challenge. It is, therefore, evident that the optimization of riverfront street space from an inclusivity perspective is important to the establishment of a human-centered, high-quality urban space. Therefore, this article starts by exploring the interactive relationship between inclusive design and street space. Based on the analysis of the characteristics of the riverfront street space and people's needs, it proposes the four inclusive design orientations of natural inclusion, group inclusion, spatial inclusion, and social inclusion. It then constructs a design framework for the inclusive optimization of riverfront street space, aiming to create streets that are “safe and accessible, diverse and shared, distinctive and friendly, green and sustainable”. In addition, this article selects riverfront streets in Wansheng District, Chongqing, as a practice case and puts forward specific strategies in four aspects: the creation of an accessible slow-traffic system, the provision of diversified functional services; the reshaping of emotional bonds, and the integration of ecological spaces.

Keywords: inclusiveness design, riverfront street, spatial optimization, street spaces

Procedia PDF Downloads 0
6467 The Effect of Initial Sample Size and Increment in Simulation Samples on a Sequential Selection Approach

Authors: Mohammad H. Almomani

Abstract:

In this paper, we argue the effect of the initial sample size, and the increment in simulation samples on the performance of a sequential approach that used in selecting the top m designs when the number of alternative designs is very large. The sequential approach consists of two stages. In the first stage the ordinal optimization is used to select a subset that overlaps with the set of actual best k% designs with high probability. Then in the second stage the optimal computing budget is used to select the top m designs from the selected subset. We apply the selection approach on a generic example under some parameter settings, with a different choice of initial sample size and the increment in simulation samples, to explore the impacts on the performance of this approach. The results show that the choice of initial sample size and the increment in simulation samples does affect the performance of a selection approach.

Keywords: Large Scale Problems, Optimal Computing Budget Allocation, ordinal optimization, simulation optimization

Procedia PDF Downloads 336
6466 Microstructural and Magnetic Properties of Ni50Mn39Sn11 and Ni50Mn36Sn14 Heusler Alloys

Authors: Mst Nazmunnahar, Juan del Val, Alena Vimmrova, Blanca Hernando, Julian González

Abstract:

We report the microstructural and magnetic properties of Ni50Mn39Sn11 and Ni50Mn36Sn14 ribbon Heusler alloys. Experimental results were obtained by differential scanning calorymetry, X-ray diffraction and vibrating sample magnetometry techniques. The Ni-Mn-Sn system undergoes a martensitic structural transformation in a wide temperature range. For example, for Ni50Mn39Sn11 the start and finish temperatures of the martensitic and austenite phase transformation for ribbon alloy were Ms = 336K , Mf = 328K, As = 335K and Af = 343K whereas no structural transformation is observed for Ni50Mn36Sn14 alloys. Magnetic measurements show the typical ferromagnetic behavior with Curie temperature 207K at low applied field of 50 Oe. The complex behavior exhibited by these Heusler alloys should be ascribed to the strong coupling between magnetism and structure, being their magnetic behavior determined by the distance between Mn atoms.

Keywords: as-cast ribbon, Heusler alloys, magnetic properties, structural transformation

Procedia PDF Downloads 433
6465 Research on Knowledge Graph Inference Technology Based on Proximal Policy Optimization

Authors: Yihao Kuang, Bowen Ding

Abstract:

With the increasing scale and complexity of knowledge graph, modern knowledge graph contains more and more types of entity, relationship, and attribute information. Therefore, in recent years, it has been a trend for knowledge graph inference to use reinforcement learning to deal with large-scale, incomplete, and noisy knowledge graphs and improve the inference effect and interpretability. The Proximal Policy Optimization (PPO) algorithm utilizes a near-end strategy optimization approach. This allows for more extensive updates of policy parameters while constraining the update extent to maintain training stability. This characteristic enables PPOs to converge to improved strategies more rapidly, often demonstrating enhanced performance early in the training process. Furthermore, PPO has the advantage of offline learning, effectively utilizing historical experience data for training and enhancing sample utilization. This means that even with limited resources, PPOs can efficiently train for reinforcement learning tasks. Based on these characteristics, this paper aims to obtain a better and more efficient inference effect by introducing PPO into knowledge inference technology.

Keywords: reinforcement learning, PPO, knowledge inference

Procedia PDF Downloads 217
6464 Experimental Optimization in Diamond Lapping of Plasma Sprayed Ceramic Coatings

Authors: S. Gowri, K. Narayanasamy, R. Krishnamurthy

Abstract:

Plasma spraying, from the point of value engineering, is considered as a cost-effective technique to deposit high performance ceramic coatings on ferrous substrates for use in the aero,automobile,electronics and semiconductor industries. High-performance ceramics such as Alumina, Zirconia, and titania-based ceramics have become a key part of turbine blades,automotive cylinder liners,microelectronic and semiconductor components due to their ability to insulate and distribute heat. However, as the industries continue to advance, improved methods are needed to increase both the flexibility and speed of ceramic processing in these applications. The ceramics mentioned were individually coated on structural steel substrate with NiCr bond coat of 50-70 micron thickness with the final thickness in the range of 150 to 200 microns. Optimal spray parameters were selected based on bond strength and porosity. The 'optimal' processed specimens were super finished by lapping using diamond and green SiC abrasives. Interesting results could be observed as follows: The green SiC could improve the surface finish of lapped surfaces almost as that by diamond in case of alumina and titania based ceramics but the diamond abrasives could improve the surface finish of PSZ better than that by green SiC. The conventional random scratches could be absent in alumina and titania ceramics but in PS those marks were found to be less. However, the flatness accuracy could be improved unto 60 to 85%. The surface finish and geometrical accuracy were measured and modeled. The abrasives in the midrange of their particle size could improve the surface quality faster and better than the particles of size in low and high ranges. From the experimental investigations after lapping process, the optimal lapping time, abrasive size, lapping pressure etc could be evaluated.

Keywords: atmospheric plasma spraying, ceramics, lapping, surface qulaity, optimization

Procedia PDF Downloads 402
6463 Multi-Objective Optimization of a Solar-Powered Triple-Effect Absorption Chiller for Air-Conditioning Applications

Authors: Ali Shirazi, Robert A. Taylor, Stephen D. White, Graham L. Morrison

Abstract:

In this paper, a detailed simulation model of a solar-powered triple-effect LiBr–H2O absorption chiller is developed to supply both cooling and heating demand of a large-scale building, aiming to reduce the fossil fuel consumption and greenhouse gas emissions in building sector. TRNSYS 17 is used to simulate the performance of the system over a typical year. A combined energetic-economic-environmental analysis is conducted to determine the system annual primary energy consumption and the total cost, which are considered as two conflicting objectives. A multi-objective optimization of the system is performed using a genetic algorithm to minimize these objectives simultaneously. The optimization results show that the final optimal design of the proposed plant has a solar fraction of 72% and leads to an annual primary energy saving of 0.69 GWh and annual CO2 emissions reduction of ~166 tonnes, as compared to a conventional HVAC system. The economics of this design, however, is not appealing without public funding, which is often the case for many renewable energy systems. The results show that a good funding policy is required in order for these technologies to achieve satisfactory payback periods within the lifetime of the plant.

Keywords: economic, environmental, multi-objective optimization, solar air-conditioning, triple-effect absorption chiller

Procedia PDF Downloads 222
6462 A Resource Optimization Strategy for CPU (Central Processing Unit) Intensive Applications

Authors: Junjie Peng, Jinbao Chen, Shuai Kong, Danxu Liu

Abstract:

On the basis of traditional resource allocation strategies, the usage of resources on physical servers in cloud data center is great uncertain. It will cause waste of resources if the assignment of tasks is not enough. On the contrary, it will cause overload if the assignment of tasks is too much. This is especially obvious when the applications are the same type because of its resource preferences. Considering CPU intensive application is one of the most common types of application in the cloud, we studied the optimization strategy for CPU intensive applications on the same server. We used resource preferences to analyze the case that multiple CPU intensive applications run simultaneously, and put forward a model which can predict the execution time for CPU intensive applications which run simultaneously. Based on the prediction model, we proposed the method to select the appropriate number of applications for a machine. Experiments show that the model can predict the execution time accurately for CPU intensive applications. To improve the execution efficiency of applications, we propose a scheduling model based on priority for CPU intensive applications. Extensive experiments verify the validity of the scheduling model.

Keywords: cloud computing, CPU intensive applications, resource optimization, strategy

Procedia PDF Downloads 264
6461 On the Homology Modeling, Structural Function Relationship and Binding Site Prediction of Human Alsin Protein

Authors: Y. Ruchi, A. Prerna, S. Deepshikha

Abstract:

Amyotrophic lateral sclerosis (ALS), also known as “Lou Gehrig’s disease”. It is a neurodegenerative disease associated with degeneration of motor neurons in the cerebral cortex, brain stem, and spinal cord characterized by distal muscle weakness, atrophy, normal sensation, pyramidal signs and progressive muscular paralysis reflecting. ALS2 is a juvenile autosomal recessive disorder, slowly progressive, that maps to chromosome 2q33 and is associated with mutations in the alsin gene, a putative GTPase regulator. In this paper we have done homology modeling of alsin2 protein using multiple templates (3KCI_A, 4LIM_A, 402W_A, 4D9S_A, and 4DNV_A) designed using the Prime program in Schrödinger software. Further modeled structure is used to identify effective binding sites on the basis of structural and physical properties using sitemap program in Schrödinger software, structural and function analysis is done by using Prosite and ExPASy server that gives insight into conserved domains and motifs that can be used for protein classification. This paper summarizes the structural, functional and binding site property of alsin2 protein. These binding sites can be potential drug target sites and can be used for docking studies.

Keywords: ALS, binding site, homology modeling, neuronal degeneration

Procedia PDF Downloads 375
6460 Molecular Dynamics Simulations of the Structural, Elastic and Thermodynamic Properties of Cubic GaBi

Authors: M. Zemouli, K. Amara, M. Elkeurti, Y. Benallou

Abstract:

We present the molecular dynamic simulations results of the structural and dynamical properties of the zinc-blende GaBi over a wide range of temperature (300-1000) K. Our simulation where performed in the framework of the three-body Tersoff potential, which accurately reproduces the lattice constants and elastic constants of the GaBi. A good agreement was found between our calculated results and the available theoretical data of the lattice constant, the bulk modulus and the cohesive energy. Our study allows us to predict the thermodynamic properties such as the specific heat and the lattice thermal expansion. In addition, this method allows us to check its ability to predict the phase transition of this compound. In particular, the transition pressure to the rock-salt phase is calculated and the results are compared with other available works.

Keywords: Gallium compounds, molecular dynamics simulations, interatomic potential thermodynamic properties, structural phase transition

Procedia PDF Downloads 426
6459 The Bernstein Expansion for Exponentials in Taylor Functions: Approximation of Fixed Points

Authors: Tareq Hamadneh, Jochen Merker, Hassan Al-Zoubi

Abstract:

Bernstein's expansion for exponentials in Taylor functions provides lower and upper optimization values for the range of its original function. these values converge to the original functions if the degree is elevated or the domain subdivided. Taylor polynomial can be applied so that the exponential is a polynomial of finite degree over a given domain. Bernstein's basis has two main properties: its sum equals 1, and positive for all x 2 (0; 1). In this work, we prove the existence of fixed points for exponential functions in a given domain using the optimization values of Bernstein. The Bernstein basis of finite degree T over a domain D is defined non-negatively. Any polynomial p of degree t can be expanded into the Bernstein form of maximum degree t ≤ T, where we only need to compute the coefficients of Bernstein in order to optimize the original polynomial. The main property is that p(x) is approximated by the minimum and maximum Bernstein coefficients (Bernstein bound). If the bound is contained in the given domain, then we say that p(x) has fixed points in the same domain.

Keywords: Bernstein polynomials, Stability of control functions, numerical optimization, Taylor function

Procedia PDF Downloads 119
6458 Optimization of Floor Heating System in the Incompressible Turbulent Flow Using Constructal Theory

Authors: Karim Farahmandfar, Hamidolah Izadi, Mohammadreza Rezaei, Amin Ardali, Ebrahim Goshtasbi Rad, Khosro Jafarpoor

Abstract:

Statistics illustrates that the higher amount of annual energy consumption is related to surmounting the demand in buildings. Therefore, it is vital to economize the energy consumption and also find the solution with regard to this issue. One of the systems for the sake of heating the building is floor heating. As a matter of fact, floor heating performance is based on convection and radiation. Actually, in addition to creating a favorable heating condition, this method leads to energy saving. It is the goal of this article to outline the constructal theory and introduce the optimization method in branch networks for floor heating. There are several steps in order to gain this purpose. First of all, the pressure drop through the two points of the network is calculated. This pressure drop is as a function of pipes diameter and other parameters. After that, the amount of heat transfer is determined. Consequently, as a result of the combination of these two functions, the final function will be determined. It is necessary to mention that flow is laminar.

Keywords: constructal theory, optimization, floor heating system, turbulent flow

Procedia PDF Downloads 295
6457 Statistical Optimization of Vanillin Production by Pycnoporus Cinnabarinus 1181

Authors: Swarali Hingse, Shraddha Digole, Uday Annapure

Abstract:

The present study investigates the biotransformation of ferulic acid to vanillin by Pycnoporus cinnabarinus and its optimization using one-factor-at-a-time method as well as statistical approach. Effect of various physicochemical parameters and medium components was studied using one-factor-at-a-time method. Screening of the significant factors was carried out using L25 Taguchi orthogonal array and then these selected significant factors were further optimized using response surface methodology (RSM). Significant media components obtained using Taguchi L25 orthogonal array were glucose, KH2PO4 and yeast extract. Further, a Box Behnken design was used to investigate the interactive effects of the three most significant media components. The final medium obtained after optimization using RSM containing glucose (34.89 g/L), diammonium tartrate (1 g/L), yeast extract (1.47 g/L), MgSO4•7H2O (0.5 g/L), KH2PO4 (0.15 g/L), and CaCl2•2H2O (20 mg/L) resulted in amplification of vanillin production from 30.88 mg/L to 187.63 mg/L.

Keywords: ferulic acid, pycnoporus cinnabarinus, response surface methodology, vanillin

Procedia PDF Downloads 366
6456 Effect of the Initial Billet Shape Parameters on the Final Product in a Backward Extrusion Process for Pressure Vessels

Authors: Archana Thangavelu, Han-Ik Park, Young-Chul Park, Joon-Hong Park

Abstract:

In this numerical study, we have proposed a method for evaluation of backward extrusion process of pressure vessel made up of steel. Demand for lighter and stiffer products have been increasing in the last years especially in automobile engineering. Through detailed finite element analysis, effective stress, strain and velocity profile have been obtained with optimal range. The process design of a forward and backward extrusion axe-symmetric part has been studied. Forging is mainly carried out because forged products are highly reliable and possess superior mechanical properties when compared to normal products. Performing computational simulations of 3D hot forging with various dimensions of billet and optimization of weight is carried out using Taguchi Orthogonal Array (OA) Optimization technique. The technique used in this study can be used for newly developed materials to investigate its forgeability for much complicated shapes in closed hot die forging process.

Keywords: backward extrusion, hot forging, optimization, finite element analysis, Taguchi method

Procedia PDF Downloads 294
6455 Research on the Development and Space Optimization of Rental-Type Public Housing in Hangzhou

Authors: Xuran Zhang, Huiru Chen

Abstract:

In recent years, China has made great efforts to cultivate and develop the housing rental market, especially the rental-type public housing, which has been paid attention to by all sectors of the society. This paper takes Hangzhou rental-type public housing as the research object, and divides it into three development stages according to the different supply modes of rental-type public housing. Through data collection and field research, the paper summarizes the spatial characteristics of rental-type public housing from the five perspectives of spatial planning, spatial layout, spatial integration, spatial organization and spatial configuration. On this basis, the paper proposes the optimization of the spatial layout. The study concludes that the spatial layout of rental-type public housing should be coordinated with the development of urban planning. When planning and constructing, it is necessary to select more mixed construction modes, to be properly centralized, and to improve the surrounding transportation service facilities.  It is hoped that the recommendations in this paper will provide a reference for the further development of rental-type public housing in Hangzhou.

Keywords: Hangzhou, rental-type public housing, spatial distribution, spatial optimization

Procedia PDF Downloads 308
6454 Expected Present Value of Losses in the Computation of Optimum Seismic Design Parameters

Authors: J. García-Pérez

Abstract:

An approach to compute optimum seismic design parameters is presented. It is based on the optimization of the expected present value of the total cost, which includes the initial cost of structures as well as the cost due to earthquakes. Different types of seismicity models are considered, including one for characteristic earthquakes. Uncertainties are included in some variables to observe the influence on optimum values. Optimum seismic design coefficients are computed for three different structural types representing high, medium and low rise buildings, located near and far from the seismic sources. Ordinary and important structures are considered in the analysis. The results of optimum values show an important influence of seismicity models as well as of uncertainties on the variables.

Keywords: importance factors, optimum parameters, seismic losses, seismic risk, total cost

Procedia PDF Downloads 273
6453 Gamma Irradiation Effects on the Crystal Structural and Transport Properties of Bi₂Te₃ Thin Films Grown by Thermal Evaporation

Authors: Shoroog Alraddadi

Abstract:

In this study, the effect of gamma irradiation on the structural and transport properties of Bismuth Telluride (Bi₂Te₃) thin films was investigated. Bi₂Te₃ thin films with thicknesses varying from 100 nm to 500 nm were grown using thermal evaporation in vacuum 10⁻⁵ Torr. The films were irradiated by Gamma radiation with different doses (50, 200, and 500 kGy). The crystal structure of Bi₂Te₃ thin films was studied by XRD diffraction. It was showed that the degree of crystallinity of films increases as the doses increase. Furthermore, it was found that the electrical conductivity of Bi₂Te₃ increase as the doses increase. From these results, it can be concluding that the effect of radiation on the structural and transport properties was positive at the levels of irradiation used.

Keywords: bismuth telluride, gamma irradiation, thin film, transport properties

Procedia PDF Downloads 143
6452 Concrete Mixes for Sustainability

Authors: Kristyna Hrabova, Sabina Hüblova, Tomas Vymazal

Abstract:

Structural design of concrete structure has the result in qualities of structural safety and serviceability, together with durability, robustness, sustainability and resilience. A sustainable approach is at the heart of the research agenda around the world, and the Fibrillation Commission is also working on a new model code 2020. Now it is clear that the effects of mechanical, environmental load and even social coherence need to be reflected and included in the designing and evaluating structures. This study aimed to present the methodology for the sustainability assessment of various concrete mixtures.

Keywords: concrete, cement, sustainability, Model Code 2020

Procedia PDF Downloads 160
6451 Molecular Dynamics Simulations of the Structural, Elastic, and Thermodynamic Properties of Cubic AlBi

Authors: M. Zemouli, K. Amara, M. Elkeurti, Y. Benallou

Abstract:

We present a theoretical study of the structural, elastic and thermodynamic properties of the zinc-blende AlBi for a wide temperature range. The simulation calculation is performed in the framework of the molecular dynamics method using the three-body Tersoff potential which reproduces provide, with reasonable accuracy, the lattice constants and elastic constants. Our results for the lattice constant, the bulk modulus and cohesive energy are in good agreement with other theoretical available works. Other thermodynamic properties such as the specific heat and the lattice thermal expansion can also be predicted. In addition, this method allows us to check its ability to predict the phase transition of this compound. In particular, the transition pressure to the rock-salt phase is calculated and the results are compared with other available works.

Keywords: aluminium compounds, molecular dynamics simulations, interatomic potential, thermodynamic properties, structural phase transition

Procedia PDF Downloads 291
6450 Optimization of Platinum Utilization by Using Stochastic Modeling of Carbon-Supported Platinum Catalyst Layer of Proton Exchange Membrane Fuel Cells

Authors: Ali Akbar, Seungho Shin, Sukkee Um

Abstract:

The composition of catalyst layers (CLs) plays an important role in the overall performance and cost of the proton exchange membrane fuel cells (PEMFCs). Low platinum loading, high utilization, and more durable catalyst still remain as critical challenges for PEMFCs. In this study, a three-dimensional material network model is developed to visualize the nanostructure of carbon supported platinum Pt/C and Pt/VACNT catalysts in pursuance of maximizing the catalyst utilization. The quadruple-phase randomly generated CLs domain is formulated using quasi-random stochastic Monte Carlo-based method. This unique statistical approach of four-phase (i.e., pore, ionomer, carbon, and platinum) model is closely mimic of manufacturing process of CLs. Various CLs compositions are simulated to elucidate the effect of electrons, ions, and mass transport paths on the catalyst utilization factor. Based on simulation results, the effect of key factors such as porosity, ionomer contents and Pt weight percentage in Pt/C catalyst have been investigated at the represented elementary volume (REV) scale. The results show that the relationship between ionomer content and Pt utilization is in good agreement with existing experimental calculations. Furthermore, this model is implemented on the state-of-the-art Pt/VACNT CLs. The simulation results on Pt/VACNT based CLs show exceptionally high catalyst utilization as compared to Pt/C with different composition ratios. More importantly, this study reveals that the maximum catalyst utilization depends on the distance spacing between the carbon nanotubes for Pt/VACNT. The current simulation results are expected to be utilized in the optimization of nano-structural construction and composition of Pt/C and Pt/VACNT CLs.

Keywords: catalyst layer, platinum utilization, proton exchange membrane fuel cell, stochastic modeling

Procedia PDF Downloads 105
6449 Structural Health Monitoring of Buildings–Recorded Data and Wave Method

Authors: Tzong-Ying Hao, Mohammad T. Rahmani

Abstract:

This article presents the structural health monitoring (SHM) method based on changes in wave traveling times (wave method) within a layered 1-D shear beam model of structure. The wave method measures the velocity of shear wave propagating in a building from the impulse response functions (IRF) obtained from recorded data at different locations inside the building. If structural damage occurs in a structure, the velocity of wave propagation through it changes. The wave method analysis is performed on the responses of Torre Central building, a 9-story shear wall structure located in Santiago, Chile. Because events of different intensity (ambient vibrations, weak and strong earthquake motions) have been recorded at this building, therefore it can serve as a full-scale benchmark to validate the structural health monitoring method utilized. The analysis of inter-story drifts and the Fourier spectra for the EW and NS motions during 2010 Chile earthquake are presented. The results for the NS motions suggest the coupling of translation and torsion responses. The system frequencies (estimated from the relative displacement response of the 8th-floor with respect to the basement from recorded data) were detected initially decreasing approximately 24% in the EW motion. Near the end of shaking, an increase of about 17% was detected. These analysis and results serve as baseline indicators of the occurrence of structural damage. The detected changes in wave velocities of the shear beam model are consistent with the observed damage. However, the 1-D shear beam model is not sufficient to simulate the coupling of translation and torsion responses in the NS motion. The wave method is proven for actual implementation in structural health monitoring systems based on carefully assessing the resolution and accuracy of the model for its effectiveness on post-earthquake damage detection in buildings.

Keywords: Chile earthquake, damage detection, earthquake response, impulse response function, shear beam model, shear wave velocity, structural health monitoring, torre central building, wave method

Procedia PDF Downloads 353