Search results for: structural vector autoregression

Authors: Abid I. Abu-Tair, Gavin M. Wilde, John M. Kinuthia

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Urban Search and Rescue (USAR) is a functional capability that has been developed to allow the United Kingdom Fire and Rescue Service to deal with ‘major incidents’ primarily involving structural collapse. The nature of the work undertaken by USAR means that staying out of a damaged or collapsed building structure is not usually an option for search and rescue personnel. As a result, there is always a risk that they could become victims. For this paper, a systematic and investigative review using desk research was undertaken to explore the role which structural engineering can play in assisting search and rescue personnel to conduct structural assessments when in the field. The focus is on how search and rescue personnel can assess damaged and collapsed building structures, not just in terms of the structural damage that may be countered, but also in relation to structural stability. Natural disasters, accidental emergencies, acts of terrorism and other extreme events can vary significantly in nature and ferocity, and can cause a wide variety of damage to building structures. It is not possible or, even realistic, to provide search and rescue personnel with definitive guidelines and procedures to assess damaged and collapsed building structures as there are too many variables to consider. However, understanding what implications damage may have upon the structural stability of a building structure will enable search and rescue personnel to judge better and quantify the risk from a life-safety standpoint. It is intended that this will allow search and rescue personnel to make informed decisions and ensure every effort is made to mitigate risk so that they do not become victims.

Keywords: damaged and collapsed building structures, life safety, quantifying risk, search and rescue personnel, structural assessments in the field

Procedia PDF Downloads 386

Authors: Sang-Wook Han, Zhenlan Jin, In-Hui Hwang, Chang-In Park

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We examined structural and electrical properties of uniformly-oriented VO₂/ZnO nanostructures. VO₂ was deposited on ZnO templates by using a direct current-sputtering deposition. Scanning electron microscope and transmission electron microscope measurements indicated that b-oriented VO₂ were uniformly crystallized on ZnO templates with different lengths. VO₂/ZnO formed nanorods on ZnO nanorods with length longer than 250 nm. X-ray absorption fine structure at V K edge of VO₂/ZnO showed M1 and R phases of VO₂ at 30 and 100 ℃, respectively, suggesting structural phase transition between temperatures. Temperature-dependent resistance measurements of VO₂/ZnO nanostructures revealed metal-to-insulator transition at 65 ℃ and 55 ℃ during heating and cooling, respectively, regardless of ZnO length. The bond lengths of V-O and V-V pairs in VO₂/ZnO nanorods were somewhat distorted, and a substantial amount of structural disorder existed in the atomic pairs, compared to those of VO₂ films without ZnO. Resistance from VO₂/ZnO nanorods revealed a sharp MIT near 65 ℃ during heating and a hysteresis behavior. The resistance results suggest that microchannel for charge carriers exist nearly room temperature during cooling. VO₂/ZnO nanorods are quite stable and reproducible so that they can be widely used for practical applications to electronic devices, gas sensors, and ultra-fast switches, as examples.

Keywords: metal-to-insulator transition, VO₂, ZnO, XAFS, structural-phase transition

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Authors: Ruby Priya, O. P. Pandey

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Herein, we report the structural and luminescent properties of undoped and Eu doped SrY₂O₄ phosphors. The phosphors are synthesized via the combustion synthesis route using glycine as a fuel. The structural, morphological, and optical characterizations are done via X-ray diffraction (XRD), scanning electron microscopy (SEM), photoluminescent (PL) techniques. The pure phase SrY₂O₄ is obtained at 1100℃, below which impure phases such as Y₂O₃ and SrO were dominant. All the phosphors are excited under UV excitation and exhibited intense emission around 611 nm, which is the typical transition of Eu ions. The phase formation of the synthesized phosphors is studied via analyzing XRD patterns. The as-synthesized phosphors find tremendous applications in optoelectronic devices, light-emitting diodes, and sensors.

Keywords: combustion, europium, glycine, luminescence

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Authors: Rims Janeliukstis, Deniss Mironovs, Andrejs Kovalovs

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Operational Modal Analysis (OMA) is widely applied as a method for Structural Health Monitoring for structural damage identification and assessment by tracking the changes of the identified modal parameters over time. Unfortunately, modal parameters also depend on such external factors as temperature and loads. Any structural condition assessment using modal parameters should be done taking into consideration those external factors, otherwise there is a high chance of false positives. A method of structural reliability assessment based on anomaly detection technique called Machalanobis Squared Distance (MSD) is proposed. It requires a set of reference conditions to learn healthy state of a structure, which all future parameters are compared to. In this study, structural modal parameters (natural frequency and mode shape), as well as ambient temperature and loads acting on the structure are used as features. Numerical tests were performed on a finite element model of a carbon fibre reinforced polymer composite beam with delamination damage at various locations and of various severities. The advantages of the demonstrated approach include relatively few computational steps, ability to distinguish between healthy and damaged conditions and discriminate between different damage severities. It is anticipated to be promising in reliability assessment of massively produced structural parts.

Keywords: operational modal analysis, reliability assessment, anomaly detection, damage, mahalanobis squared distance

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Authors: Mizam Doğan

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In service life; structures can be damaged if they are subjected to dead and live loads which are greater than design values. For preventing this case; possible loads must be correctly calculated, structure must be designed according to determined loads, and structure must not be used out of its function. If loading case of the structure changes when its function changes; it must be reinforced for continuing it is new function. Reinforcement is a process that is made by increasing the existing strengths of structural system elements of the structure as reinforced concrete walls, beams, and slabs. Reinforcement can be done by casting reinforced concrete, placing steel and fiber structural elements. In this paper, reinforcing of columns and slabs of a structure of which function is changed is studied step by step. This reinforcement is made for increasing vertical and lateral load carrying capacity of the building. Not for repairing damaged structural system.

Keywords: strengthening, RC slabs, seismic load, steel beam, structural irregularity

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Authors: Brandtner-Hafner Martin

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Adhesives have established themselves as an innovative joining technology in the industry. Their strengths lie in joining different materials, avoiding structural weakening as in welding or screwing, and enabling lightweight construction methods. Now there are a variety of ways to improve the efficiency and effectiveness of bonded joints. One way is to add fiber fillers. This leads to an improvement in adhesion and cohesion (structural integrity). In this study, the effectiveness of fiber-modified adhesives for bonding different construction materials is reviewed. A series of experimental tests were performed using the fracture analytical GF principle to study the adhesive bonding safety and performance of the joint. Three different structural adhesive systems based on epoxy, CA/A hybrid, and PUR were modified with different fiber materials on different substrates. The results show that significant performance improvements can be achieved and that bonding reliability can be sustainably increased.

Keywords: fiber-modified adhesives, bonding safety, GF-principle, fracture analysis

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Authors: Muhammad Fawad

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Monitoring and structural health assessment are the primary requirements for the performance evaluation of damaged bridges. This paper highlights the case study of a damaged Reinforced Concrete (RC) bridge structure where the Finite element (FE) modelling of this structure was done using the material properties extracted by the in-situ testing. Analysis was carried out to evaluate the bridge damage. On the basis of FE analysis results, this study proposes a proper Structural Health Monitoring (SHM) system that will extend the life cycle of the bridge with minimal repair costs and reduced risk of failure. This system is based on the installation of three different types of sensors: Liquid Levelling sensors (LLS) for measurement of vertical displacement, Distributed Fiber Optic Sensors (DFOS) for crack monitoring, and Weigh in Motion (WIM) devices for monitoring of moving loads on the bridge.

Keywords: bridges, reinforced concrete, finite element method, structural health monitoring, sensors

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Authors: S. Louhibi-Fasla, H. Achour, B. Amrani

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The purpose of this work is to provide some additional information to the existing data on the physical properties of AlBi with state-of-the-art first-principles method of the full potential linear augmented plane wave (FPLAPW). Additionally to the structural properties, the electronic properties have also been investigated. The dependence of the volume, the bulk modulus, the variation of the thermal expansion α, as well as the Debye temperature are successfully obtained in the whole range from 0 to 30 GPa and temperature range from 0 to 1200 K. The latter are the basis of solid-state science and industrial applications and their study is of importance to extend our knowledge on their specific behaviour when undergoing severe constraints of high pressure and high temperature environments.

Keywords: AlBi, FP-LAPW, structural properties, electronic properties

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Authors: Bingchun Liu, Pei-Chann Chang, Natasha Huang, Dun Li

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Machine Learning and Data Mining are the two important tools for extracting useful information and knowledge from large datasets. In machine learning, classification is a wildly used technique to predict qualitative variables and is generally preferred over regression from an operational point of view. Due to the enormous increase in air pollution in various countries especially China, Air Quality Classification has become one of the most important topics in air quality research and modelling. This study aims at introducing a hybrid classification model based on information theory and Support Vector Machine (SVM) using the air quality data of four cities in China namely Beijing, Guangzhou, Shanghai and Tianjin from Jan 1, 2014 to April 30, 2016. China's Ministry of Environmental Protection has classified the daily air quality into 6 levels namely Serious Pollution, Severe Pollution, Moderate Pollution, Light Pollution, Good and Excellent based on their respective Air Quality Index (AQI) values. Using the information theory, information gain (IG) is calculated and feature selection is done for both categorical features and continuous numeric features. Then SVM Machine Learning algorithm is implemented on the selected features with cross-validation. The final evaluation reveals that the IG and SVM hybrid model performs better than SVM (alone), Artificial Neural Network (ANN) and K-Nearest Neighbours (KNN) models in terms of accuracy as well as complexity.

Keywords: machine learning, air quality classification, air quality index, information gain, support vector machine, cross-validation

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Authors: Jakub Bartus, Jaroslav Odrobinak

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In general, composite steel and concrete structures present an effective structural solution utilizing the full potential of both materials. As they have numerous advantages on the construction side, they can greatly reduce the overall cost of construction, which has been the main objective of the last decade, highlighted by the current economic and social crisis. The study represents not only an analysis of composite beams’ behavior having web openings but emphasizes the influence of these openings on the total strain distribution at the level of the steel bottom flange as well. The major investigation was focused on a change in structural performance with respect to various layouts of openings. Examining this structural modification, an improvement of load carrying capacity of composite beams was a prime objective. The study is divided into analytical and numerical parts. The analytical part served as an initial step into the design process of composite beam samples, in which optimal dimensions and specific levels of utilization in individual stress states were taken into account. The numerical part covered the discretization of the preset structural issue in the form of a finite element (FE) model using beam and shell elements accounting for material non–linearities. As an outcome, several conclusions were drawn describing and explaining the effect of web opening presence on the structural performance of composite beams.

Keywords: beam, steel flange, total strain, web opening

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Authors: Houxiang Zhu, Chun Liang

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The CRISPR-Cpf1 system has been successfully applied in genome editing. However, target efficiency of the CRISPR-Cpf1 system varies among different gRNA sequences. The published CRISPR-Cpf1 gRNA data was reanalyzed. Many sequences and structural features of gRNAs (e.g., the position-specific nucleotide composition, position-nonspecific nucleotide composition, GC content, minimum free energy, and melting temperature) correlated with target efficiency were found. Using machine learning technology, a support vector machine (SVM) model was created to predict target efficiency for any given gRNAs. The first web service application, CRISPR-DT (CRISPR DNA Targeting), has been developed to help users design optimal gRNAs for the CRISPR-Cpf1 system by considering both target efficiency and specificity. CRISPR-DT will empower researchers in genome editing.

Keywords: CRISPR-Cpf1, genome editing, target efficiency, target specificity

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Authors: Serpil Türkyılmaz, Mesut Balıbey

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In this study, long memory properties in volatility of Turkey Stock Market are being examined through the FIGARCH, FIEGARCH and FIAPARCH models under different distribution assumptions as normal and skewed student-t distributions. Furthermore, structural changes in volatility of Turkey Stock Market are investigated. The results display long memory property and the presence of asymmetric effects of shocks in volatility of Turkey Stock Market.

Keywords: FIAPARCH model, FIEGARCH model, FIGARCH model, structural break

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Authors: Rafik Djemili, Hocine Bourouba, M. C. Amara Korba

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In this paper, we present a method in order to classify EEG signals for Brain-Computer Interfaces (BCI). EEG signals are first processed by means of spectral estimation methods to derive reliable features before classification step. Spectral estimation methods used are standard periodogram and the periodogram calculated by the Welch method; both methods are compared with Logarithm of Band Power (logBP) features. In the method proposed, we apply Linear Discriminant Analysis (LDA) followed by Support Vector Machine (SVM). Classification accuracy reached could be as high as 85%, which proves the effectiveness of classification of EEG signals based BCI using spectral methods.

Keywords: brain-computer interface, motor imagery, electroencephalogram, linear discriminant analysis, support vector machine

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Authors: Ibrahim Djelloul Berkane

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A survey was conducted to assess the presence of the virus in Citrus tristeza one of the main citrus regions of Algeria, namely the Chlef region, using the technique of Direct Tissue Print Immunoprinting Assay (DTBIA) and the Double Sandwich ELISA antibodies. A nursery citrus, lumber yards, and commercial orchards, which are the main varieties cultivated citrus were subjected to samples collected samples for laboratory analysis. 0.91% of the plants tested orchards were infected with CTV, while no positive case was detected at the nursery the yard, however, it is reported that an alarming rate of 10,5% of orchards tested at the common Chettia were infected with tristeza virus. The investigation was launched to identify the vector species tristeza revealed the presence of a vector is important Aphis gossypii.

Keywords: aphis, chlef, citrus, DAS-ELISA, DTBIA, tristeza

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Authors: N. Jinesh, K. Shankar

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This article presents a method of using the one dimensional piezo-electric patch on beam model for structural identification. A hybrid element constituted of one dimensional beam element and a PZT sensor is used with reduced material properties. This model is convenient and simple for identification of beams. Accuracy of this element is first verified against a corresponding 3D finite element model (FEM). The structural identification is carried out as an inverse problem whereby parameters are identified by minimizing the deviation between the predicted and measured voltage response of the patch, when subjected to excitation. A non-classical optimization algorithm Particle Swarm Optimization is used to minimize this objective function. The signals are polluted with 5% Gaussian noise to simulate experimental noise. The proposed method is applied on beam structure and identified parameters are stiffness and damping. The model is also validated experimentally.

Keywords: inverse problem, particle swarm optimization, PZT patches, structural identification

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Authors: Sittampalam Manoharan, Gary Chai, Sanaul Chowdhury, Andrew Golding

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The primary objective of this paper is to present a simplified approach to develop the structural deterioration model using traffic speed deflectometer data for flexible pavements. Maintaining assets to meet functional performance is not economical or sustainable in the long terms, and it would end up needing much more investments for road agencies and extra costs for road users. Performance models have to be included for structural and functional predicting capabilities, in order to assess the needs, and the time frame of those needs. As such structural modelling plays a vital role in the prediction of pavement performance. A structural condition is important for the prediction of remaining life and overall health of a road network and also major influence on the valuation of road pavement. Therefore, the structural deterioration model is a critical input into pavement management system for predicting pavement rehabilitation needs accurately. The Traffic Speed Deflectometer (TSD) is a vehicle-mounted Doppler laser system that is capable of continuously measuring the structural bearing capacity of a pavement whilst moving at traffic speeds. The device’s high accuracy, high speed, and continuous deflection profiles are useful for network-level applications such as predicting road rehabilitations needs and remaining structural service life. The methodology adopted in this model by utilizing time series TSD maximum deflection (D0) data in conjunction with rutting, rutting progression, pavement age, subgrade strength and equivalent standard axle (ESA) data. Then, regression analyses were undertaken to establish a correlation equation of structural deterioration as a function of rutting, pavement age, seal age and equivalent standard axle (ESA). This study developed a simple structural deterioration model which will enable to incorporate available TSD structural data in pavement management system for developing network-level pavement investment strategies. Therefore, the available funding can be used effectively to minimize the whole –of- life cost of the road asset and also improve pavement performance. This study will contribute to narrowing the knowledge gap in structural data usage in network level investment analysis and provide a simple methodology to use structural data effectively in investment decision-making process for road agencies to manage aging road assets.

Keywords: adjusted structural number (SNP), maximum deflection (D0), equant standard axle (ESA), traffic speed deflectometer (TSD)

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Authors: Nam-Hee Kim, Jang-Hoon Ko, Kwon-Hee Lee

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A relief valve is a mechanical element to keep safety by controlling high pressure. Usually, the high pressure is relieved by using the spring force and letting the fluid to flow from another way out of system. When its normal pressure is reached, the relief valve can return to initial state. The relief valve in this study has been applied for pressure vessel, evaporator, piping line, etc. The relief valve should be designed for smooth operation and should satisfy the structural safety requirement under operating condition. In general, the structural analysis is performed by following fluid flow analysis. In this process, the FSI (Fluid-Structure Interaction) is required to input the force obtained from the output of the flow analysis. Firstly, this study predicts the velocity profile and the pressure distribution in the given system. In this study, the assumptions for flow analysis are as follows: • The flow is steady-state and three-dimensional. • The fluid is Newtonian and incompressible. • The walls of the pipe and valve are smooth. The flow characteristics in this relief valve does not induce any problem. The commercial software ANSYS/CFX is utilized for flow analysis. On the contrary, very high pressure may cause structural problem due to severe stress. The relief valve is made of body, bonnet, guide, piston and nozzle, and its material is stainless steel. To investigate its structural safety, the worst case loading is considered as the pressure of 700 bar. The load is applied to inside the valve, which is greater than the load obtained from FSI. The maximum stress is calculated as 378 MPa by performing the finite element analysis. However, the value is greater than its allowable value. Thus, an alternative design is suggested to improve the structural performance through case study. We found that the sensitive design variable to the strength is the shape of the nozzle. The case study is to vary the size of the nozzle. Finally, it can be seen that the suggested design satisfy the structural design requirement. The FE analysis is performed by using the commercial software ANSYS/Workbench.

Keywords: relief valve, structural analysis, structural design, strength, safety factor

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Authors: Abderazak Guettaf

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The mathematical models of the physical phenomena interacting in inductive plasma were described by the physics equations of the continuous mediums. A 3D model based on magnetic potential vector and electric scalar potential (A, V) formulation is used. The finished volume method is applied to electromagnetic equation, to obtain the field distribution inside the plasma. The numerical results of the method developed on a basic model designed starting from a real three-dimensional model were exposed. From the mathematical model 3D spreading assumptions and boundary conditions, we evaluated the electric field in the load and we have developed a numerical code made under the MATLAB environment, all verifying the effectiveness and validity of this code.

Keywords: electric field, 3D magnetic potential vector and electric scalar potential (A, V) formulation, finished volumes, annular plasma

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Authors: Bessaad Taieb, Benbouali Abderrahmen

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Fuzzy controllers are a powerful tool for controlling complex processes. However, its robustness capacity remains moderately limited because it loses its property for large ranges of parametric variations. In this paper, the proposed control method is designed, based on a fuzzy adaptive controller used as a remedy for this problem. For increase the robustness of the vector control and to maintain the performance of the five-phase asynchronous machine despite the presence of disturbances (variation of rotor resistance, rotor inertia variations, sudden variations in the load etc.), by applying the method of behaviour model control (BMC). The results of simulation show that the fuzzy adaptive control provides best performance and has a more robustness as the fuzzy (FLC) and as a conventional (PI) controller.

Keywords: fuzzy adaptive control, behaviour model control, vector control, five-phase asynchronous machine

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Authors: Nandini Sharma

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Monitoring the characteristics of a nanostructured material comprises measurements of structural, morphological, mechanical, optical and electronic properties of the synthesized nanopowder and different layers and coatings of nanomaterials coated on transparent conducting oxides (TCOs) substrates like fluorine doped tin oxide (FTO) or Indium doped tin oxide (ITO). This article focuses on structural and optical characterization with emphasis on measurements of the photocatalytic efficiency as a photocatalyst and their interpretation to extract relevant information about various TCOs and materials, their emitter regions, and surface passivation. It also covers a brief description of techniques based on photoluminescence that can portray high resolution pictorial graphs for application as solar energy devices. With the advancement in the scientific techniques, detailed information about the structural, morphological, and optical properties can be investigated, which is further useful for engineering and designing of an efficient device. The common principles involved in the prevalent characterization techniques aid to illustrate the range of options that can be broadened in near future for acurate device characterization and diagnosis.

Keywords: characterization, structural, optical, nanomaterial

Procedia PDF Downloads 134

Authors: Muhammad Sohail Sajid, Qurat-ul-Ain, Zafar Iqbal, Muhammad Nisar Khan, Asma Kausar, Adil Ejaz

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Rickettsiosis, caused by a Spotted Fever Group Rickettsiae (SFGR), is considered as an emerging infectious disease from public and veterinary perspective. The present study reports distribution of SFGR in the host (buffalo and cattle) and vector (ticks) population determined through gene specific amplification through PCR targeting outer membrane protein (ompA). Tick and blood samples were collected using standard protocols through convenient sampling from district Faisalabad. Ticks were dissected to extract salivary glands (SG). Blood and tick SG pools were subjected to DNA extraction and amplification of ompA using PCR. Overall prevalence of SFGR was reported as 21.5% and 33.6 % from blood and ticks, respectively. Hyalomma anatolicum was more prevalent tick associated with SFGR as compared to Rhipicephalus sp. Higher prevalence of SFGR was reported in cattle (25%) population as compared to that of buffalo (17.07%). On seasonal basis, high SFGR prevalence was recorded during spring season (48.1%, 26.32%, 17.76%) as compared to winter (27.9%, 21.43%, 15.38%) in vector and host (cattle and buffalo respectively) population. Sequencing analysis indicated that rickettsial endo-symbionts were associated with ticks of the study area. These results provided baseline information about the prevalence of SFGR in vector and host population.

Keywords: Rickettsia, livestock, polymerase chain reaction, sequencing, ticks, vectors

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Authors: Sandeep Singh

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In this article, two classes of iterative schemes are proposed for approximating solutions of nonlinear systems of equations whose orders of convergence are six and eight respectively. Sixth order scheme requires the evaluation of two vector-functions, two first Fr'echet derivatives and three matrices inversion per iteration. This three-step sixth-order method is further extended to eighth-order method which requires one more step and the evaluation of one extra vector-function. Moreover, computational efficiency is compared with some other recently published methods in which we found, our methods are more efficient than existing numerical methods for higher and medium size nonlinear system of equations. Numerical tests are performed to validate the proposed schemes.

Keywords: Nonlinear systems, Computational complexity, order of convergence, Jarratt-type scheme

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Authors: Randa M. Ali, Naguiba F. Loutfy, Osama M. Awad

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Background: Leishmaniasis is a worldwide disease, affecting 88 countries, it is estimated that about 350 million people are at risk of leishmaniasis. Overall prevalence is 12 million people with annual mortality of about 60,000. Annual incidence is 1,500,000 cases of cutaneous leishmaniasis (CL) worldwide and half million cases of visceral Leishmaniasis (VL). Objectives: The objective of this study was to assess primary health care physicians knowledge (PHP) and attitude about leishmaniasis and to assess awareness of local inhabitants about the disease and its vector in four areas in west Alexandria, Egypt. Methods: This study was a cross sectional survey that was conducted in four PHC units in west Alexandria. All physicians currently working in these units during the study period were invited to participate in the study, only 20 PHP completed the questionnaire. 60 local inhabitant were selected randomly from the four areas of the study, 15 from each area; Data was collected through two different specially designed questionnaires. Results: 11(55%) percent of the physicians had satisfactory knowledge, they answered more than 9 (60%) questions out of a total 14 questions about leishmaniasis and sandfly. The second part of the questionnaire is concerned with attitude of the primary health care physicians about leishmaniasis, 17 (85%) had good attitude and 3 (15%) had poor attitude. The second questionnaire showed that the awareness of local inhabitants about leishmaniasis and sandly as a vector of the disease is poor and needs to be corrected. Most of the respondents (90%) had not heard about leishmaniasis, Only 3 (5%) of the interviewed inhabitants said they know sandfly and its role in transmission of leishmaniasis. Conclusions: knowledge and attitudes of physicians are acceptable. However, there is, room for improvement and could be done through formal training courses and distribution of guidelines. In addition to raising the awareness of primary health care physicians about the importance of early detection and notification of cases of lesihmaniasis. Moreover, health education for raising awareness of the public regarding the vector and the disease is necessary because related studies have demonstrated that if the inhabitants do not perceive mosquitoes to be responsible for diseases such as malaria they do not take enough measures to protect themselves against the vector.

Keywords: leishmaniasis, PHP, knowledge, attitude, local inhabitants

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Authors: Jay Prakash Singh

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The aim of the present paper is to study properties of Quasi conformally flat LP-Sasakian manifolds with a coefficient α. In this paper, we prove that a Quasi conformally flat LP-Sasakian manifold M (n > 3) with a constant coefficient α is an η−Einstein and in a quasi conformally flat LP-Sasakian manifold M (n > 3) with a constant coefficient α if the scalar curvature tensor is constant then M is of constant curvature.

Keywords: LP-Sasakian manifolds, quasi-conformal curvature tensor, concircular vector field, torse forming vector field, Einstein manifold

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Authors: Angga S. Fajar, Y. Takahashi, J. Kiyono, S. Sawada

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The structural system concept of RC pier accompanied with multi sliding friction damping mechanism was developed based on numerical analysis approach. However in the implementation, to make design for such kind of this structural system consumes a lot of effort in case high of complexity. During making design, the special behaviors of this structural system should be considered including flexible small deformation, sufficient elastic deformation capacity, sufficient lateral force resistance, and sufficient energy dissipation. The confinement distribution of friction devices has significant influence to its. Optimization and prediction with multi function regression of this structural system expected capable of providing easier and simpler design method. The confinement distribution of friction devices is optimized with SNOPT in Opensees, while some design variables of the structure are predicted using multi function regression of ANN. Based on the optimization and prediction this structural system is able to be designed easily and simply.

Keywords: RC Pier, multi sliding friction device, optimal design, flexible small deformation

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Authors: Mitchell Gohnert, Ryan Bradley

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This paper reviews some fundamental concepts of structural optimization, which are based on the type of materials used in construction and the shape of the structure. The first step in structural optimization is to break down all internal forces in a structure into fundamental stresses, which are tensions and compressions. Knowing the stress patterns directs our selection of structural shapes and the most appropriate type of construction material. In our selection of materials, it is essential to understand all construction materials have flaws, or micro-cracks, which reduce the capacity of the material, especially when subjected to tensions. Because of material defects, many construction materials perform significantly better when subjected to compressive forces. Structures are also more efficient if bending moments are eliminated. Bending stresses produce high peak stresses at each face of the member, and therefore, substantially more material is required to resist bending. The shape of the structure also has a profound effect on stress levels. Stress may be reduced dramatically by simply changing the shape. Catenary, triangular and linear shapes are the fundamental structural forms to achieve optimal stress flow. If the natural flow of stress matches the shape of the structures, the most optimal shape is determined.

Keywords: arches, economy of stresses, material strength, optimization, shells

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Authors: Farid Khosravikia, Patricia Clayton

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The main objective of this work is to evaluate the advantages and disadvantages of various machine learning techniques in two key steps of seismic hazard and risk assessment of different types of structures. The first step is the development of ground-motion models, which are used for forecasting ground-motion intensity measures (IM) given source characteristics, source-to-site distance, and local site condition for future events. IMs such as peak ground acceleration and velocity (PGA and PGV, respectively) as well as 5% damped elastic pseudospectral accelerations at different periods (PSA), are indicators of the strength of shaking at the ground surface. Typically, linear regression-based models, with pre-defined equations and coefficients, are used in ground motion prediction. However, due to the restrictions of the linear regression methods, such models may not capture more complex nonlinear behaviors that exist in the data. Thus, this study comparatively investigates potential benefits from employing other machine learning techniques as statistical method in ground motion prediction such as Artificial Neural Network, Random Forest, and Support Vector Machine. The results indicate the algorithms satisfy some physically sound characteristics such as magnitude scaling distance dependency without requiring pre-defined equations or coefficients. Moreover, it is shown that, when sufficient data is available, all the alternative algorithms tend to provide more accurate estimates compared to the conventional linear regression-based method, and particularly, Random Forest outperforms the other algorithms. However, the conventional method is a better tool when limited data is available. Second, it is investigated how machine learning techniques could be beneficial for developing probabilistic seismic demand models (PSDMs), which provide the relationship between the structural demand responses (e.g., component deformations, accelerations, internal forces, etc.) and the ground motion IMs. In the risk framework, such models are used to develop fragility curves estimating exceeding probability of damage for pre-defined limit states, and therefore, control the reliability of the predictions in the risk assessment. In this study, machine learning algorithms like artificial neural network, random forest, and support vector machine are adopted and trained on the demand parameters to derive PSDMs for them. It is observed that such models can provide more accurate estimates of prediction in relatively shorter about of time compared to conventional methods. Moreover, they can be used for sensitivity analysis of fragility curves with respect to many modeling parameters without necessarily requiring more intense numerical response-history analysis.

Keywords: artificial neural network, machine learning, random forest, seismic risk analysis, seismic hazard analysis, support vector machine

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Authors: Serges Mendomo Meye, Li Guowei, Shen Zhenzhong

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Earthquake is one of the main loads threatening dam safety. Once the dam is damaged, it will bring huge losses of life and property to the country and people. Therefore, it is very important to research the seismic safety of the dam. Due to the complex foundation conditions, high fortification intensity, and high scientific and technological content, it is necessary to adopt reasonable methods to evaluate the seismic safety performance of concrete arch dams built and under construction in strong earthquake areas. Structural seismic vulnerability analysis can predict the probability of structural failure at all levels under different intensity earthquakes, which can provide a scientific basis for reasonable seismic safety evaluation and decision-making. In this paper, the response surface method (RSM) is applied to the seismic vulnerability analysis of arch dams, which improves the efficiency of vulnerability analysis. Based on the central composite test design method, the material-seismic intensity samples are established. The response surface model (RSM) with arch crown displacement as performance index is obtained by finite element (FE) calculation of the samples, and then the accuracy of the response surface model (RSM) is verified. To obtain the seismic vulnerability curves, the seismic intensity measure ??(?1) is chosen to be 0.1~1.2g, with an interval of 0.1g and a total of 12 intensity levels. For each seismic intensity level, the arch crown displacement corresponding to 100 sets of different material samples can be calculated by algebraic operation of the response surface model (RSM), which avoids 1200 times of nonlinear dynamic calculation of arch dam; thus, the efficiency of vulnerability analysis is improved greatly.

Keywords: high concrete arch dam, performance index, response surface method, seismic vulnerability analysis, vector-valued intensity measure

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Authors: Zain Ul Abdin, Mirza Aizaz Asim, Rao Sohail Ahmad Khan, Luqman Amrao, Fiaz Hussain, Hasooba Hira, Saqi Kosar Abbas

Abstract:

The success of Integrated vector management programmes mainly depends on the correct identification of insect vector species involved in vector borne diseases. Based on molecular data the most important insect species involved as vectors for Zoonotic diseases in Pakistan were identified. The precise and accurate identification of such type of organism is only possible through molecular based techniques like “DNA barcoding”. Morphological species identification in insects at any life stage, is very challenging, therefore, DNA barcoding was used as a tool for rapid and accurate species identification in a wide variety of taxa across the globe and parallel studies revealed that DNA barcoding data can be effectively used in resolving taxonomic ambiguities, detection of cryptic diversity, invasion biology, description of new species etc. A comprehensive survey was carried out for the collection of insects (both adult and immature stages) in district Faisalabad, Pakistan and their DNA was extracted and mitochondrial cytochrome oxidase subunit I (COI-59) barcode sequences was used for molecular identification of immature and adult life stage.This preliminary research work opens new frontiers for developing sustainable insect vectors management programmes for saving lives of mankind from fatal diseases.

Keywords: zoonotic diseases, cytochrome oxidase, and insect vectors, CO1

Procedia PDF Downloads 153

Authors: M. Yoneda

Abstract:

It is known that stationary human occupants act as dynamic mass-spring-damper systems and can change the modal properties of civil engineering structures. This paper describes the full scale measurement to explain the tuned mass damper effects of stationary people on structural damping of footbridge with center span length of 33 m. A human body can be represented by a lumped system consisting of masses, springs, and dashpots. Complex eigenvalue calculation is also conducted by using ISO5982:1981 human model (two degree of freedom system). Based on experimental and analytical results for the footbridge with the stationary people in the standing position, it is demonstrated that stationary people behave as a tuned mass damper and that ISO5982:1981 human model can explain the structural damping characteristics measured in the field.

Keywords: dynamic interaction, footbridge, stationary people, structural damping

Procedia PDF Downloads 258