Quantification of Launch Vehicle Subsystem Design Uncertainty and Performance Variability for Systems Engineering Decision Making and Risk Mitigation

2022 ◽  
Author(s):  
Lea Harris ◽  
Adam Cox ◽  
Dimitri N. Mavris
2020 ◽  
Vol 43 ◽  
Author(s):  
Valerie F. Reyna ◽  
David A. Broniatowski

Abstract Gilead et al. offer a thoughtful and much-needed treatment of abstraction. However, it fails to build on an extensive literature on abstraction, representational diversity, neurocognition, and psychopathology that provides important constraints and alternative evidence-based conceptions. We draw on conceptions in software engineering, socio-technical systems engineering, and a neurocognitive theory with abstract representations of gist at its core, fuzzy-trace theory.


2013 ◽  
Author(s):  
Stephen J. Guastello ◽  
Katherine Reiter ◽  
Anton Shircel ◽  
Paul Timm ◽  
Matthew Malon ◽  
...  

2021 ◽  
pp. 1-18
Author(s):  
ShuoYan Chou ◽  
Truong ThiThuy Duong ◽  
Nguyen Xuan Thao

Energy plays a central part in economic development, yet alongside fossil fuels bring vast environmental impact. In recent years, renewable energy has gradually become a viable source for clean energy to alleviate and decouple with a negative connotation. Different types of renewable energy are not without trade-offs beyond costs and performance. Multiple-criteria decision-making (MCDM) has become one of the most prominent tools in making decisions with multiple conflicting criteria existing in many complex real-world problems. Information obtained for decision making may be ambiguous or uncertain. Neutrosophic is an extension of fuzzy set types with three membership functions: truth membership function, falsity membership function and indeterminacy membership function. It is a useful tool when dealing with uncertainty issues. Entropy measures the uncertainty of information under neutrosophic circumstances which can be used to identify the weights of criteria in MCDM model. Meanwhile, the dissimilarity measure is useful in dealing with the ranking of alternatives in term of distance. This article proposes to build a new entropy and dissimilarity measure as well as to construct a novel MCDM model based on them to improve the inclusiveness of the perspectives for decision making. In this paper, we also give out a case study of using this model through the process of a renewable energy selection scenario in Taiwan performed and assessed.


2020 ◽  
Vol 98 (Supplement_4) ◽  
pp. 43-43
Author(s):  
Scott C Merrill ◽  
Christopher Koliba ◽  
Gabriela Bucini ◽  
Eric Clark ◽  
Luke Trinity ◽  
...  

Abstract Disease and its consequences result in social and economic impacts to the US animal livestock industry, ranging from losses in human capital to economic costs in excess of a billion dollars annually. Impacts would dramatically escalate if a devastating disease like Foot and Mouth Disease or African Swine Fever virus were to emerge in the United States. Investing in preventative biosecurity can reduce the likelihood of disease incursions and their negative impact on our livestock industry, yet uncertainty persists with regards to developing an effective biosecurity structure and culture. Here we show the implications of human behavior and decision making for biosecurity effectiveness, from the operational level to the owner/managerial level and finally to the systems level. For example, adjustments to risk messaging strategies could double worker compliance with biosecurity practices at the operational level. The improvement of our risk communication strategy may increase willingness to invest in biosecurity. Furthermore, the adaptation of policies could nudge behavior so that we observe a short disease outbreak followed by a quick eradication instead of a pandemic. Our research shows how the emergence of now-endemic diseases, such as Porcine Epidemic Diarrhea virus, cannot be adequately modeled without the use of a human behavioral component. Focusing solely on any one sector or level of the livestock system is not sufficient to predict emergent disease patterns and their social and economic impact on livestock industries. These results provide insight toward developing more effective risk mitigation strategies and ways to nudge behavior toward more disease resilient systems.


Energies ◽  
2021 ◽  
Vol 14 (11) ◽  
pp. 3066
Author(s):  
Michał Patyk ◽  
Przemysław Bodziony ◽  
Zbigniew Krysa

Selection and assessment of mining equipment used in open pit rock mines relies chiefly on estimates of overall exploitation cost. The rational arrangement of mining equipment and systems comprising loading machines, haul trucks and crushing plants should be preceded by a thorough analysis of technical and economic aspects, such as investment outlays and the costs of further exploitation, which largely determine the costs of mining operations and the deposit value. Additionally, the operational parameters of the mining equipment ought to be considered. In this study, a universal set of evaluation criteria has been developed, and an evaluation method has been applied for the selection of surface mining equipment and the processing system to be operated in specific mining conditions, defined by the user. The objective of this study is to develop and apply the new methodology of multi-criteria selection of open pit rock mining equipment based on multiple criteria decision-making (MCDM) procedures, to enable the optimization of loading, handling and crushing processes. The methodology, underpinned by the principles of MCDM, provides the dedicated ranking procedures, including the ELECTRE III. The applied methodology allows the alternative options (variants) to be ranked accordingly. Ultimately, a more universal methodology is developed, applicable in other surface mines where geological and mining conditions are similar. It may prove particularly useful in selection and performance assessment of mining equipment and process line configurations in mining of low-quality rock deposits. Therefore, we undertook to develop universal criteria and applications for the selection and performance assessment of process machines for surface mines, taking into account environmental aspects as well as deposit quality.


Buildings ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 51
Author(s):  
Amaya Osácar ◽  
Juan Bautista Echeverria Trueba ◽  
Brian Meacham

There is a trend in Europe towards increasing the quality and performance of regulations. At the same time, regulatory failure has been observed in the area of building fire safety regulation in England and elsewhere. As a result, an analysis of the appropriateness of fire safety regulations in Spain is warranted, with the objective being to assess whether a suitable level of fire safety is currently being delivered. Three basic elements must be considered in such analysis: the legal and regulatory framework, the level of fire risk/safety of buildings that is expected and the level which actually results, and a suitable method of analysis. The focus of this paper is creating a legal and regulatory framework, in particular with respect to fire safety in buildings. Components of an ”ideal” building regulatory framework to adequately control fire risk are presented, the existing building regulatory framework is summarized, and an analysis of the gaps between the ideal and the existing systems is presented. It is concluded that the gaps between the ideal and the existing framework are significant, and that the current fire safety regulations are not appropriate for assuring delivery of the intended level of fire risk mitigation.


2001 ◽  
Vol 17 (1) ◽  
pp. 114-122 ◽  
Author(s):  
Steven H. Sheingold

Decision making in health care has become increasingly reliant on information technology, evidence-based processes, and performance measurement. It is therefore a time at which it is of critical importance to make data and analyses more relevant to decision makers. Those who support Bayesian approaches contend that their analyses provide more relevant information for decision making than do classical or “frequentist” methods, and that a paradigm shift to the former is long overdue. While formal Bayesian analyses may eventually play an important role in decision making, there are several obstacles to overcome if these methods are to gain acceptance in an environment dominated by frequentist approaches. Supporters of Bayesian statistics must find more accommodating approaches to making their case, especially in finding ways to make these methods more transparent and accessible. Moreover, they must better understand the decision-making environment they hope to influence. This paper discusses these issues and provides some suggestions for overcoming some of these barriers to greater acceptance.


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