Search results for: surrogate safety
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 3305

Search results for: surrogate safety

3305 Variable-Fidelity Surrogate Modelling with Kriging

Authors: Selvakumar Ulaganathan, Ivo Couckuyt, Francesco Ferranti, Tom Dhaene, Eric Laermans

Abstract:

Variable-fidelity surrogate modelling offers an efficient way to approximate function data available in multiple degrees of accuracy each with varying computational cost. In this paper, a Kriging-based variable-fidelity surrogate modelling approach is introduced to approximate such deterministic data. Initially, individual Kriging surrogate models, which are enhanced with gradient data of different degrees of accuracy, are constructed. Then these Gradient enhanced Kriging surrogate models are strategically coupled using a recursive CoKriging formulation to provide an accurate surrogate model for the highest fidelity data. While, intuitively, gradient data is useful to enhance the accuracy of surrogate models, the primary motivation behind this work is to investigate if it is also worthwhile incorporating gradient data of varying degrees of accuracy.

Keywords: Kriging, CoKriging, Surrogate modelling, Variable- fidelity modelling, Gradients

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3304 Microscopic Simulation of Toll Plaza Safety and Operations

Authors: Bekir O. Bartin, Kaan Ozbay, Sandeep Mudigonda, Hong Yang

Abstract:

The use of microscopic traffic simulation in evaluating the operational and safety conditions at toll plazas is demonstrated. Two toll plazas in New Jersey are selected as case studies and were developed and validated in Paramics traffic simulation software. In order to simulate drivers’ lane selection behavior in Paramics, a utility-based lane selection approach is implemented in Paramics Application Programming Interface (API). For each vehicle approaching the toll plaza, a utility value is assigned to each toll lane by taking into account the factors that are likely to impact drivers’ lane selection behavior, such as approach lane, exit lane and queue lengths. The results demonstrate that similar operational conditions, such as lane-by-lane toll plaza traffic volume can be attained using this approach. In addition, assessment of safety at toll plazas is conducted via a surrogate safety measure. In particular, the crash index (CI), an improved surrogate measure of time-to-collision (TTC), which reflects the severity of a crash is used in the simulation analyses. The results indicate that the spatial and temporal frequency of observed crashes can be simulated using the proposed methodology. Further analyses can be conducted to evaluate and compare various different operational decisions and safety measures using microscopic simulation models.

Keywords: microscopic simulation, toll plaza, surrogate safety, application programming interface

Procedia PDF Downloads 152
3303 An Adaptive Hybrid Surrogate-Assisted Particle Swarm Optimization Algorithm for Expensive Structural Optimization

Authors: Xiongxiong You, Zhanwen Niu

Abstract:

Choosing an appropriate surrogate model plays an important role in surrogates-assisted evolutionary algorithms (SAEAs) since there are many types and different kernel functions in the surrogate model. In this paper, an adaptive selection of the best suitable surrogate model method is proposed to solve different kinds of expensive optimization problems. Firstly, according to the prediction residual error sum of square (PRESS) and different model selection strategies, the excellent individual surrogate models are integrated into multiple ensemble models in each generation. Then, based on the minimum root of mean square error (RMSE), the best suitable surrogate model is selected dynamically. Secondly, two methods with dynamic number of models and selection strategies are designed, which are used to show the influence of the number of individual models and selection strategy. Finally, some compared studies are made to deal with several commonly used benchmark problems, as well as a rotor system optimization problem. The results demonstrate the accuracy and robustness of the proposed method.

Keywords: adaptive selection, expensive optimization, rotor system, surrogates assisted evolutionary algorithms

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3302 Analysis of Moving Loads on Bridges Using Surrogate Models

Authors: Susmita Panda, Arnab Banerjee, Ajinkya Baxy, Bappaditya Manna

Abstract:

The design of short to medium-span high-speed bridges in critical locations is an essential aspect of vehicle-bridge interaction. Due to dynamic interaction between moving load and bridge, mathematical models or finite element modeling computations become time-consuming. Thus, to reduce the computational effort, a universal approximator using an artificial neural network (ANN) has been used to evaluate the dynamic response of the bridge. The data set generation and training of surrogate models have been conducted over the results obtained from mathematical modeling. Further, the robustness of the surrogate model has been investigated, which showed an error percentage of less than 10% with conventional methods. Additionally, the dependency of the dynamic response of the bridge on various load and bridge parameters has been highlighted through a parametric study.

Keywords: artificial neural network, mode superposition method, moving load analysis, surrogate models

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3301 A TgCNN-Based Surrogate Model for Subsurface Oil-Water Phase Flow under Multi-Well Conditions

Authors: Jian Li

Abstract:

The uncertainty quantification and inversion problems of subsurface oil-water phase flow usually require extensive repeated forward calculations for new runs with changed conditions. To reduce the computational time, various forms of surrogate models have been built. Related research shows that deep learning has emerged as an effective surrogate model, while most surrogate models with deep learning are purely data-driven, which always leads to poor robustness and abnormal results. To guarantee the model more consistent with the physical laws, a coupled theory-guided convolutional neural network (TgCNN) based surrogate model is built to facilitate computation efficiency under the premise of satisfactory accuracy. The model is a convolutional neural network based on multi-well reservoir simulation. The core notion of this proposed method is to bridge two separate blocks on top of an overall network. They underlie the TgCNN model in a coupled form, which reflects the coupling nature of pressure and water saturation in the two-phase flow equation. The model is driven by not only labeled data but also scientific theories, including governing equations, stochastic parameterization, boundary, and initial conditions, well conditions, and expert knowledge. The results show that the TgCNN-based surrogate model exhibits satisfactory accuracy and efficiency in subsurface oil-water phase flow under multi-well conditions.

Keywords: coupled theory-guided convolutional neural network, multi-well conditions, surrogate model, subsurface oil-water phase

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3300 The Gaze; Objectification of the Surrogate Mother in Cross-Border Surrogacy: An Empirical Study Applied to Surrogacy Facilitators

Authors: Yingyi Luo

Abstract:

Cross-border surrogacy is seen by many as a market in which women are bought and sold commodities at risk of trafficking. A surrogate can be framed as either a fully acknowledged subject, with whom intended parents engage in cross-border surrogacy—or as a tool utilized by intended parents and surrogacy facilitators in the furtherance of their own objectives. In order to identify which frame prevails, this paper applies subjectivity theory to an empirical study of cross-border surrogacy facilitated by facilitators in Australia analysing interviews with surrogate agents, counsellors and lawyers, and observations at trade show. The aim of the paper is to advance understanding of the dynamics of the relationship between intended parents, surrogates, and surrogacy facilitators by collecting new data and applying unique framework. As dominant players, surrogacy facilitators have a significant impact on determining the nature of cross-border surrogacy. However, little is known concerning the manner in which facilitators influence the inter-subjectivity between surrogate mothers and intended parents. Thus, this paper intends to identify how facilitators depict surrogate mothers, the degree to which their perspectives bear upon both the subjectivity of the surrogate mother and the relationship of intended parents with surrogate mothers. For the purpose of introducing and developing this framework in the context of cross-border surrogacy, this paper borrows from the work of theorists not often mentioned in bioethics, including Jacques Lacan, Marco Cavallaro, Michel Foucault, and others. It also applies the concept of 'the gaze' along with the dynamic of 'self' and 'other' to the cross-border surrogacy arrangement. Applying the concept of the gaze can provide a new way to interpret the power dynamic that plays out among surrogacy facilitators, intended parents, and surrogates within the commercial surrogacy arrangement and how the subjectivity is produced through the power. Viewing the relationships between the players in cross-border surrogacy through the lens of gaze theory, this paper finds that, in cross-border surrogacy, due to the structural power imbalance, affluent intended parents and surrogacy facilitators are possessors of the gaze, while surrogate mothers are under the thrall of the gaze. Specifically, facilitators frame surrogate mothers' reproductive abilities as commodities that intended parents can purchase to fulfil their urgent need to have children and experience full subjectivity, and they take a cut of the money that paid by intended parents. Therefore, commodification of the body results in degrading a surrogate mother (the object), reifying her as no more than a walking womb (the other), a process which is highly detrimental to the self of surrogate mothers. This relationship, formalized through contractual means, allows intended parents and facilitators to take advantage of surrogate mothers in the furtherance of their own objectives. This argument is enriched by new data from interviews and observations that provide nuance to this understanding of inter-subjectivity.

Keywords: cross-border surrogacy, facilitators, self, surrogate mothers

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3299 Pefloxacin as a Surrogate Marker for Ciprofloxacin Resistance in Salmonella: Study from North India

Authors: Varsha Gupta, Priya Datta, Gursimran Mohi, Jagdish Chander

Abstract:

Fluoroquinolones form the mainstay of therapy for the treatment of infections due to Salmonella enterica subsp. enterica. There is a complex interplay between several resistance mechanisms for quinolones and various fluoroquinolones discs, giving varying results, making detection and interpretation of fluoroquinolone resistance difficult. For detection of fluoroquinolone resistance in Salmonella ssp., we compared the use of pefloxacin and nalidixic acid discs as surrogate marker. Using MIC for ciprofloxacin as the gold standard, 43.5% of strains showed MIC as ≥1 μg/ml and were thus resistant to fluoroquinoloes. Based on the performance of nalidixic acid and pefloxacin discs as surrogate marker for ciprofloxacin resistance, both the discs could correctly detect all the resistant phenotypes; however, use of nalidixic acid disc showed false resistance in the majority of the sensitive phenotypes. We have also tested newer antimicrobial agents like cefixime, imipenem, tigecycline and azithromycin against Salmonella spp. Moreover, there was a comeback of susceptibility to older antimicrobials like ampicillin, chloramphenicol, and cotrimoxazole. We can also use cefixime, imipenem, tigecycline and azithromycin in the treatment of multidrug resistant S. typhi due to their high susceptibility.

Keywords: salmonella, pefloxacin, surrogate marker, chloramphenicol

Procedia PDF Downloads 941
3298 Performance Evaluation of Using Genetic Programming Based Surrogate Models for Approximating Simulation Complex Geochemical Transport Processes

Authors: Hamed K. Esfahani, Bithin Datta

Abstract:

Transport of reactive chemical contaminant species in groundwater aquifers is a complex and highly non-linear physical and geochemical process especially for real life scenarios. Simulating this transport process involves solving complex nonlinear equations and generally requires huge computational time for a given aquifer study area. Development of optimal remediation strategies in aquifers may require repeated solution of such complex numerical simulation models. To overcome this computational limitation and improve the computational feasibility of large number of repeated simulations, Genetic Programming based trained surrogate models are developed to approximately simulate such complex transport processes. Transport process of acid mine drainage, a hazardous pollutant is first simulated using a numerical simulated model: HYDROGEOCHEM 5.0 for a contaminated aquifer in a historic mine site. Simulation model solution results for an illustrative contaminated aquifer site is then approximated by training and testing a Genetic Programming (GP) based surrogate model. Performance evaluation of the ensemble GP models as surrogate models for the reactive species transport in groundwater demonstrates the feasibility of its use and the associated computational advantages. The results show the efficiency and feasibility of using ensemble GP surrogate models as approximate simulators of complex hydrogeologic and geochemical processes in a contaminated groundwater aquifer incorporating uncertainties in historic mine site.

Keywords: geochemical transport simulation, acid mine drainage, surrogate models, ensemble genetic programming, contaminated aquifers, mine sites

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3297 Development of a Reduced Multicomponent Jet Fuel Surrogate for Computational Fluid Dynamics Application

Authors: Muhammad Zaman Shakir, Mingfa Yao, Zohaib Iqbal

Abstract:

This study proposed four Jet fuel surrogate (S1, S2 S3, and 4) with careful selection of seven large hydrocarbon fuel components, ranging from C₉-C₁₆ of higher molecular weight and higher boiling point, adapting the standard molecular distribution size of the actual jet fuel. The surrogate was composed of seven components, including n-propyl cyclohexane (C₉H₁₈), n- propylbenzene (C₉H₁₂), n-undecane (C₁₁H₂₄), n- dodecane (C₁₂H₂₆), n-tetradecane (C₁₄H₃₀), n-hexadecane (C₁₆H₃₄) and iso-cetane (iC₁₆H₃₄). The skeletal jet fuel surrogate reaction mechanism was developed by two approaches, firstly based on a decoupling methodology by describing the C₄ -C₁₆ skeletal mechanism for the oxidation of heavy hydrocarbons and a detailed H₂ /CO/C₁ mechanism for prediction of oxidation of small hydrocarbons. The combined skeletal jet fuel surrogate mechanism was compressed into 128 species, and 355 reactions and thereby can be used in computational fluid dynamics (CFD) simulation. The extensive validation was performed for individual single-component including ignition delay time, species concentrations profile and laminar flame speed based on various fundamental experiments under wide operating conditions, and for their blended mixture, among all the surrogate, S1 has been extensively validated against the experimental data in a shock tube, rapid compression machine, jet-stirred reactor, counterflow flame, and premixed laminar flame over wide ranges of temperature (700-1700 K), pressure (8-50 atm), and equivalence ratio (0.5-2.0) to capture the properties target fuel Jet-A, while the rest of three surrogate S2, S3 and S4 has been validated for Shock Tube ignition delay time only to capture the ignition characteristic of target fuel S-8 & GTL, IPK and RP-3 respectively. Based on the newly proposed HyChem model, another four surrogate with similar components and composition, was developed and parallel validations data was used as followed for previously developed surrogate but at high-temperature condition only. After testing the mechanism prediction performance of surrogates developed by the decoupling methodology, the comparison was done with the results of surrogates developed by the HyChem model. It was observed that all of four proposed surrogates in this study showed good agreement with the experimental measurements and the study comes to this conclusion that like the decoupling methodology HyChem model also has a great potential for the development of oxidation mechanism for heavy alkanes because of applicability, simplicity, and compactness.

Keywords: computational fluid dynamics, decoupling methodology Hychem, jet fuel, surrogate, skeletal mechanism

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3296 Commercial Surrogacy and Rights of the Children Born

Authors: Neha Tiwari

Abstract:

Rights are prerequisite for individuals to pursue their aims and enrich themselves. Laski has said rights are, ‘conditions of social life without which no man can seek himself at his best.’ However with superior technology, rights of many individuals are at stake as well. One such sufferer is the babies born out of the practice of commercial surrogacy. Commercial surrogacy has emerged as the most viable option for the childless couples. The practice has garnered lot of debate in both academia and media. Some argue for a complete ban and some for strict rules and regulation. Most of the time the debate is regarding the rights of the surrogate, something which we cannot ignore. Equally important are the rights of the children born out of such arrangements. However, not much attention is being paid to them. Recently, a controversy emerged when a surrogate gave birth to twins. One of the babies, Gammy born with down syndrome was left behind by the couple. Gammy could die because his poor Thai surrogate mother may not be able to pay for his treatment. Even if he survives, he will never know his twin sister as her identity would never be disclosed. This is just one of many such cases where the future of such babies is being played with. If the rights of these children are not taken care of many of them will have to bear the brunt of society's ignorance and perhaps live with a scar which won't heal in their lifetime.

Keywords: babies, commercial surrogacy, rights, technology

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3295 Probability-Based Damage Detection of Structures Using Kriging Surrogates and Enhanced Ideal Gas Molecular Movement Algorithm

Authors: M. R. Ghasemi, R. Ghiasi, H. Varaee

Abstract:

Surrogate model has received increasing attention for use in detecting damage of structures based on vibration modal parameters. However, uncertainties existing in the measured vibration data may lead to false or unreliable output result from such model. In this study, an efficient approach based on Monte Carlo simulation is proposed to take into account the effect of uncertainties in developing a surrogate model. The probability of damage existence (PDE) is calculated based on the probability density function of the existence of undamaged and damaged states. The kriging technique allows one to genuinely quantify the surrogate error, therefore it is chosen as metamodeling technique. Enhanced version of ideal gas molecular movement (EIGMM) algorithm is used as main algorithm for model updating. The developed approach is applied to detect simulated damage in numerical models of 72-bar space truss and 120-bar dome truss. The simulation results show the proposed method can perform well in probability-based damage detection of structures with less computational effort compared to direct finite element model.

Keywords: probability-based damage detection (PBDD), Kriging, surrogate modeling, uncertainty quantification, artificial intelligence, enhanced ideal gas molecular movement (EIGMM)

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3294 Infilling Strategies for Surrogate Model Based Multi-disciplinary Analysis and Applications to Velocity Prediction Programs

Authors: Malo Pocheau-Lesteven, Olivier Le Maître

Abstract:

Engineering and optimisation of complex systems is often achieved through multi-disciplinary analysis of the system, where each subsystem is modeled and interacts with other subsystems to model the complete system. The coherence of the output of the different sub-systems is achieved through the use of compatibility constraints, which enforce the coupling between the different subsystems. Due to the complexity of some sub-systems and the computational cost of evaluating their respective models, it is often necessary to build surrogate models of these subsystems to allow repeated evaluation these subsystems at a relatively low computational cost. In this paper, gaussian processes are used, as their probabilistic nature is leveraged to evaluate the likelihood of satisfying the compatibility constraints. This paper presents infilling strategies to build accurate surrogate models of the subsystems in areas where they are likely to meet the compatibility constraint. It is shown that these infilling strategies can reduce the computational cost of building surrogate models for a given level of accuracy. An application of these methods to velocity prediction programs used in offshore racing naval architecture further demonstrates these method's applicability in a real engineering context. Also, some examples of the application of uncertainty quantification to field of naval architecture are presented.

Keywords: infilling strategy, gaussian process, multi disciplinary analysis, velocity prediction program

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3293 Nelder-Mead Parametric Optimization of Elastic Metamaterials with Artificial Neural Network Surrogate Model

Authors: Jiaqi Dong, Qing-Hua Qin, Yi Xiao

Abstract:

Some of the most fundamental challenges of elastic metamaterials (EMMs) optimization can be attributed to the high consumption of computational power resulted from finite element analysis (FEA) simulations that render the optimization process inefficient. Furthermore, due to the inherent mesh dependence of FEA, minuscule geometry features, which often emerge during the later stages of optimization, induce very fine elements, resulting in enormously high time consumption, particularly when repetitive solutions are needed for computing the objective function. In this study, a surrogate modelling algorithm is developed to reduce computational time in structural optimization of EMMs. The surrogate model is constructed based on a multilayer feedforward artificial neural network (ANN) architecture, trained with prepopulated eigenfrequency data prepopulated from FEA simulation and optimized through regime selection with genetic algorithm (GA) to improve its accuracy in predicting the location and width of the primary elastic band gap. With the optimized ANN surrogate at the core, a Nelder-Mead (NM) algorithm is established and its performance inspected in comparison to the FEA solution. The ANNNM model shows remarkable accuracy in predicting the band gap width and a reduction of time consumption by 47%.

Keywords: artificial neural network, machine learning, mechanical metamaterials, Nelder-Mead optimization

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3292 Human Rights in Cross-Border Surrogacy: An Exploratory Study Applied to Surrogacy Facilitators

Authors: Yingyi Luo

Abstract:

Cross-border commercial surrogacy, where Australians travel overseas to access reproduction through a surrogate mother, is an increasing phenomenon. This paper focuses on the role of Australian surrogacy facilitators, including lawyers, non-for-profit agents, fertility counselors, who act as intermediaries managing cross-border surrogacy arrangements in Australia. It explores the extent to which surrogacy facilitators are concerned with the human rights of children born through cross-border surrogacy, surrogate mothers in developing countries, and intended parents. Commercial surrogacy is a matter that is often cast in the language of human rights. This paper will contribute to an in-depth understanding of the dynamics between intended parents, surrogates, and surrogacy facilitators by adopting a human rights framework to inform data analysis regarding the role of facilitators. The purpose of this research is to inform debate and discussion on law reform related to surrogacy. This paper presented here centers on interviews with surrogacy facilitators in Australia and non-participant observations in Australia to generate thick, empirical data about the fertility industry. The data showed that the process of facilitating surrogacy arrangements had prompted facilitators to form a view on human rights as they applied to their works. Although facilitators claimed that the right of intended parents, surrogate mothers, and children were all taken into consideration, the researcher observed that the commercial surrogacy contracts described by these facilitators favored the interests of intended parents with the baby acting as their unique selling point. The interests and needs of surrogate mothers were not prioritized in the views or actions of facilitators. The result was a commercial transaction that entailed the purchase, through cross-border surrogacy, of a child, as a commodity, by relatively affluent intended parents from disadvantaged surrogate mothers through unfair contracts.

Keywords: cross-border surrogacy, facilitators, human rights, surrogacy

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3291 Artificial Neural Network Based Parameter Prediction of Miniaturized Solid Rocket Motor

Authors: Hao Yan, Xiaobing Zhang

Abstract:

The working mechanism of miniaturized solid rocket motors (SRMs) is not yet fully understood. It is imperative to explore its unique features. However, there are many disadvantages to using common multi-objective evolutionary algorithms (MOEAs) in predicting the parameters of the miniaturized SRM during its conceptual design phase. Initially, the design variables and objectives are constrained in a lumped parameter model (LPM) of this SRM, which leads to local optima in MOEAs. In addition, MOEAs require a large number of calculations due to their population strategy. Although the calculation time for simulating an LPM just once is usually less than that of a CFD simulation, the number of function evaluations (NFEs) is usually large in MOEAs, which makes the total time cost unacceptably long. Moreover, the accuracy of the LPM is relatively low compared to that of a CFD model due to its assumptions. CFD simulations or experiments are required for comparison and verification of the optimal results obtained by MOEAs with an LPM. The conceptual design phase based on MOEAs is a lengthy process, and its results are not precise enough due to the above shortcomings. An artificial neural network (ANN) based parameter prediction is proposed as a way to reduce time costs and improve prediction accuracy. In this method, an ANN is used to build a surrogate model that is trained with a 3D numerical simulation. In design, the original LPM is replaced by a surrogate model. Each case uses the same MOEAs, in which the calculation time of the two models is compared, and their optimization results are compared with 3D simulation results. Using the surrogate model for the parameter prediction process of the miniaturized SRMs results in a significant increase in computational efficiency and an improvement in prediction accuracy. Thus, the ANN-based surrogate model does provide faster and more accurate parameter prediction for an initial design scheme. Moreover, even when the MOEAs converge to local optima, the time cost of the ANN-based surrogate model is much lower than that of the simplified physical model LPM. This means that designers can save a lot of time during code debugging and parameter tuning in a complex design process. Designers can reduce repeated calculation costs and obtain accurate optimal solutions by combining an ANN-based surrogate model with MOEAs.

Keywords: artificial neural network, solid rocket motor, multi-objective evolutionary algorithm, surrogate model

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3290 Incorporation of Safety into Design by Safety Cube

Authors: Mohammad Rajabalinejad

Abstract:

Safety is often seen as a requirement or a performance indicator through the design process, and this does not always result in optimally safe products or systems. This paper suggests integrating the best safety practices with the design process to enrich the exploration experience for designers and add extra values for customers. For this purpose, the commonly practiced safety standards and design methods have been reviewed and their common blocks have been merged forming Safety Cube. Safety Cube combines common blocks for design, hazard identification, risk assessment and risk reduction through an integral approach. An example application presents the use of Safety Cube for design of machinery.

Keywords: safety, safety cube, product, system, machinery, design

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3289 An Investigation on the Relationship between Taxi Company Safety Climate and Safety Performance of Taxi Drivers in Iloilo City

Authors: Jasper C. Dioco

Abstract:

The study was done to investigate the relationship of taxi company safety climate and drivers’ safety motivation and knowledge on taxi drivers’ safety performance. Data were collected from three Taxi Companies with taxi drivers as participants (N = 84). The Hiligaynon translated version of Transportation Companies’ Climate Scale (TCCS), Safety Motivation and Knowledge Scale, Occupational Safety Motivation Questionnaire and Global Safety Climate Scale were used to study the relationships among four parameters: (a) Taxi company safety climate; (b) Safety motivation; (c) Safety knowledge; and (d) Safety performance. Correlational analyses found that there is no relation between safety climate and safety performance. A Hierarchical regression demonstrated that safety motivation predicts the most variance in safety performance. The results will greatly impact how taxi company can increase safe performance through the confirmation of the proximity of variables to organizational outcome. A strong positive safety climate, in which employees perceive safety to be a priority and that managers are committed to their safety, is likely to increase motivation to be safety. Hence, to improve outcomes, providing knowledge based training and health promotion programs within the organization must be implemented. Policy change might include overtime rules and fatigue driving awareness programs.

Keywords: safety climate, safety knowledge, safety motivation, safety performance, taxi drivers

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3288 Data-Driven Surrogate Models for Damage Prediction of Steel Liquid Storage Tanks under Seismic Hazard

Authors: Laura Micheli, Majd Hijazi, Mahmoud Faytarouni

Abstract:

The damage reported by oil and gas industrial facilities revealed the utmost vulnerability of steel liquid storage tanks to seismic events. The failure of steel storage tanks may yield devastating and long-lasting consequences on built and natural environments, including the release of hazardous substances, uncontrolled fires, and soil contamination with hazardous materials. It is, therefore, fundamental to reliably predict the damage that steel liquid storage tanks will likely experience under future seismic hazard events. The seismic performance of steel liquid storage tanks is usually assessed using vulnerability curves obtained from the numerical simulation of a tank under different hazard scenarios. However, the computational demand of high-fidelity numerical simulation models, such as finite element models, makes the vulnerability assessment of liquid storage tanks time-consuming and often impractical. As a solution, this paper presents a surrogate model-based strategy for predicting seismic-induced damage in steel liquid storage tanks. In the proposed strategy, the surrogate model is leveraged to reduce the computational demand of time-consuming numerical simulations. To create the data set for training the surrogate model, field damage data from past earthquakes reconnaissance surveys and reports are collected. Features representative of steel liquid storage tank characteristics (e.g., diameter, height, liquid level, yielding stress) and seismic excitation parameters (e.g., peak ground acceleration, magnitude) are extracted from the field damage data. The collected data are then utilized to train a surrogate model that maps the relationship between tank characteristics, seismic hazard parameters, and seismic-induced damage via a data-driven surrogate model. Different types of surrogate algorithms, including naïve Bayes, k-nearest neighbors, decision tree, and random forest, are investigated, and results in terms of accuracy are reported. The model that yields the most accurate predictions is employed to predict future damage as a function of tank characteristics and seismic hazard intensity level. Results show that the proposed approach can be used to estimate the extent of damage in steel liquid storage tanks, where the use of data-driven surrogates represents a viable alternative to computationally expensive numerical simulation models.

Keywords: damage prediction , data-driven model, seismic performance, steel liquid storage tanks, surrogate model

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3287 Assessment of Association Between Microalbuminuria and Lung Function Test Among the Community of Jimma Town

Authors: Diriba Dereje

Abstract:

Background: Cardiac and renal disease are the most prevalent chronic non-communicable diseases (CNCD) affecting the community in a significant manner. The best and recommended method in halting CNCD is by working on prevention as early as possible. This is only possible if early surrogate markers are identified. As part of the stated solution, this study will identify an association between microalbuminuria (an early surrogate marker of renal and cardiac disease) and lung function test among adult in the community. Objective: The main aim of this study was to assess an association between microalbuminuria (an early surrogate marker of renal and cardiac disease) and lung function test among adult in the community. Methodology: Community based cross sectional study was conducted among 384 adult in Jimma town. A systematic sampling technique was used in selecting participants to the study. In searching for the possible association, binary and multivariate logistic regression and t-test was conducted. Finally, the association between microalbuminuria and lung function test was well stated in the form of figures and written description. Result and Conclusion: A significant association was found between microalbuminuria and different lung function test parameters.

Keywords: microalbuminuria, lung function, association, test

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3286 Safety Factors for Improvement of Labor's Health and Safety in Construction Industry of Pakistan

Authors: Ahsan Ali Khan

Abstract:

During past few years, researchers are emphasizing more on the need of safety in construction industry. This need of safety is an important issue in developing countries. As due to development they are facing huge construction growth. This research is done to evaluate labor safety condition in construction industry of Pakistan. The research carried out through questionnaire survey at different construction sites. Useful data are gathered from these sites which then factor analyzed resulting in five factors. These factors reflect that most of the workers are aware of the safety need, but they divert this responsibility towards management and claim that the work is more essential for management instead of safety. Moreover, those work force which is unaware of safety state that there is lack of any training and guidance from upper management which lead to many unfavorable events on construction sites. There is need of implementation safety activities by management like training, formulation of rules and policies. This research will be helpful to divert management attention towards safety need so they will make efforts for safety of their manpower—the workers.

Keywords: labor's safety, management role, Pakistan, safety factors

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3285 Artificial Neural Network Modeling and Genetic Algorithm Based Optimization of Hydraulic Design Related to Seepage under Concrete Gravity Dams on Permeable Soils

Authors: Muqdad Al-Juboori, Bithin Datta

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Hydraulic structures such as gravity dams are classified as essential structures, and have the vital role in providing strong and safe water resource management. Three major aspects must be considered to achieve an effective design of such a structure: 1) The building cost, 2) safety, and 3) accurate analysis of seepage characteristics. Due to the complexity and non-linearity relationships of the seepage process, many approximation theories have been developed; however, the application of these theories results in noticeable errors. The analytical solution, which includes the difficult conformal mapping procedure, could be applied for a simple and symmetrical problem only. Therefore, the objectives of this paper are to: 1) develop a surrogate model based on numerical simulated data using SEEPW software to approximately simulate seepage process related to a hydraulic structure, 2) develop and solve a linked simulation-optimization model based on the developed surrogate model to describe the seepage occurring under a concrete gravity dam, in order to obtain optimum and safe design at minimum cost. The result shows that the linked simulation-optimization model provides an efficient and optimum design of concrete gravity dams.

Keywords: artificial neural network, concrete gravity dam, genetic algorithm, seepage analysis

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3284 Research Progress on Patient Perception Assessment Tools for Patient Safety

Authors: Yirui Wang

Abstract:

In the past few decades, patient safety has been the focus of much attention in the global medical and health field. As medical standards continue to improve and develop, the demand for patient safety is also growing. As one of the important dimensions in assessing patient safety, the Patient Perception Patient Safety Assessment Tool provides unique and valuable information from the patient's own perspective and plays an important role in promoting patient safety. This article aims to summarize and analyze the assessment content, assessment methods and applications of currently commonly used patient-perceived patient safety assessment tools at home and abroad, with a view to providing a reference for medical staff to select appropriate patient-perceived patient safety assessment tools.

Keywords: patients, patient safety, perception, assessment tools, review

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3283 A Comparative Analysis of Safety Orientation and Safety Performance in Organizations: A Project Management Perspective

Authors: Dina Alfreahat, Zoltan Sebestyen

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Safety is considered as one of the project’s success factors. Poor safety management may result in accidents that impact human, economic, and legal issues. Therefore, it is necessary to consider safety and health as a project success factor along with other project success factors, such as time, cost, and quality. Organizations have a knowledge deficit of the implementation of long-term safety practices, and due to cost control, safety problems tend to receive the least priority. They usually assume that safety management involves expenditures unrelated to production goals, thereby considering it unnecessary for profitability and competitiveness. The purpose of this study is to introduce, analysis and identify the correlation between the orientation of the public safety procedures of an organization and the public safety standards applied in the project. Therefore, the authors develop the process and collect the possible mathematical-statistical tools supporting the previously mentioned goal. The result shows that the adoption of management to safety is a major factor in implementing the safety standard in the project and thereby improving safety performance. It may take time and effort to adopt the mindset of safety orientation service development, but at the same time, the higher organizational investment in safety and health programs will contribute to the loyalty of staff to safety compliance.

Keywords: project management perspective, safety orientation, safety performance, safety standards

Procedia PDF Downloads 142
3282 Safety Management and Occupational Injuries Assessing the Mediating Role of Safety Compliance: Downstream Oil and Gas Industry of Malaysia

Authors: Muhammad Ajmal, Ahmad Shahrul Nizam Bin Isha, Shahrina Md. Nordin, Paras Behrani, Al-Baraa Abdulrahman Al-Mekhlafi

Abstract:

This study aims to investigate the impact of safety management practices via safety compliance on occupational injuries in the context of downstream the oil and gas industry of Malaysia. However, it is still challenging for researchers and academicians to control occupational injuries in high-safety-sensitive organizations. In this study response rate was 62%, and 280 valid responses were used for analysis through SmartPLS. The study results revealed that safety management practices (management commitment, safety training, safety promotion policies, workers’ involvement) play a significant role in lowering the rate of accidents in downstream the oil and gas industry via safety compliance. Furthermore, the study results also revealed that safety management practices also reduce safety management costs of organizations, e.g., lost work days and employee absenteeism. Moreover, this study is helpful for safety leaders and managers to understand the importance of safety management practices to lower the ratio of occupational injuries.

Keywords: safety management, safety compliance, occupational injuries, oil and gas, Malaysia

Procedia PDF Downloads 112
3281 Safety-Security Co-Engineering of Control Systems

Authors: Elena A. Troubitsyna

Abstract:

Designers of modern safety-critical control systems are increasingly relying on networking to provide the systems with advanced functionality and satisfy customer’s needs. However, networking nature of modern control systems also brings new technological challenges associated with ensuring system safety in the presence of openness and hence, potential security threats. In this paper, we propose a methodology that relies on systems-theoretic analysis to enable an integrated analysis of safety and security requirements of controlling software. We demonstrate how to create a safety case – a structured argument about system safety – with explicit representation of both safety and security goals. Our approach provides the designers with a systematic approach to analysing safety and security interdependencies while designing safety-critical control systems.

Keywords: controlling software, integrated analysis, security, safety-security co-engineering

Procedia PDF Downloads 465
3280 Unbreakable Obedience of Safety Regulation: The Study of Authoritarian Leadership and Safety Performance

Authors: Hong-Yi Kuo

Abstract:

Leadership is a key factor of improving workplace safety, and there have been abundant of studies which support the positive effects of appropriate leadership on employee safety performance in the western academic. However, little safety research focus on the Chinese leadership style like paternalistic leadership. To fill this gap, the resent study aims to examine the relationship between authoritarian leadership (one of the ternary mode in paternalistic leadership) and safety outcomes. This study makes hypothesis on different levels. First, on the group level, as an authoritarian leader regards safety value as the most important tasks, there would be positive effect on group safety outcomes through strengthening safety group norms by the emphasis on etiquette. Second, on the cross level, when a leader with authoritarian style has high priority on safety, employees may more obey the safety rules because of fear due to emphasis on absolute authority over the leader. Therefore, employees may show more safety performance and then increase individual safety outcomes. Survey data would be collected from 50 manufacturing groups (each group with more than 5 members and a leader) and a hierarchical linear modeling analysis would be conducted to analyze the hypothesis. Above the predictive result, the study expects to be a cornerstone of safety leadership research in the Chinese academic and practice.

Keywords: safety leadership, authoritarian leadership, group norms, safety behavior, supervisor safety priority

Procedia PDF Downloads 194
3279 Establishing a Surrogate Approach to Assess the Exposure Concentrations during Coating Process

Authors: Shan-Hong Ying, Ying-Fang Wang

Abstract:

A surrogate approach was deployed for assessing exposures of multiple chemicals at the selected working area of coating processes and applied to assess the exposure concentration of similar exposed groups using the same chemicals but different formula ratios. For the selected area, 6 to 12 portable photoionization detector (PID) were placed uniformly in its workplace to measure its total VOCs concentrations (CT-VOCs) for 6 randomly selected workshifts. Simultaneously, one sampling strain was placed beside one of these portable PIDs, and the collected air sample was analyzed for individual concentration (CVOCi) of 5 VOCs (xylene, butanone, toluene, butyl acetate, and dimethylformamide). Predictive models were established by relating the CT-VOCs to CVOCi of each individual compound via simple regression analysis. The established predictive models were employed to predict each CVOCi based on the measured CT-VOC for each the similar working area using the same portable PID. Results show that predictive models obtained from simple linear regression analyses were found with an R2 = 0.83~0.99 indicating that CT-VOCs were adequate for predicting CVOCi. In order to verify the validity of the exposure prediction model, the sampling analysis of the above chemical substances was further carried out and the correlation between the measured value (Cm) and the predicted value (Cp) was analyzed. It was found that there is a good correction between the predicted value and measured value of each measured chemical substance (R2=0.83~0.98). Therefore, the surrogate approach could be assessed the exposure concentration of similar exposed groups using the same chemicals but different formula ratios. However, it is recommended to establish the prediction model between the chemical substances belonging to each coater and the direct-reading PID, which is more representative of reality exposure situation and more accurately to estimate the long-term exposure concentration of operators.

Keywords: exposure assessment, exposure prediction model, surrogate approach, TVOC

Procedia PDF Downloads 116
3278 Navigating Safety Horizons: A Qualitative Exploration of Jobsite Safety Orientations in the US Construction Industry

Authors: Roxana Poushang Baghery, Matthew D. Reyes

Abstract:

This paper presents a comprehensive investigation into jobsite safety orientation programs within the US construction industry. Through interviews with industry professionals, this paper explores the domains of safety roles, daily safety practices, safety culture, and experts’ insights. This study underscores the pivotal significance of safety orientation programs, addressing their content, coordination, technology integration, and emergency procedures. Key findings emphasize the influential roles of leadership, language, and technology in the enhancement of these programs. Advocating for a paradigm shift, this paper calls for a multifaceted approach rooted in engagement, leadership commitment, clear communication, technological integration, simplicity, and a persistent pursuit of improvement in safety orientations. This study significantly contributes to the ongoing evolution and enhancement of safety practices, ensuring the safety and success of construction projects and, above all, the safeguarding of its workforce.

Keywords: jobsite safety orientation, construction industry, safety culture, workplace incidents

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3277 A Study on the Functional Safety Analysis of Stage Control System Based on International Electronical Committee 61508-2

Authors: Youn-Sung Kim, Hye-Mi Kim, Sang-Hoon Seo, Jaden Cha

Abstract:

This International standard IEC 61508 sets out a generic approach for all safety lifecycle activities for systems comprised of electrical/electronic/programmable electronic (E/E/PE) elements that are used to perform safety functions. The control unit in stage control system is safety related facilities to control state and speed for stage system running, and it performs safety-critical function by stage control system. The controller unit is part of safety loops corresponding to the IEC 61508 and classified as logic part in the safety loop. In this paper, we analyze using FMEDA (Failure Mode Effect and Diagnostic Analysis) to verification for fault tolerance methods and functional safety of control unit. Moreover, we determined SIL (Safety Integrity Level) for control unit according to the safety requirements defined in IEC 61508-2 based on an analyzed functional safety.

Keywords: safety function, failure mode effect, IEC 61508-2, diagnostic analysis, stage control system

Procedia PDF Downloads 241
3276 Occupational Safety in Construction Projects

Authors: Heba Elbibas, Esra Gnijeewa, Zedan Hatush

Abstract:

This paper presents research on occupational safety in construction projects, where the importance of safety management in projects was studied, including the preparation of a safety plan and program for each project and the identification of the responsibilities of each party to the contract. The research consists of two parts: 1-Field visits: which were field visits to three construction projects, including building projects, road projects, and tower installation. The safety level of these projects was evaluated through a checklist that includes the most important safety elements in terms of the application of these items in the projects. 2-Preparation of a questionnaire: which included supervisors and engineers and aimed to determine the level of awareness and commitment of different project categories to safety standards. The results showed the following: i) There is a moderate occupational safety policy. ii) The preparation and storage of maintenance reports are not fully complied with. iii) There is a moderate level of training on occupational safety for project workers. iv) The company does not impose penalties on safety violators permanently. v) There is a moderate policy for equipment and machinery safety. vi) Self-injuries occur due to (fatigue, lack of attention, deliberate error, and emotional factors), with a rate of 82.4%.

Keywords: management, safety, occupational safety, classification

Procedia PDF Downloads 66