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1 – 10 of over 2000Gulshan Singh, Miguel Cortina, Harry Millwater and Allan Clauer
The purpose of this paper is to estimate probabilistic and regional importance sensitivities of fatigue life, with respect to the laser peening (LP) parameters applied to a…
Abstract
Purpose
The purpose of this paper is to estimate probabilistic and regional importance sensitivities of fatigue life, with respect to the laser peening (LP) parameters applied to a Titanium turbine disk.
Design/methodology/approach
The sensitivities were calculated from Monte Carlo (MC) analysis of 21,000 simulations and probabilistic sensitivity methods.
Findings
The probabilistic sensitivity results indicate that the peak pressure and the mid‐span are the most important variables. The regional importance sensitivity results indicate that probability of failure is the most sensitive to the left tail of peak pressure and middle region of mid‐span and the fatigue life mean is the most sensitive to the left tails of the peak pressure and the mid‐span.
Practical implications
The sensitivity results of this research indicate that more time and energy should be focused on managing peak pressure and mid‐span, as compared to the remaining variables, to design and improve the laser peening process.
Originality/value
The paper presents four sensitivity analysis approaches which were formulated and employed to estimate fatigue life sensitivities with respect to the LP variables.
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The purpose of this paper is to report a study in which the feasibility of conducting probabilistic finite element analysis (FEA) for crane hook design has been explored.
Abstract
Purpose
The purpose of this paper is to report a study in which the feasibility of conducting probabilistic finite element analysis (FEA) for crane hook design has been explored.
Design/methodology/approach
This paper presents the results of probabilistic analysis, where in the input random variables are varied and corresponding variations in the output parameters were observed. In this study, material properties and load have been considered as random input variables and the maximum stress, maximum deflection variations were considered as output random variables.
Findings
The probability of occurrence of output variation and the sensitivity of output variables on the input variables are the important results generated from this analysis. By performing this probabilistic analysis, the random selection of factor of safety could be avoided.
Research limitations/implications
The implementation study has been carried out for a single product.
Practical implications
The usage of the approach will indicate the importance of probabilistic analysis in product design and development process. This process will enable the organization to compete in the global market.
Originality/value
A case study has been reported to indicate the feasibility of performing probabilistic FEA for crane hook design. Hence, the contributions are original.
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High‐dimensional model representation (HDMR) is a general set of quantitative model assessment and analysis tools for capturing the high‐dimensional relationships between sets of…
Abstract
Purpose
High‐dimensional model representation (HDMR) is a general set of quantitative model assessment and analysis tools for capturing the high‐dimensional relationships between sets of input and output model variables. It is an efficient formulation of the system response, if higher‐order cooperative effects are weak, allowing the physical model to be captured by the lower‐order terms. The paper's aim is to develop a new computational tool for estimating probabilistic sensitivity of structural/mechanical systems subject to random loads, material properties and geometry.
Design/methodology/approach
When first‐order HDMR approximation of the original high‐dimensional limit state is not adequate to provide the desired accuracy to the sensitivity analysis, this paper presents an enhanced HDMR (eHDMR) method to represent the higher‐order terms of HDMR expansion by expressions similar to the lower‐order ones with monomial multipliers. The accuracy of the HDMR expansion can be significantly improved using preconditioning with a minimal number of additional input‐output samples without directly invoking the determination of second‐ and higher‐order terms. As a part of this effort, the efficacy of HDMR, which is recently applied to uncertainty analysis, is also demonstrated. The method is based on computing eHDMR approximation of system responses and score functions associated with probability distribution of a random input. Surrogate model is constructed using moving least squares interpolation formula. Once the surrogate model form is defined, both the probabilistic response and its sensitivities can be estimated from a single probabilistic analysis, without requiring the gradients of performance functions.
Findings
The results of two numerical examples involving mathematical function and structural/solid‐mechanics problems indicate that the sensitivities obtained using eHDMR approximation provide significant accuracy when compared with the conventional Monte Carlo method, while requiring fewer original model simulations.
Originality/value
This is the first time where application of eHDMR concepts is explored in the stochastic sensitivity analysis. The present computational approach is valuable to the practical modelling and design community.
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Thuy Duong Oesterreich and Frank Teuteberg
Despite the advantages that the VoFI approach offers compared with traditional capital budgeting methods, its application for the appraisal of information technology (IT) and…
Abstract
Purpose
Despite the advantages that the VoFI approach offers compared with traditional capital budgeting methods, its application for the appraisal of information technology (IT) and information systems (IS) investments in both research and practice is not widespread to date. Given the static nature of the generic VoFI table, the method reaches its limits in its financial plan form because it is unable to investigate the dynamic behaviour of complex investment calculations. To date, there has been no attempt to address these shortcomings to advance the use of VoFI as a useful and valid capital budgeting method in finance and accounting. Therefore, the purpose of this study is to address this research gap and aim at developing a ‘dynamic’ VoFI model that integrates all input variables and target measures of a VoFI table and visualises the causal relationships among these variables.
Design/methodology/approach
The ‘dynamic’ VoFI model is developed through System Dynamics (SD) modelling to enhance the strength of the VoFI concept as an instrument for visualising the financial implications of investments in IT and IS at the corporate level. Case study research is used as a research method to study the behaviour of the developed model. The validity of the model is demonstrated by conducting simulation runs in Vensim software. In addition, probabilistic sensitivity analyses are performed to account for the impact of uncertainty on the main model variables.
Findings
The results demonstrate the usefulness of SD modelling for extending the generic VoFI concept by integrating risk analyses and providing a new strategy of data analysis and data presentation different from the typical financial plan form. Furthermore, the dynamic VoFI model enables the visualisation of interdependencies among the various variables incorporated in the VoFI financial plan, which significantly enhances the conceptual understanding of the investment and its financial consequences.
Originality/value
The integration of the VoFI concept into an SD model helps researchers and practitioners to enhance their conceptual understanding of this method. This thus increases its acceptance and popularity as a practical capital budgeting method, especially for the financial assessment of IT and IS investments. The VoFI model proposed in this paper should also enable analysts and decision makers to become more conscious of the interdependencies between the assumptions made for an appraisal and the quantitative results.
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Maria Giuffrida, Riccardo Mangiaracina, Alessandro Perego and Angela Tumino
The purpose of this paper is to support companies’ risk-informed selection of a logistics solution to operate in China via cross-border e-commerce (CBEC).
Abstract
Purpose
The purpose of this paper is to support companies’ risk-informed selection of a logistics solution to operate in China via cross-border e-commerce (CBEC).
Design/methodology/approach
Decision theory is applied to the recent field of CBEC. This theoretic setup involves a decision maker who must choose among a set of alternatives, whose consequences depend on uncertain factors (Savage, 1954). The study develops an activity-based model to calculate logistics costs in a deterministic setting. Simulations and probabilistic sensitivity analyses are later performed to evaluate the impact of uncertainty.
Findings
There are four main solutions to enter China, determined by the adopted international transport mean and the presence of a local warehouse. The most important risk factors affecting the choice of the logistics solution are change of CBEC regulation, product value, expected service level and demand level.
Originality/value
From a theoretical perspective, this study improves CBEC literature, so far characterised by descriptive papers, often lacking industry focus or empirical exploration. It also provides new application opportunities for decision theory, whereas previous contributions have proposed different theoretical approaches, such as transaction cost or institutional theory. From a practical viewpoint, the paper is the first to compare the costs of the main logistics solutions to sell online to China, by taking uncertainty into account. The results can be used to better understand the differences among solutions and identify the most critical parameters. Finally, this research provides some observations for policy implementation.
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Simon Adamtey and James Ogechi Kereri
Residential projects frequently suffer from low-risk management (RM) implementation and, consequently, are more likely to fail to meet performance objectives. With RM becoming an…
Abstract
Purpose
Residential projects frequently suffer from low-risk management (RM) implementation and, consequently, are more likely to fail to meet performance objectives. With RM becoming an essential requirement, the purpose of this study is to investigate RM implementation in terms of status, risk analysis techniques, barriers and impact of RM on residential projects across the USA.
Design/methodology/approach
Data were collected from 105 general contractors who had completed 3,265 residential projects in the past five years. Data collection was through a US national survey sent out through emails between August and November 2019 to residential general contractor firms. The firms were randomly selected from national organizations, such as the National Association of Home Builders, Associated General Contractors of America and Associated Builders and Contractors.
Findings
The analysis indicated that RM implementation is still extremely low at 22.27%. However, there was an increase in RM implementation as the cost and duration of projects increased. Direct judgment is the most used technique. Also, the one-sample t-test indicated that the barriers have a significant impact on RM implementation. Multinomial logistic regression results indicated that the impact of lack of management support, lack of money or budget, the complexity of analytical tools and lack of time to perform analysis predict the impact on the overall performance of construction projects. Overall, the results provide empirical evidence, which can influence management’s decision-making regarding RM and improve implementation in residential projects.
Originality/value
There is a lack of empirical evidence on the impact of barriers to RM implementation on the performance of construction projects. This research contributes to the body of knowledge by bridging this gap through a robust analysis of data collected from real residential projects.
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The purpose of this paper is to analyze a thermal power plant (TPP) by taking into consideration its key components, namely, boiler, turbine, conveyor and generator, which are…
Abstract
Purpose
The purpose of this paper is to analyze a thermal power plant (TPP) by taking into consideration its key components, namely, boiler, turbine, conveyor and generator, which are handled by a human operator. It is well known fact that the continuous power generation through a power plant depends on the reliability/availability of its components.
Design/methodology/approach
The various performance measures of a TPP are obtained by using mathematical modeling, Markov process and supplementary variable technique.
Findings
Reliability, i.e. mean time to failure with respect to different components of a TPP, has been obtained and demonstrated with the help of graphs. Critical components of the system are identified through sensitivity analysis.
Originality/value
In the present paper, a mathematical model based on the functioning of a TPP has been developed. Conclusions in this paper are good references for the design of a TPP.
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This paper gives a bibliographical review of the finite element methods (FEMs) applied for the linear and nonlinear, static and dynamic analyses of basic structural elements from…
Abstract
This paper gives a bibliographical review of the finite element methods (FEMs) applied for the linear and nonlinear, static and dynamic analyses of basic structural elements from the theoretical as well as practical points of view. The bibliography at the end of the paper contains more than 1330 references to papers, conference proceedings and theses/dissertations dealing with the analysis of beams, columns, rods, bars, cables, discs, blades, shafts, membranes, plates and shells that were published in 1999–2002.
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