Sensitivity analysis of a greedy heuristic for knapsack problems
Ghosh, D; Chakravarti, N; Sierksma, G
2006-01-01
In this paper, we carry out parametric analysis as well as a tolerance limit based sensitivity analysis of a greedy heuristic for two knapsack problems-the 0-1 knapsack problem and the subset sum problem. We carry out the parametric analysis based on all problem parameters. In the tolerance limit
Sheridan, Robert P
2008-02-01
We introduce two ways of testing the robustness of conclusions from studies comparing virtual screening methods: alternative "global goodness" metrics and sensitivity analysis. While the robustness tests cannot eliminate all biases in virtual screening comparisons, they are useful as a "reality check" for any given study. To illustrate this, we apply them to a set of enrichments published in McGaughey et al. (J. Chem. Inf. Model. 2007, 47, 1504-1519) where 11 target protein/ligand combinations are tested on 2D and 3D similarity methods, plus docking. The major conclusions in that paper, for instance, that ligand-based methods are better than docking methods, hold up. However, some minor conclusions, such as Glide being the best docking method, do not.
... page: //medlineplus.gov/ency/article/003741.htm Sensitivity analysis To use the sharing features on this page, please enable JavaScript. Sensitivity analysis determines the effectiveness of antibiotics against microorganisms (germs) ...
State analysis of BOP using statistical and heuristic methods
International Nuclear Information System (INIS)
Heo, Gyun Young; Chang, Soon Heung
2003-01-01
Under the deregulation environment, the performance enhancement of BOP in nuclear power plants is being highlighted. To analyze performance level of BOP, we use the performance test procedures provided from an authorized institution such as ASME. However, through plant investigation, it was proved that the requirements of the performance test procedures about the reliability and quantity of sensors was difficult to be satisfied. As a solution of this, state analysis method that are the expanded concept of signal validation, was proposed on the basis of the statistical and heuristic approaches. Authors recommended the statistical linear regression model by analyzing correlation among BOP parameters as a reference state analysis method. Its advantage is that its derivation is not heuristic, it is possible to calculate model uncertainty, and it is easy to apply to an actual plant. The error of the statistical linear regression model is below 3% under normal as well as abnormal system states. Additionally a neural network model was recommended since the statistical model is impossible to apply to the validation of all of the sensors and is sensitive to the outlier that is the signal located out of a statistical distribution. Because there are a lot of sensors need to be validated in BOP, wavelet analysis (WA) were applied as a pre-processor for the reduction of input dimension and for the enhancement of training accuracy. The outlier localization capability of WA enhanced the robustness of the neural network. The trained neural network restored the degraded signals to the values within ±3% of the true signals
Pieterse, Arwen H; de Vries, Marieke
2013-09-01
Increasingly, patient decision aids and values clarification methods (VCMs) are being developed to support patients in making preference-sensitive health-care decisions. Many VCMs encourage extensive deliberation about options, without solid theoretical or empirical evidence showing that deliberation is advantageous. Research suggests that simple, fast and frugal heuristic decision strategies sometimes result in better judgments and decisions. Durand et al. have developed two fast and frugal heuristic-based VCMs. To critically analyse the suitability of the 'take the best' (TTB) and 'tallying' fast and frugal heuristics in the context of patient decision making. Analysis of the structural similarities between the environments in which the TTB and tallying heuristics have been proven successful and the context of patient decision making and of the potential of these heuristic decision processes to support patient decision making. The specific nature of patient preference-sensitive decision making does not seem to resemble environments in which the TTB and tallying heuristics have proven successful. Encouraging patients to consider less rather than more relevant information potentially even deteriorates their values clarification process. Values clarification methods promoting the use of more intuitive decision strategies may sometimes be more effective. Nevertheless, we strongly recommend further theoretical thinking about the expected value of such heuristics and of other more intuitive decision strategies in this context, as well as empirical assessments of the mechanisms by which inducing such decision strategies may impact the quality and outcome of values clarification. © 2011 John Wiley & Sons Ltd.
Karsten R.; Teismann H.; Vogels A.
2013-01-01
In classical demographic theory, reproductive value and stable age distribution are proportional to the sensitivities of the asymptotic population size to changes in mortality and maternity, respectively. In this note we point out that analogous relationships hold if the maternity function is allowed to depend on the population density. The relevant formulae can essentially be obtained by replacing the growth rate ("Lotka'sr") with zero. These facts may be used to derive heuristics for popula...
Karsten, Richard; Teismann, Holger; Vogels, Angela
2013-05-01
In classical demographic theory, reproductive value and stable age distribution are proportional to the sensitivities of the asymptotic population size to changes in mortality and maternity, respectively. In this note we point out that analogous relationships hold if the maternity function is allowed to depend on the population density. The relevant formulae can essentially be obtained by replacing the growth rate ("Lotka's r") with zero. These facts may be used to derive heuristics for population management (pest control). Copyright © 2013 Elsevier Inc. All rights reserved.
Maniscalco, Brian; Peters, Megan A K; Lau, Hakwan
2016-04-01
Zylberberg et al. [Zylberberg, Barttfeld, & Sigman (Frontiers in Integrative Neuroscience, 6; 79, 2012), Frontiers in Integrative Neuroscience 6:79] found that confidence decisions, but not perceptual decisions, are insensitive to evidence against a selected perceptual choice. We present a signal detection theoretic model to formalize this insight, which gave rise to a counter-intuitive empirical prediction: that depending on the observer's perceptual choice, increasing task performance can be associated with decreasing metacognitive sensitivity (i.e., the trial-by-trial correspondence between confidence and accuracy). The model also provides an explanation as to why metacognitive sensitivity tends to be less than optimal in actual subjects. These predictions were confirmed robustly in a psychophysics experiment. In a second experiment we found that, in at least some subjects, the effects were replicated even under performance feedback designed to encourage optimal behavior. However, some subjects did show improvement under feedback, suggesting the tendency to ignore evidence against a selected perceptual choice may be a heuristic adopted by the perceptual decision-making system, rather than reflecting inherent biological limitations. We present a Bayesian modeling framework that explains why this heuristic strategy may be advantageous in real-world contexts.
Mode analysis of heuristic behavior of searching for multimodal optimum point
Energy Technology Data Exchange (ETDEWEB)
Kamei, K; Araki, Y; Inoue, K
1982-01-01
Describes an experimental study of a heuristic behavior of searching for the global optimum (maximum) point of a two-dimensional, multimodal, nonlinear and unknown function. First, the authors define three modes dealing with the trial purposes, called the purpose modes and show the heuristic search behaviors expressed by the purpose modes which the human subjects select in the search experiments. Second, the authors classify the heuristic search behaviors into three types according to the mode transitions and extracts eight states of searches which cause the mode transitions. Third, a model of the heuristic search behavior is composed of the eight mode transitions. The analysis of the heuristic search behaviors by use of the purpose modes plays an important role in the heuristic search techniques. 6 references.
Using Heuristic Task Analysis to Create Web-Based Instructional Design Theory
Fiester, Herbert R.
2010-01-01
The first purpose of this study was to identify procedural and heuristic knowledge used when creating web-based instruction. The second purpose of this study was to develop suggestions for improving the Heuristic Task Analysis process, a technique for eliciting, analyzing, and representing expertise in cognitively complex tasks. Three expert…
Triple Modular Redundancy verification via heuristic netlist analysis
Directory of Open Access Journals (Sweden)
Giovanni Beltrame
2015-08-01
Full Text Available Triple Modular Redundancy (TMR is a common technique to protect memory elements for digital processing systems subject to radiation effects (such as in space, high-altitude, or near nuclear sources. This paper presents an approach to verify the correct implementation of TMR for the memory elements of a given netlist (i.e., a digital circuit specification using heuristic analysis. The purpose is detecting any issues that might incur during the use of automatic tools for TMR insertion, optimization, place and route, etc. Our analysis does not require a testbench and can perform full, exhaustive coverage within less than an hour even for large designs. This is achieved by applying a divide et impera approach, splitting the circuit into smaller submodules without loss of generality, instead of applying formal verification to the whole netlist at once. The methodology has been applied to a production netlist of the LEON2-FT processor that had reported errors during radiation testing, successfully showing a number of unprotected memory elements, namely 351 flip-flops.
Heuristic Evaluation of E-Learning Courses: A Comparative Analysis of Two E-Learning Heuristic Sets
Zaharias, Panagiotis; Koutsabasis, Panayiotis
2012-01-01
Purpose: The purpose of this paper is to discuss heuristic evaluation as a method for evaluating e-learning courses and applications and more specifically to investigate the applicability and empirical use of two customized e-learning heuristic protocols. Design/methodology/approach: Two representative e-learning heuristic protocols were chosen…
MacGillivray, Brian H
2017-08-01
In many environmental and public health domains, heuristic methods of risk and decision analysis must be relied upon, either because problem structures are ambiguous, reliable data is lacking, or decisions are urgent. This introduces an additional source of uncertainty beyond model and measurement error - uncertainty stemming from relying on inexact inference rules. Here we identify and analyse heuristics used to prioritise risk objects, to discriminate between signal and noise, to weight evidence, to construct models, to extrapolate beyond datasets, and to make policy. Some of these heuristics are based on causal generalisations, yet can misfire when these relationships are presumed rather than tested (e.g. surrogates in clinical trials). Others are conventions designed to confer stability to decision analysis, yet which may introduce serious error when applied ritualistically (e.g. significance testing). Some heuristics can be traced back to formal justifications, but only subject to strong assumptions that are often violated in practical applications. Heuristic decision rules (e.g. feasibility rules) in principle act as surrogates for utility maximisation or distributional concerns, yet in practice may neglect costs and benefits, be based on arbitrary thresholds, and be prone to gaming. We highlight the problem of rule-entrenchment, where analytical choices that are in principle contestable are arbitrarily fixed in practice, masking uncertainty and potentially introducing bias. Strategies for making risk and decision analysis more rigorous include: formalising the assumptions and scope conditions under which heuristics should be applied; testing rather than presuming their underlying empirical or theoretical justifications; using sensitivity analysis, simulations, multiple bias analysis, and deductive systems of inference (e.g. directed acyclic graphs) to characterise rule uncertainty and refine heuristics; adopting "recovery schemes" to correct for known biases
International Nuclear Information System (INIS)
Edalati, Sh; Houshangi far, A; Torabi, N; Baneshi, Z; Behjat, A
2017-01-01
Poly(3,4-ethylendioxythiophene):poly(styrene sulfonate) (PEDOT:PSS) was deposited on a fluoride-doped tin oxide glass substrate using a heuristic method to fabricate platinum-free counter electrodes for dye-sensitized solar cells (DSSCs). In this heuristic method a thin layer of PEDOT:PPS is obtained by spin coating the PEDOT:PSS on a Cu substrate and then removing the substrate with FeCl 3 . The characteristics of the deposited PEDOT:PSS were studied by energy dispersive x-ray analysis and scanning electron microscopy, which revealed the micro-electronic specifications of the cathode. The aforementioned DSSCs exhibited a solar conversion efficiency of 3.90%, which is far higher than that of DSSCs with pure PEDOT:PSS (1.89%). This enhancement is attributed not only to the micro-electronic specifications but also to the HNO 3 treatment through our heuristic method. The results of cyclic voltammetry, electrochemical impedance spectroscopy (EIS) and Tafel polarization plots show the modified cathode has a dual function, including excellent conductivity and electrocatalytic activity for iodine reduction. (paper)
Choosing a heuristic and root node for edge ordering in BDD-based network reliability analysis
International Nuclear Information System (INIS)
Mo, Yuchang; Xing, Liudong; Zhong, Farong; Pan, Zhusheng; Chen, Zhongyu
2014-01-01
In the Binary Decision Diagram (BDD)-based network reliability analysis, heuristics have been widely used to obtain a reasonably good ordering of edge variables. Orderings generated using different heuristics can lead to dramatically different sizes of BDDs, and thus dramatically different running times and memory usages for the analysis of the same network. Unfortunately, due to the nature of the ordering problem (i.e., being an NP-complete problem) no formal guidelines or rules are available for choosing a good heuristic or for choosing a high-performance root node to perform edge searching using a particular heuristic. In this work, we make novel contributions by proposing heuristic and root node selection methods based on the concept of boundary sets for the BDD-based network reliability analysis. Empirical studies show that the proposed selection methods can help to generate high-performance edge ordering for most of studied cases, enabling the efficient BDD-based reliability analysis of large-scale networks. The proposed methods are demonstrated on different types of networks, including square lattice networks, torus lattice networks and de Bruijn networks
Sensitivity study on heuristic rules applied to the neutronic optimization of cells for BWR
International Nuclear Information System (INIS)
Gonzalez C, J.; Martin del Campo M, C.; Francois L, J.L.
2004-01-01
The objective of this work is to verify the validity of the heuristic rules that have been applied in the processes of radial optimization of fuel cells. It was examined the rule with respect to the accommodation of fuel in the corners of the cell and it became special attention on the influence of the position and concentration of those pellets with gadolinium in the reactivity of the cell and the safety parameters. The evaluation behaved on designed cells violating the heuristic rules. For both cases the cells were analyzed between infinite using the HELIOS code. Additionally, for the second case, it was behaved a stage more exhaustive where it was used one of the studied cells that it completed those safety parameters and of reactivity to generate the design of an assemble that was used to calculate with CM-PRESTO the behavior of the nucleus during three operation cycles. (Author)
Heuristic Task Analysis on E-Learning Course Development: A Formative Research Study
Lee, Ji-Yeon; Reigeluth, Charles M.
2009-01-01
Utilizing heuristic task analysis (HTA), a method developed for eliciting, analyzing, and representing expertise in complex cognitive tasks, a formative research study was conducted on the task of e-learning course development to further improve the HTA process. Three instructional designers from three different post-secondary institutions in the…
Fitness levels with tail bounds for the analysis of randomized search heuristics
DEFF Research Database (Denmark)
Witt, Carsten
2014-01-01
The fitness-level method, also called the method of f-based partitions, is an intuitive and widely used technique for the running time analysis of randomized search heuristics. It was originally defined to prove upper and lower bounds on the expected running time. Recently, upper tail bounds were...
Sensitivity and uncertainty analysis
Cacuci, Dan G; Navon, Ionel Michael
2005-01-01
As computer-assisted modeling and analysis of physical processes have continued to grow and diversify, sensitivity and uncertainty analyses have become indispensable scientific tools. Sensitivity and Uncertainty Analysis. Volume I: Theory focused on the mathematical underpinnings of two important methods for such analyses: the Adjoint Sensitivity Analysis Procedure and the Global Adjoint Sensitivity Analysis Procedure. This volume concentrates on the practical aspects of performing these analyses for large-scale systems. The applications addressed include two-phase flow problems, a radiative c
Heuristic Sensitivity Analysis for Baker's Yeast Model Parameters
Leão, Celina P.; Soares, Filomena O.
2004-01-01
The baker's yeast, essentially composed by living cells of Saccharomyces cerevisiae, used in the bread making and beer industries as a microorganism, has an important industrial role. The simulation procedure represents then a necessary tool to understand clearly the baker's yeast fermentation process. The use of mathematical models based on mass balance equations requires the knowledge of the reaction kinetics, thermodynamics, and transport and physical properties. Models may be more or less...
Directory of Open Access Journals (Sweden)
Berezovsky Igor
2006-03-01
Full Text Available Abstract Background Manually finding subtle yet statistically significant links to distantly related homologues becomes practically impossible for very populated protein families due to the sheer number of similarity searches to be invoked and analyzed. The unclear evolutionary relationship between classical mammalian lipases and the recently discovered human adipose triglyceride lipase (ATGL; a patatin family member is an exemplary case for such a problem. Results We describe an unsupervised, sensitive sequence segment collection heuristic suitable for assembling very large protein families. It is based on fan-like expanding, iterative database searches. To prevent inclusion of unrelated hits, additional criteria are introduced: minimal alignment length and overlap with starting sequence segments, finding starting sequences in reciprocal searches, automated filtering for compositional bias and repetitive patterns. This heuristic was implemented as FAMILYSEARCHER in the ANNIE sequence analysis environment and applied to search for protein links between the classical lipase family and the patatin-like group. Conclusion The FAMILYSEARCHER is an efficient tool for tracing distant evolutionary relationships involving large protein families. Although classical lipases and ATGL have no obvious sequence similarity and differ with regard to fold and catalytic mechanism, homology links detected with FAMILYSEARCHER show that they are evolutionarily related. The conserved sequence parts can be narrowed down to an ancestral core module consisting of three β-strands, one α-helix and a turn containing the typical nucleophilic serine. Moreover, this ancestral module also appears in numerous enzymes with various substrate specificities, but that critically rely on nucleophilic attack mechanisms.
International Nuclear Information System (INIS)
Ronald L. Boring; David I. Gertman; Jeffrey C. Joe; Julie L. Marble
2005-01-01
An ongoing issue within human-computer interaction (HCI) is the need for simplified or ''discount'' methods. The current economic slowdown has necessitated innovative methods that are results driven and cost effective. The myriad methods of design and usability are currently being cost-justified, and new techniques are actively being explored that meet current budgets and needs. Recent efforts in human reliability analysis (HRA) are highlighted by the ten-year development of the Standardized Plant Analysis Risk HRA (SPAR-H) method. The SPAR-H method has been used primarily for determining human centered risk at nuclear power plants. The SPAR-H method, however, shares task analysis underpinnings with HCI. Despite this methodological overlap, there is currently no HRA approach deployed in heuristic usability evaluation. This paper presents an extension of the existing SPAR-H method to be used as part of heuristic usability evaluation in HCI
Directory of Open Access Journals (Sweden)
Iulian N. BUJOREANU
2011-01-01
Full Text Available Sensitivity analysis represents such a well known and deeply analyzed subject that anyone to enter the field feels like not being able to add anything new. Still, there are so many facets to be taken into consideration.The paper introduces the reader to the various ways sensitivity analysis is implemented and the reasons for which it has to be implemented in most analyses in the decision making processes. Risk analysis is of outmost importance in dealing with resource allocation and is presented at the beginning of the paper as the initial cause to implement sensitivity analysis. Different views and approaches are added during the discussion about sensitivity analysis so that the reader develops an as thoroughly as possible opinion on the use and UTILITY of the sensitivity analysis. Finally, a round-up conclusion brings us to the question of the possibility of generating the future and analyzing it before it unfolds so that, when it happens it brings less uncertainty.
Sensitivity Analysis Without Assumptions.
Ding, Peng; VanderWeele, Tyler J
2016-05-01
Unmeasured confounding may undermine the validity of causal inference with observational studies. Sensitivity analysis provides an attractive way to partially circumvent this issue by assessing the potential influence of unmeasured confounding on causal conclusions. However, previous sensitivity analysis approaches often make strong and untestable assumptions such as having an unmeasured confounder that is binary, or having no interaction between the effects of the exposure and the confounder on the outcome, or having only one unmeasured confounder. Without imposing any assumptions on the unmeasured confounder or confounders, we derive a bounding factor and a sharp inequality such that the sensitivity analysis parameters must satisfy the inequality if an unmeasured confounder is to explain away the observed effect estimate or reduce it to a particular level. Our approach is easy to implement and involves only two sensitivity parameters. Surprisingly, our bounding factor, which makes no simplifying assumptions, is no more conservative than a number of previous sensitivity analysis techniques that do make assumptions. Our new bounding factor implies not only the traditional Cornfield conditions that both the relative risk of the exposure on the confounder and that of the confounder on the outcome must satisfy but also a high threshold that the maximum of these relative risks must satisfy. Furthermore, this new bounding factor can be viewed as a measure of the strength of confounding between the exposure and the outcome induced by a confounder.
International Nuclear Information System (INIS)
Trovão, João P.; Antunes, Carlos Henggeler
2015-01-01
Highlights: • Two meta-heuristic approaches are evaluated for multi-ESS management in electric vehicles. • An online global energy management strategy with two different layers is studied. • Meta-heuristic techniques are used to define optimized energy sharing mechanisms. • A comparative analysis for ARTEMIS driving cycle is addressed. • The effectiveness of the double-layer management with meta-heuristic is presented. - Abstract: This work is focused on the performance evaluation of two meta-heuristic approaches, simulated annealing and particle swarm optimization, to deal with power management of a dual energy storage system for electric vehicles. The proposed strategy is based on a global energy management system with two layers: long-term (energy) and short-term (power) management. A rule-based system deals with the long-term (strategic) layer and for the short-term (action) layer meta-heuristic techniques are developed to define optimized online energy sharing mechanisms. Simulations have been made for several driving cycles to validate the proposed strategy. A comparative analysis for ARTEMIS driving cycle is presented evaluating three performance indicators (computation time, final value of battery state of charge, and minimum value of supercapacitors state of charge) as a function of input parameters. The results show the effectiveness of an implementation based on a double-layer management system using meta-heuristic methods for online power management supported by a rule set that restricts the search space
An analysis of generalised heuristics for vehicle routing and personnel rostering problems
Mustafa Misir; Pieter Smet; Greet Vanden Berghe
2015-01-01
The present study investigates the performance of heuristics while solving problems with routing and rostering characteristics. The target problems include scheduling and routing home care, security and maintenance personnel. In analysing the behaviour of the heuristics and determining the requirements for solving the aforementioned problems, the winning hyper-heuristic from the first International Cross-domain Heuristic Search Challenge (CHeSC 2011) is employed. The completely new applicatio...
Interference and Sensitivity Analysis.
VanderWeele, Tyler J; Tchetgen Tchetgen, Eric J; Halloran, M Elizabeth
2014-11-01
Causal inference with interference is a rapidly growing area. The literature has begun to relax the "no-interference" assumption that the treatment received by one individual does not affect the outcomes of other individuals. In this paper we briefly review the literature on causal inference in the presence of interference when treatments have been randomized. We then consider settings in which causal effects in the presence of interference are not identified, either because randomization alone does not suffice for identification, or because treatment is not randomized and there may be unmeasured confounders of the treatment-outcome relationship. We develop sensitivity analysis techniques for these settings. We describe several sensitivity analysis techniques for the infectiousness effect which, in a vaccine trial, captures the effect of the vaccine of one person on protecting a second person from infection even if the first is infected. We also develop two sensitivity analysis techniques for causal effects in the presence of unmeasured confounding which generalize analogous techniques when interference is absent. These two techniques for unmeasured confounding are compared and contrasted.
Directory of Open Access Journals (Sweden)
Jinggang Chu
2015-05-01
Full Text Available River basin simulation and multi-reservoir optimal operation have been critical for river basin management. Due to the intense interaction between human activities and river basin systems, the river basin model and multi-reservoir operation model are complicated with a large number of parameters. Therefore, fast and stable optimization algorithms are required for river basin management under the changing conditions of climate and current human activities. This study presents a new global optimization algorithm, named as heuristic dynamically dimensioned search with sensitivity information (HDDS-S, to effectively perform river basin simulation and multi-reservoir optimal operation during river basin management. The HDDS-S algorithm is built on the dynamically dimensioned search (DDS algorithm; and has an improved computational efficiency while maintaining its search capacity compared to the original DDS algorithm. This is mainly due to the non-uniform probability assigned to each decision variable on the basis of its changing sensitivity to the optimization objectives during the adaptive change from global to local search with dimensionality reduced. This study evaluates the new algorithm by comparing its performance with the DDS algorithm on a river basin model calibration problem and a multi-reservoir optimal operation problem. The results obtained indicate that the HDDS-S algorithm outperforms the DDS algorithm in terms of search ability and computational efficiency in the two specific problems. In addition; similar to the DDS algorithm; the HDDS-S algorithm is easy to use as it does not require any parameter tuning and automatically adjusts its search to find good solutions given an available computational budget.
Engineering applications of heuristic multilevel optimization methods
Barthelemy, Jean-Francois M.
1989-01-01
Some engineering applications of heuristic multilevel optimization methods are presented and the discussion focuses on the dependency matrix that indicates the relationship between problem functions and variables. Coordination of the subproblem optimizations is shown to be typically achieved through the use of exact or approximate sensitivity analysis. Areas for further development are identified.
DEFF Research Database (Denmark)
Lund, Henrik; Sorknæs, Peter; Mathiesen, Brian Vad
2018-01-01
of electricity, which have been introduced in recent decades. These uncertainties pose a challenge to the design and assessment of future energy strategies and investments, especially in the economic assessment of renewable energy versus business-as-usual scenarios based on fossil fuels. From a methodological...... point of view, the typical way of handling this challenge has been to predict future prices as accurately as possible and then conduct a sensitivity analysis. This paper includes a historical analysis of such predictions, leading to the conclusion that they are almost always wrong. Not only...... are they wrong in their prediction of price levels, but also in the sense that they always seem to predict a smooth growth or decrease. This paper introduces a new method and reports the results of applying it on the case of energy scenarios for Denmark. The method implies the expectation of fluctuating fuel...
Chemical kinetic functional sensitivity analysis: Elementary sensitivities
International Nuclear Information System (INIS)
Demiralp, M.; Rabitz, H.
1981-01-01
Sensitivity analysis is considered for kinetics problems defined in the space--time domain. This extends an earlier temporal Green's function method to handle calculations of elementary functional sensitivities deltau/sub i//deltaα/sub j/ where u/sub i/ is the ith species concentration and α/sub j/ is the jth system parameter. The system parameters include rate constants, diffusion coefficients, initial conditions, boundary conditions, or any other well-defined variables in the kinetic equations. These parameters are generally considered to be functions of position and/or time. Derivation of the governing equations for the sensitivities and the Green's funciton are presented. The physical interpretation of the Green's function and sensitivities is given along with a discussion of the relation of this work to earlier research
MOVES regional level sensitivity analysis
2012-01-01
The MOVES Regional Level Sensitivity Analysis was conducted to increase understanding of the operations of the MOVES Model in regional emissions analysis and to highlight the following: : the relative sensitivity of selected MOVES Model input paramet...
Energy Technology Data Exchange (ETDEWEB)
Ostafew, C. [Azure Dynamics Corp., Toronto, ON (Canada)
2010-07-01
This presentation included a sensitivity analysis of electric vehicle components on overall efficiency. The presentation provided an overview of drive cycles and discussed the major contributors to range in terms of rolling resistance; aerodynamic drag; motor efficiency; and vehicle mass. Drive cycles that were presented included: New York City Cycle (NYCC); urban dynamometer drive cycle; and US06. A summary of the findings were presented for each of the major contributors. Rolling resistance was found to have a balanced effect on each drive cycle and proportional to range. In terms of aerodynamic drive, there was a large effect on US06 range. A large effect was also found on NYCC range in terms of motor efficiency and vehicle mass. figs.
Hospitality and Tourism Online Review Research: A Systematic Analysis and Heuristic-Systematic Model
Directory of Open Access Journals (Sweden)
Sunyoung Hlee
2018-04-01
Full Text Available With tremendous growth and potential of online consumer reviews, online reviews of hospitality and tourism are now playing a significant role in consumer attitude and buying behaviors. This study reviewed and analyzed hospitality and tourism related articles published in academic journals. The systematic approach was used to analyze 55 research articles between January 2008 and December 2017. This study presented a brief synthesis of research by investigating content-related characteristics of hospitality and tourism online reviews (HTORs in different market segments. Two research questions were addressed. Building upon our literature analysis, we used the heuristic-systematic model (HSM to summarize and classify the characteristics affecting consumer perception in previous HTOR studies. We believe that the framework helps researchers to identify the research topic in extended HTORs literature and to point out possible direction for future studies.
Usable guidelines for usable websites? an analysis of five e-government heuristics
Welle Donker-Kuijer, M.C.J.; de Jong, Menno D.T.; Lentz, Leo
2010-01-01
Many government organizations use web heuristics for the quality assurance of their websites. Heuristics may be used by web designers to guide the decisions about a website in development, or by web evaluators to optimize or assess the quality of an existing website. Despite their popularity, very
Minimizing impacts of land use change on ecosystem services using multi-criteria heuristic analysis.
Keller, Arturo A; Fournier, Eric; Fox, Jessica
2015-06-01
Development of natural landscapes to support human activities impacts the capacity of the landscape to provide ecosystem services. Typically, several ecosystem services are impacted at a single development site and various footprint scenarios are possible, thus a multi-criteria analysis is needed. Restoration potential should also be considered for the area surrounding the permanent impact site. The primary objective of this research was to develop a heuristic approach to analyze multiple criteria (e.g. impacts to various ecosystem services) in a spatial configuration with many potential development sites. The approach was to: (1) quantify the magnitude of terrestrial ecosystem service (biodiversity, carbon sequestration, nutrient and sediment retention, and pollination) impacts associated with a suite of land use change scenarios using the InVEST model; (2) normalize results across categories of ecosystem services to allow cross-service comparison; (3) apply the multi-criteria heuristic algorithm to select sites with the least impact to ecosystem services, including a spatial criterion (separation between sites). As a case study, the multi-criteria impact minimization algorithm was applied to InVEST output to select 25 potential development sites out of 204 possible locations (selected by other criteria) within a 24,000 ha property. This study advanced a generally applicable spatial multi-criteria approach for 1) considering many land use footprint scenarios, 2) balancing impact decisions across a suite of ecosystem services, and 3) determining the restoration potential of ecosystem services after impacts. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.
Event based neutron activation spectroscopy and analysis algorithm using MLE and meta-heuristics
International Nuclear Information System (INIS)
Wallace, B.
2014-01-01
Techniques used in neutron activation analysis are often dependent on the experimental setup. In the context of developing a portable and high efficiency detection array, good energy resolution and half-life discrimination are difficult to obtain with traditional methods given the logistic and financial constraints. An approach different from that of spectrum addition and standard spectroscopy analysis was needed. The use of multiple detectors prompts the need for a flexible storage of acquisition data to enable sophisticated post processing of information. Analogously to what is done in heavy ion physics, gamma detection counts are stored as two-dimensional events. This enables post-selection of energies and time frames without the need to modify the experimental setup. This method of storage also permits the use of more complex analysis tools. Given the nature of the problem at hand, a light and efficient analysis code had to be devised. A thorough understanding of the physical and statistical processes involved was used to create a statistical model. Maximum likelihood estimation was combined with meta-heuristics to produce a sophisticated curve-fitting algorithm. Simulated and experimental data were fed into the analysis code prompting positive results in terms of half-life discrimination, peak identification and noise reduction. The code was also adapted to other fields of research such as heavy ion identification of the quasi-target (QT) and quasi-particle (QP). The approach used seems to be able to translate well into other fields of research. (author)
Heuristic Analysis In Architecture Of Aqa-Bozorg Mosque-School In Qajar Dynasty
Directory of Open Access Journals (Sweden)
Azarafrooz Hosseini
2016-12-01
Full Text Available Architecture during Qajar dynasty has witnessed significant developments. The change which was particularly prevalent in advanced form, was the combination of two function: mosque and school. An important issue in the mosque-school typology is the spatial layout of the space, so that the two functions could maintain their independence and do not cause flaws to each other. The aim of this study is to understand how the combination of religious and educational functions in one building is. In this research Aqa-Bozorg mosque-school is analyzed by heuristic analysis method in order to recognize the different factors such as space and quality of human cognition. The result shows that this place with religious function, is not limited to religious ceremonies, vast assemblies with social or political motivation, rather it could be known as set of usual belief or hidden ones which are existed in profound layer of thinking and culture of society. So not only formal speech or sermon, rather customs, architectural features, art sights and even arrangement of main features in a religious building could convey implication to the audience who are consciously or unconsciously affected and make their ideology based on this.
Maternal sensitivity: a concept analysis.
Shin, Hyunjeong; Park, Young-Joo; Ryu, Hosihn; Seomun, Gyeong-Ae
2008-11-01
The aim of this paper is to report a concept analysis of maternal sensitivity. Maternal sensitivity is a broad concept encompassing a variety of interrelated affective and behavioural caregiving attributes. It is used interchangeably with the terms maternal responsiveness or maternal competency, with no consistency of use. There is a need to clarify the concept of maternal sensitivity for research and practice. A search was performed on the CINAHL and Ovid MEDLINE databases using 'maternal sensitivity', 'maternal responsiveness' and 'sensitive mothering' as key words. The searches yielded 54 records for the years 1981-2007. Rodgers' method of evolutionary concept analysis was used to analyse the material. Four critical attributes of maternal sensitivity were identified: (a) dynamic process involving maternal abilities; (b) reciprocal give-and-take with the infant; (c) contingency on the infant's behaviour and (d) quality of maternal behaviours. Maternal identity and infant's needs and cues are antecedents for these attributes. The consequences are infant's comfort, mother-infant attachment and infant development. In addition, three positive affecting factors (social support, maternal-foetal attachment and high self-esteem) and three negative affecting factors (maternal depression, maternal stress and maternal anxiety) were identified. A clear understanding of the concept of maternal sensitivity could be useful for developing ways to enhance maternal sensitivity and to maximize the developmental potential of infants. Knowledge of the attributes of maternal sensitivity identified in this concept analysis may be helpful for constructing measuring items or dimensions.
Global optimization and sensitivity analysis
International Nuclear Information System (INIS)
Cacuci, D.G.
1990-01-01
A new direction for the analysis of nonlinear models of nuclear systems is suggested to overcome fundamental limitations of sensitivity analysis and optimization methods currently prevalent in nuclear engineering usage. This direction is toward a global analysis of the behavior of the respective system as its design parameters are allowed to vary over their respective design ranges. Presented is a methodology for global analysis that unifies and extends the current scopes of sensitivity analysis and optimization by identifying all the critical points (maxima, minima) and solution bifurcation points together with corresponding sensitivities at any design point of interest. The potential applicability of this methodology is illustrated with test problems involving multiple critical points and bifurcations and comprising both equality and inequality constraints
Heuristics in Conflict Resolution
Drescher, Christian; Gebser, Martin; Kaufmann, Benjamin; Schaub, Torsten
2010-01-01
Modern solvers for Boolean Satisfiability (SAT) and Answer Set Programming (ASP) are based on sophisticated Boolean constraint solving techniques. In both areas, conflict-driven learning and related techniques constitute key features whose application is enabled by conflict analysis. Although various conflict analysis schemes have been proposed, implemented, and studied both theoretically and practically in the SAT area, the heuristic aspects involved in conflict analysis have not yet receive...
Analysis of the iteratively regularized Gauss-Newton method under a heuristic rule
Jin, Qinian; Wang, Wei
2018-03-01
The iteratively regularized Gauss-Newton method is one of the most prominent regularization methods for solving nonlinear ill-posed inverse problems when the data is corrupted by noise. In order to produce a useful approximate solution, this iterative method should be terminated properly. The existing a priori and a posteriori stopping rules require accurate information on the noise level, which may not be available or reliable in practical applications. In this paper we propose a heuristic selection rule for this regularization method, which requires no information on the noise level. By imposing certain conditions on the noise, we derive a posteriori error estimates on the approximate solutions under various source conditions. Furthermore, we establish a convergence result without using any source condition. Numerical results are presented to illustrate the performance of our heuristic selection rule.
The Availability Heuristic, Intuitive Cost-Benefit Analysis, and Climate Change
International Nuclear Information System (INIS)
Sunstein, C.R.
2006-01-01
Because risks are on all sides of social situations, it is not possible to be 'precautionary' in general. The availability heuristic ensures that some risks stand out as particularly salient, whatever their actual magnitude. Taken together with intuitive cost-benefit balancing, the availability heuristic helps to explain differences across groups, cultures, and even nations in the assessment of precautions to reduce the risks associated with climate change. There are complex links among availability, social processes for the spreading of information, and predispositions. If the United States is to take a stronger stand against climate change, it is likely to be a result of available incidents that seem to show that climate change produces serious and tangible harm
Design of application for graph's handling with heuristic algorithms of analysis
López, Carlos Andrés; Ardila Urueña, William
2008-01-01
El siguiente artículo muestra la manera de desarrollar una sencilla aplicación de entorno grafico sobre la cual se puede experimentar diversas técnicas, desde algoritmos de resolución de grafos hasta heurísticas empleadas en inteligencia artificial. The next section shows how to develop a simple graphical application environment on which to experiment with various techniques, from algorithms resolution graph until heuristics used in artificial intelligence.
Directory of Open Access Journals (Sweden)
Diego Tami
2018-01-01
Full Text Available We discuss three sets of heuristic coefficients used in uniform theory of diffraction (UTD to characterize the electromagnetic scattering in realistic urban scenarios and canonical examples of diffraction by lossy conducting wedges using the three sets of heuristic coefficients and the Malyuzhinets solution as reference model. We compare not only the results of the canonical models but also their implementation in real outdoor scenarios. To predict the coverage of mobile networks, we used propagation models for outdoor environments by using a 3D ray-tracing model based on a brute-force algorithm for ray launching and a propagation model based on image theory. To evaluate each set of coefficients, we analyzed the mean and standard deviation of the absolute error between estimates and measured data in Ottawa, Canada; Valencia, Spain; and Cali, Colombia. Finally, we discuss the path loss prediction for each set of heuristic UTD coefficients in outdoor environment, as well as the comparison with the canonical results.
International Nuclear Information System (INIS)
Horwedel, J.E.; Wright, R.Q.; Maerker, R.E.
1990-01-01
A sensitivity analysis of EQ3, a computer code which has been proposed to be used as one link in the overall performance assessment of a national high-level waste repository, has been performed. EQ3 is a geochemical modeling code used to calculate the speciation of a water and its saturation state with respect to mineral phases. The model chosen for the sensitivity analysis is one which is used as a test problem in the documentation of the EQ3 code. Sensitivities are calculated using both the CHAIN and ADGEN options of the GRESS code compiled under G-float FORTRAN on the VAX/VMS and verified by perturbation runs. The analyses were performed with a preliminary Version 1.0 of GRESS which contains several new algorithms that significantly improve the application of ADGEN. Use of ADGEN automates the implementation of the well-known adjoint technique for the efficient calculation of sensitivities of a given response to all the input data. Application of ADGEN to EQ3 results in the calculation of sensitivities of a particular response to 31,000 input parameters in a run time of only 27 times that of the original model. Moreover, calculation of the sensitivities for each additional response increases this factor by only 2.5 percent. This compares very favorably with a running-time factor of 31,000 if direct perturbation runs were used instead. 6 refs., 8 tabs
High order depletion sensitivity analysis
International Nuclear Information System (INIS)
Naguib, K.; Adib, M.; Morcos, H.N.
2002-01-01
A high order depletion sensitivity method was applied to calculate the sensitivities of build-up of actinides in the irradiated fuel due to cross-section uncertainties. An iteration method based on Taylor series expansion was applied to construct stationary principle, from which all orders of perturbations were calculated. The irradiated EK-10 and MTR-20 fuels at their maximum burn-up of 25% and 65% respectively were considered for sensitivity analysis. The results of calculation show that, in case of EK-10 fuel (low burn-up), the first order sensitivity was found to be enough to perform an accuracy of 1%. While in case of MTR-20 (high burn-up) the fifth order was found to provide 3% accuracy. A computer code SENS was developed to provide the required calculations
2015-01-01
How can we advance knowledge? Which methods do we need in order to make new discoveries? How can we rationally evaluate, reconstruct and offer discoveries as a means of improving the ‘method’ of discovery itself? And how can we use findings about scientific discovery to boost funding policies, thus fostering a deeper impact of scientific discovery itself? The respective chapters in this book provide readers with answers to these questions. They focus on a set of issues that are essential to the development of types of reasoning for advancing knowledge, such as models for both revolutionary findings and paradigm shifts; ways of rationally addressing scientific disagreement, e.g. when a revolutionary discovery sparks considerable disagreement inside the scientific community; frameworks for both discovery and inference methods; and heuristics for economics and the social sciences.
Sensitivity Analysis of Simulation Models
Kleijnen, J.P.C.
2009-01-01
This contribution presents an overview of sensitivity analysis of simulation models, including the estimation of gradients. It covers classic designs and their corresponding (meta)models; namely, resolution-III designs including fractional-factorial two-level designs for first-order polynomial
Sensitivity analysis using probability bounding
International Nuclear Information System (INIS)
Ferson, Scott; Troy Tucker, W.
2006-01-01
Probability bounds analysis (PBA) provides analysts a convenient means to characterize the neighborhood of possible results that would be obtained from plausible alternative inputs in probabilistic calculations. We show the relationship between PBA and the methods of interval analysis and probabilistic uncertainty analysis from which it is jointly derived, and indicate how the method can be used to assess the quality of probabilistic models such as those developed in Monte Carlo simulations for risk analyses. We also illustrate how a sensitivity analysis can be conducted within a PBA by pinching inputs to precise distributions or real values
Neural Signatures of Rational and Heuristic Choice Strategies: A Single Trial ERP Analysis
Directory of Open Access Journals (Sweden)
Szymon Wichary
2017-08-01
Full Text Available In multi-attribute choice, people use heuristics to simplify decision problems. We studied the use of heuristic and rational strategies and their electrophysiological correlates. Since previous work linked the P3 ERP component to attention and decision making, we were interested whether the amplitude of this component is associated with decision strategy use. To this end, we recorded EEG when participants performed a two-alternative choice task, where they could acquire decision cues in a sequential manner and use them to make choices. We classified participants’ choices as consistent with a rational Weighted Additive rule (WADD or a simple heuristic Take The Best (TTB. Participants differed in their preference for WADD and TTB. Using a permutation-based single trial approach, we analyzed EEG responses to consecutive decision cues and their relation to the individual strategy preference. The preference for WADD over TTB was associated with overall higher signal amplitudes to decision cues in the P3 time window. Moreover, the preference for WADD was associated with similar P3 amplitudes to consecutive cues, whereas the preference for TTB was associated with substantial decreases in P3 amplitudes to consecutive cues. We also found that the preference for TTB was associated with enhanced N1 component to cues that discriminated decision alternatives, suggesting very early attention allocation to such cues by TTB users. Our results suggest that preference for either WADD or TTB has an early neural signature reflecting differences in attentional weighting of decision cues. In light of recent findings and hypotheses regarding P3, we interpret these results as indicating the involvement of catecholamine arousal systems in shaping predecisional information processing and strategy selection.
Neural Signatures of Rational and Heuristic Choice Strategies: A Single Trial ERP Analysis.
Wichary, Szymon; Magnuski, Mikołaj; Oleksy, Tomasz; Brzezicka, Aneta
2017-01-01
In multi-attribute choice, people use heuristics to simplify decision problems. We studied the use of heuristic and rational strategies and their electrophysiological correlates. Since previous work linked the P3 ERP component to attention and decision making, we were interested whether the amplitude of this component is associated with decision strategy use. To this end, we recorded EEG when participants performed a two-alternative choice task, where they could acquire decision cues in a sequential manner and use them to make choices. We classified participants' choices as consistent with a rational Weighted Additive rule (WADD) or a simple heuristic Take The Best (TTB). Participants differed in their preference for WADD and TTB. Using a permutation-based single trial approach, we analyzed EEG responses to consecutive decision cues and their relation to the individual strategy preference. The preference for WADD over TTB was associated with overall higher signal amplitudes to decision cues in the P3 time window. Moreover, the preference for WADD was associated with similar P3 amplitudes to consecutive cues, whereas the preference for TTB was associated with substantial decreases in P3 amplitudes to consecutive cues. We also found that the preference for TTB was associated with enhanced N1 component to cues that discriminated decision alternatives, suggesting very early attention allocation to such cues by TTB users. Our results suggest that preference for either WADD or TTB has an early neural signature reflecting differences in attentional weighting of decision cues. In light of recent findings and hypotheses regarding P3, we interpret these results as indicating the involvement of catecholamine arousal systems in shaping predecisional information processing and strategy selection.
Sensitivity analysis in remote sensing
Ustinov, Eugene A
2015-01-01
This book contains a detailed presentation of general principles of sensitivity analysis as well as their applications to sample cases of remote sensing experiments. An emphasis is made on applications of adjoint problems, because they are more efficient in many practical cases, although their formulation may seem counterintuitive to a beginner. Special attention is paid to forward problems based on higher-order partial differential equations, where a novel matrix operator approach to formulation of corresponding adjoint problems is presented. Sensitivity analysis (SA) serves for quantitative models of physical objects the same purpose, as differential calculus does for functions. SA provides derivatives of model output parameters (observables) with respect to input parameters. In remote sensing SA provides computer-efficient means to compute the jacobians, matrices of partial derivatives of observables with respect to the geophysical parameters of interest. The jacobians are used to solve corresponding inver...
Feingold, Graham; Balsells, Joseph; Glassmeier, Franziska; Yamaguchi, Takanobu; Kazil, Jan; McComiskey, Allison
2017-07-01
The relationship between the albedo of a cloudy scene A and cloud fraction fc is studied with the aid of heuristic models of stratocumulus and cumulus clouds. Existing work has shown that scene albedo increases monotonically with increasing cloud fraction but that the relationship varies from linear to superlinear. The reasons for these differences in functional dependence are traced to the relationship between cloud deepening and cloud widening. When clouds deepen with no significant increase in fc (e.g., in solid stratocumulus), the relationship between A and fc is linear. When clouds widen as they deepen, as in cumulus cloud fields, the relationship is superlinear. A simple heuristic model of a cumulus cloud field with a power law size distribution shows that the superlinear A-fc behavior is traced out either through random variation in cloud size distribution parameters or as the cloud field oscillates between a relative abundance of small clouds (steep slopes on a log-log plot) and a relative abundance of large clouds (flat slopes). Oscillations of this kind manifest in large eddy simulation of trade wind cumulus where the slope and intercept of the power law fit to the cloud size distribution are highly correlated. Further analysis of the large eddy model-generated cloud fields suggests that cumulus clouds grow larger and deeper as their underlying plumes aggregate; this is followed by breakup of large plumes and a tendency to smaller clouds. The cloud and thermal size distributions oscillate back and forth approximately in unison.
Sensitivity Analysis of Viscoelastic Structures
Directory of Open Access Journals (Sweden)
A.M.G. de Lima
2006-01-01
Full Text Available In the context of control of sound and vibration of mechanical systems, the use of viscoelastic materials has been regarded as a convenient strategy in many types of industrial applications. Numerical models based on finite element discretization have been frequently used in the analysis and design of complex structural systems incorporating viscoelastic materials. Such models must account for the typical dependence of the viscoelastic characteristics on operational and environmental parameters, such as frequency and temperature. In many applications, including optimal design and model updating, sensitivity analysis based on numerical models is a very usefull tool. In this paper, the formulation of first-order sensitivity analysis of complex frequency response functions is developed for plates treated with passive constraining damping layers, considering geometrical characteristics, such as the thicknesses of the multi-layer components, as design variables. Also, the sensitivity of the frequency response functions with respect to temperature is introduced. As an example, response derivatives are calculated for a three-layer sandwich plate and the results obtained are compared with first-order finite-difference approximations.
Directory of Open Access Journals (Sweden)
Milagros Loreto
2016-09-01
Full Text Available The Modified Spectral Projected Subgradient (MSPS was proposed to solve Langrangen Dual Problems, and its convergence was shown when the momentum term was zero. The MSPS uses a momentum term in order to speed up its convergence. The momentum term is built on the multiplication of a momentum parameter and the direction of the previous iterate. In this work, we show convergence when the momentum parameter is a non-zero constant. We also propose heuristics to choose the momentum parameter intended to avoid the Zigzagging Phenomenon of Kind I. This phenomenon is present in the MSPS when at an iterate the subgradient forms an obtuse angle with the previous direction. We identify and diminish the Zigzagging Phenomenon of Kind I on Setcovering problems, and compare our numerical results to those of the original MSPS algorithm.
UMTS Common Channel Sensitivity Analysis
DEFF Research Database (Denmark)
Pratas, Nuno; Rodrigues, António; Santos, Frederico
2006-01-01
and as such it is necessary that both channels be available across the cell radius. This requirement makes the choice of the transmission parameters a fundamental one. This paper presents a sensitivity analysis regarding the transmission parameters of two UMTS common channels: RACH and FACH. Optimization of these channels...... is performed and values for the key transmission parameters in both common channels are obtained. On RACH these parameters are the message to preamble offset, the initial SIR target and the preamble power step while on FACH it is the transmission power offset....
TEMAC, Top Event Sensitivity Analysis
International Nuclear Information System (INIS)
Iman, R.L.; Shortencarier, M.J.
1988-01-01
1 - Description of program or function: TEMAC is designed to permit the user to easily estimate risk and to perform sensitivity and uncertainty analyses with a Boolean expression such as produced by the SETS computer program. SETS produces a mathematical representation of a fault tree used to model system unavailability. In the terminology of the TEMAC program, such a mathematical representation is referred to as a top event. The analysis of risk involves the estimation of the magnitude of risk, the sensitivity of risk estimates to base event probabilities and initiating event frequencies, and the quantification of the uncertainty in the risk estimates. 2 - Method of solution: Sensitivity and uncertainty analyses associated with top events involve mathematical operations on the corresponding Boolean expression for the top event, as well as repeated evaluations of the top event in a Monte Carlo fashion. TEMAC employs a general matrix approach which provides a convenient general form for Boolean expressions, is computationally efficient, and allows large problems to be analyzed. 3 - Restrictions on the complexity of the problem - Maxima of: 4000 cut sets, 500 events, 500 values in a Monte Carlo sample, 16 characters in an event name. These restrictions are implemented through the FORTRAN 77 PARAMATER statement
Heuristic rules analysis on the fuel cells design using greedy search
International Nuclear Information System (INIS)
Ortiz, J. J.; Castillo, J. A.; Montes, J. L.; Hernandez, J. L.
2009-10-01
This work approaches the study of one of the heuristic rules of fuel cells design for boiling water nuclear reactors. This rule requires that the minor uranium enrichment is placed in the corners of the fuel cell. Also the search greedy is applied for the fuel cells design where explicitly does not take in count this rule, allowing the possibility to place any uranium enrichment with the condition that it does not contain gadolinium. Results are shown in the quality of the obtained cell by search greedy when it considers the rule and when not. The cell quality is measured with the value of the power pick factor obtained, as well as of the neutrons multiplication factor in an infinite medium. Cells were analyzed with 1 and 2 gadolinium concentrations low operation conditions at 120% of the nominal power of the reactors of the nuclear power plant of Laguna Verde. The results show that not to consider the rule in cells with a single gadolinium concentration, it has as repercussion that the greedy search has a minor performance. On the other hand with cells of two gadolinium concentrations, the performance of the greedy search was better. (Author)
Pleger, Lyn; Sager, Fritz
2016-09-18
Evaluations can only serve as a neutral evidence base for policy decision-making as long as they have not been altered along non-scientific criteria. Studies show that evaluators are repeatedly put under pressure to deliver results in line with given expectations. The study of pressure and influence to misrepresent findings is hence an important research strand for the development of evaluation praxis. A conceptual challenge in the area of evaluation ethics research is the fact that pressure can be not only negative, but also positive. We develop a heuristic model of influence on evaluations that does justice to this ambivalence of influence: the BUSD-model (betterment, undermining, support, distortion). The model is based on the distinction of two dimensions, namely 'explicitness of pressure' and 'direction of influence'. We demonstrate how the model can be applied to understand pressure and offer a practical tool to distinguish positive from negative influence in the form of three so-called differentiators (awareness, accordance, intention). The differentiators comprise a practical component by assisting evaluators who are confronted with influence. Copyright © 2016 Elsevier Ltd. All rights reserved.
Hilbig, Benjamin E; Pohl, Rüdiger F
2009-09-01
According to part of the adaptive toolbox notion of decision making known as the recognition heuristic (RH), the decision process in comparative judgments-and its duration-is determined by whether recognition discriminates between objects. By contrast, some recently proposed alternative models predict that choices largely depend on the amount of evidence speaking for each of the objects and that decision times thus depend on the evidential difference between objects, or the degree of conflict between options. This article presents 3 experiments that tested predictions derived from the RH against those from alternative models. All experiments used naturally recognized objects without teaching participants any information and thus provided optimal conditions for application of the RH. However, results supported the alternative, evidence-based models and often conflicted with the RH. Recognition was not the key determinant of decision times, whereas differences between objects with respect to (both positive and negative) evidence predicted effects well. In sum, alternative models that allow for the integration of different pieces of information may well provide a better account of comparative judgments. (c) 2009 APA, all rights reserved.
The Probability Heuristics Model of Syllogistic Reasoning.
Chater, Nick; Oaksford, Mike
1999-01-01
Proposes a probability heuristic model for syllogistic reasoning and confirms the rationality of this heuristic by an analysis of the probabilistic validity of syllogistic reasoning that treats logical inference as a limiting case of probabilistic inference. Meta-analysis and two experiments involving 40 adult participants and using generalized…
de Jong, Menno D.T.; van der Geest, Thea
2000-01-01
This article is intended to make Web designers more aware of the qualities of heuristics by presenting a framework for analyzing the characteristics of heuristics. The framework is meant to support Web designers in choosing among alternative heuristics. We hope that better knowledge of the
Chanlen, Niphon
The purpose of this study was to examine the longitudinal impacts of the Science Writing Heuristic (SWH) approach on student science achievement measured by the Iowa Test of Basic Skills (ITBS). A number of studies have reported positive impact of an inquiry-based instruction on student achievement, critical thinking skills, reasoning skills, attitude toward science, etc. So far, studies have focused on exploring how an intervention affects student achievement using teacher/researcher-generated measurement. Only a few studies have attempted to explore the long-term impacts of an intervention on student science achievement measured by standardized tests. The students' science and reading ITBS data was collected from 2000 to 2011 from a school district which had adopted the SWH approach as the main approach in science classrooms since 2002. The data consisted of 12,350 data points from 3,039 students. The multilevel model for change with discontinuity in elevation and slope technique was used to analyze changes in student science achievement growth trajectories prior and after adopting the SWH approach. The results showed that the SWH approach positively impacted students by initially raising science achievement scores. The initial impact was maintained and gradually increased when students were continuously exposed to the SWH approach. Disadvantaged students who were at risk of having low science achievement had bigger benefits from experience with the SWH approach. As a result, existing problematic achievement gaps were narrowed down. Moreover, students who started experience with the SWH approach as early as elementary school seemed to have better science achievement growth compared to students who started experiencing with the SWH approach only in high school. The results found in this study not only confirmed the positive impacts of the SWH approach on student achievement, but also demonstrated additive impacts found when students had longitudinal experiences
Data fusion qualitative sensitivity analysis
International Nuclear Information System (INIS)
Clayton, E.A.; Lewis, R.E.
1995-09-01
Pacific Northwest Laboratory was tasked with testing, debugging, and refining the Hanford Site data fusion workstation (DFW), with the assistance of Coleman Research Corporation (CRC), before delivering the DFW to the environmental restoration client at the Hanford Site. Data fusion is the mathematical combination (or fusion) of disparate data sets into a single interpretation. The data fusion software used in this study was developed by CRC. The data fusion software developed by CRC was initially demonstrated on a data set collected at the Hanford Site where three types of data were combined. These data were (1) seismic reflection, (2) seismic refraction, and (3) depth to geologic horizons. The fused results included a contour map of the top of a low-permeability horizon. This report discusses the results of a sensitivity analysis of data fusion software to variations in its input parameters. The data fusion software developed by CRC has a large number of input parameters that can be varied by the user and that influence the results of data fusion. Many of these parameters are defined as part of the earth model. The earth model is a series of 3-dimensional polynomials with horizontal spatial coordinates as the independent variables and either subsurface layer depth or values of various properties within these layers (e.g., compression wave velocity, resistivity) as the dependent variables
Heuristic Search Theory and Applications
Edelkamp, Stefan
2011-01-01
Search has been vital to artificial intelligence from the very beginning as a core technique in problem solving. The authors present a thorough overview of heuristic search with a balance of discussion between theoretical analysis and efficient implementation and application to real-world problems. Current developments in search such as pattern databases and search with efficient use of external memory and parallel processing units on main boards and graphics cards are detailed. Heuristic search as a problem solving tool is demonstrated in applications for puzzle solving, game playing, constra
Gigerenzer, Gerd; Gaissmaier, Wolfgang
2011-01-01
As reflected in the amount of controversy, few areas in psychology have undergone such dramatic conceptual changes in the past decade as the emerging science of heuristics. Heuristics are efficient cognitive processes, conscious or unconscious, that ignore part of the information. Because using heuristics saves effort, the classical view has been that heuristic decisions imply greater errors than do "rational" decisions as defined by logic or statistical models. However, for many decisions, the assumptions of rational models are not met, and it is an empirical rather than an a priori issue how well cognitive heuristics function in an uncertain world. To answer both the descriptive question ("Which heuristics do people use in which situations?") and the prescriptive question ("When should people rely on a given heuristic rather than a complex strategy to make better judgments?"), formal models are indispensable. We review research that tests formal models of heuristic inference, including in business organizations, health care, and legal institutions. This research indicates that (a) individuals and organizations often rely on simple heuristics in an adaptive way, and (b) ignoring part of the information can lead to more accurate judgments than weighting and adding all information, for instance for low predictability and small samples. The big future challenge is to develop a systematic theory of the building blocks of heuristics as well as the core capacities and environmental structures these exploit.
A Variable-Selection Heuristic for K-Means Clustering.
Brusco, Michael J.; Cradit, J. Dennis
2001-01-01
Presents a variable selection heuristic for nonhierarchical (K-means) cluster analysis based on the adjusted Rand index for measuring cluster recovery. Subjected the heuristic to Monte Carlo testing across more than 2,200 datasets. Results indicate that the heuristic is extremely effective at eliminating masking variables. (SLD)
Probabilistic sensitivity analysis of biochemical reaction systems.
Zhang, Hong-Xuan; Dempsey, William P; Goutsias, John
2009-09-07
Sensitivity analysis is an indispensable tool for studying the robustness and fragility properties of biochemical reaction systems as well as for designing optimal approaches for selective perturbation and intervention. Deterministic sensitivity analysis techniques, using derivatives of the system response, have been extensively used in the literature. However, these techniques suffer from several drawbacks, which must be carefully considered before using them in problems of systems biology. We develop here a probabilistic approach to sensitivity analysis of biochemical reaction systems. The proposed technique employs a biophysically derived model for parameter fluctuations and, by using a recently suggested variance-based approach to sensitivity analysis [Saltelli et al., Chem. Rev. (Washington, D.C.) 105, 2811 (2005)], it leads to a powerful sensitivity analysis methodology for biochemical reaction systems. The approach presented in this paper addresses many problems associated with derivative-based sensitivity analysis techniques. Most importantly, it produces thermodynamically consistent sensitivity analysis results, can easily accommodate appreciable parameter variations, and allows for systematic investigation of high-order interaction effects. By employing a computational model of the mitogen-activated protein kinase signaling cascade, we demonstrate that our approach is well suited for sensitivity analysis of biochemical reaction systems and can produce a wealth of information about the sensitivity properties of such systems. The price to be paid, however, is a substantial increase in computational complexity over derivative-based techniques, which must be effectively addressed in order to make the proposed approach to sensitivity analysis more practical.
Sensitivity Analysis of a Physiochemical Interaction Model ...
African Journals Online (AJOL)
In this analysis, we will study the sensitivity analysis due to a variation of the initial condition and experimental time. These results which we have not seen elsewhere are analysed and discussed quantitatively. Keywords: Passivation Rate, Sensitivity Analysis, ODE23, ODE45 J. Appl. Sci. Environ. Manage. June, 2012, Vol.
Sensitivity Analysis of Multidisciplinary Rotorcraft Simulations
Wang, Li; Diskin, Boris; Biedron, Robert T.; Nielsen, Eric J.; Bauchau, Olivier A.
2017-01-01
A multidisciplinary sensitivity analysis of rotorcraft simulations involving tightly coupled high-fidelity computational fluid dynamics and comprehensive analysis solvers is presented and evaluated. An unstructured sensitivity-enabled Navier-Stokes solver, FUN3D, and a nonlinear flexible multibody dynamics solver, DYMORE, are coupled to predict the aerodynamic loads and structural responses of helicopter rotor blades. A discretely-consistent adjoint-based sensitivity analysis available in FUN3D provides sensitivities arising from unsteady turbulent flows and unstructured dynamic overset meshes, while a complex-variable approach is used to compute DYMORE structural sensitivities with respect to aerodynamic loads. The multidisciplinary sensitivity analysis is conducted through integrating the sensitivity components from each discipline of the coupled system. Numerical results verify accuracy of the FUN3D/DYMORE system by conducting simulations for a benchmark rotorcraft test model and comparing solutions with established analyses and experimental data. Complex-variable implementation of sensitivity analysis of DYMORE and the coupled FUN3D/DYMORE system is verified by comparing with real-valued analysis and sensitivities. Correctness of adjoint formulations for FUN3D/DYMORE interfaces is verified by comparing adjoint-based and complex-variable sensitivities. Finally, sensitivities of the lift and drag functions obtained by complex-variable FUN3D/DYMORE simulations are compared with sensitivities computed by the multidisciplinary sensitivity analysis, which couples adjoint-based flow and grid sensitivities of FUN3D and FUN3D/DYMORE interfaces with complex-variable sensitivities of DYMORE structural responses.
Morris, Graham P.
2013-12-17
Fully automated and computer assisted heuristic data analysis approaches have been applied to a series of AC voltammetric experiments undertaken on the [Fe(CN)6]3-/4- process at a glassy carbon electrode in 3 M KCl aqueous electrolyte. The recovered parameters in all forms of data analysis encompass E0 (reversible potential), k0 (heterogeneous charge transfer rate constant at E0), α (charge transfer coefficient), Ru (uncompensated resistance), and Cdl (double layer capacitance). The automated method of analysis employed time domain optimization and Bayesian statistics. This and all other methods assumed the Butler-Volmer model applies for electron transfer kinetics, planar diffusion for mass transport, Ohm\\'s Law for Ru, and a potential-independent Cdl model. Heuristic approaches utilize combinations of Fourier Transform filtering, sensitivity analysis, and simplex-based forms of optimization applied to resolved AC harmonics and rely on experimenter experience to assist in experiment-theory comparisons. Remarkable consistency of parameter evaluation was achieved, although the fully automated time domain method provided consistently higher α values than those based on frequency domain data analysis. The origin of this difference is that the implemented fully automated method requires a perfect model for the double layer capacitance. In contrast, the importance of imperfections in the double layer model is minimized when analysis is performed in the frequency domain. Substantial variation in k0 values was found by analysis of the 10 data sets for this highly surface-sensitive pathologically variable [Fe(CN) 6]3-/4- process, but remarkably, all fit the quasi-reversible model satisfactorily. © 2013 American Chemical Society.
Directory of Open Access Journals (Sweden)
I PUTU SUDANA
2011-01-01
Full Text Available Prinsip heuristics tidak dapat dikatakan sebagai sebuah pendekatanpengambilan keputusan yang non-rasional, karena penerapan atau penggunaanyang unconscious atau subtle mind tidak dapat dianggap sebagai tindakanyang irrational. Dengan alasan tersebut, terdapat cukup alasan untukmenyatakan bahwa pengklasifikasian pendekatan-pendekatan keputusansemestinya menggunakan terminologi analytical dan experiential, dan bukanmemakai istilah rational dan non-rational seperti yang umumnya diikuti.Penerapan pendekatan heuristics dapat ditemukan pada berbagai disiplin,termasuk bisnis dan akuntansi. Topik heuristics semestinya mendapatperhatian yang cukup luas dari para periset di bidang akuntansi. Bidangbehavioral research in accounting menawarkan banyak kemungkinan untukdikaji, karena prinsip heuristics bertautan erat dengan aspek manusia sebagaipelaku dalam pengambilan keputusan.
Regenwetter, Michel; Ho, Moon-Ho R; Tsetlin, Ilia
2007-10-01
This project reconciles historically distinct paradigms at the interface between individual and social choice theory, as well as between rational and behavioral decision theory. The authors combine a utility-maximizing prescriptive rule for sophisticated approval voting with the ignorance prior heuristic from behavioral decision research and two types of plurality heuristics to model approval voting behavior. When using a sincere plurality heuristic, voters simplify their decision process by voting for their single favorite candidate. When using a strategic plurality heuristic, voters strategically focus their attention on the 2 front-runners and vote for their preferred candidate among these 2. Using a hierarchy of Thurstonian random utility models, the authors implemented these different decision rules and tested them statistically on 7 real world approval voting elections. They cross-validated their key findings via a psychological Internet experiment. Although a substantial number of voters used the plurality heuristic in the real elections, they did so sincerely, not strategically. Moreover, even though Thurstonian models do not force such agreement, the results show, in contrast to common wisdom about social choice rules, that the sincere social orders by Condorcet, Borda, plurality, and approval voting are identical in all 7 elections and in the Internet experiment. PsycINFO Database Record (c) 2007 APA, all rights reserved.
Analysis of Heuristics in Business Recruitment based on a Portfolio of Real Derivatives
Directory of Open Access Journals (Sweden)
Silvia Bou Ysás
2014-01-01
Full Text Available Departing from the notion that labour legislation should be founded in the generation of job stability a model for recruitment is presented in which the employer is likened to the holder of an investment portfolio containing two real derivatives – swap or the option of sale. This model allows us on one hand to analyze sensitivity to the variables that are at play in an employment contract and, on the other, look at the effects that the most recent reforms in Spanish labour laws have had on contracting decisions made by employers. The results are clear: social security benefits are shown to be the most sensitive variable on the work contract, and applying the changes proposed in the latest labour reforms, this effect is upheld. The study concludes that reducing the costs of dismissal does not increase the likelihood of employers’ taking on new staff.
Risk Characterization uncertainties associated description, sensitivity analysis
International Nuclear Information System (INIS)
Carrillo, M.; Tovar, M.; Alvarez, J.; Arraez, M.; Hordziejewicz, I.; Loreto, I.
2013-01-01
The power point presentation is about risks to the estimated levels of exposure, uncertainty and variability in the analysis, sensitivity analysis, risks from exposure to multiple substances, formulation of guidelines for carcinogenic and genotoxic compounds and risk subpopulations
Object-sensitive Type Analysis of PHP
Van der Hoek, Henk Erik; Hage, J
2015-01-01
In this paper we develop an object-sensitive type analysis for PHP, based on an extension of the notion of monotone frameworks to deal with the dynamic aspects of PHP, and following the framework of Smaragdakis et al. for object-sensitive analysis. We consider a number of instantiations of the
Mittag, Kathleen Cage
Most researchers using factor analysis extract factors from a matrix of Pearson product-moment correlation coefficients. A method is presented for extracting factors in a non-parametric way, by extracting factors from a matrix of Spearman rho (rank correlation) coefficients. It is possible to factor analyze a matrix of association such that…
Sensitivity analysis of source driven subcritical systems by the HGPT methodology
International Nuclear Information System (INIS)
Gandini, A.
1997-01-01
The heuristically based generalized perturbation theory (HGPT) methodology has been extensively used in the last decades for analysis studies in the nuclear reactor field. Its use leads to fundamental reciprocity relationships from which perturbation, or sensitivity expressions can be derived, to first and higher order, in terms of simple integration operation of quantities calculated at unperturbed system conditions. Its application to subcritical, source-driven systems, now considered with increasing interest in many laboratories for their potential use as nuclear waste burners and/or safer energy producers, is here commented, with particular emphasis to problems implying an intensive system control variable. (author)
Zhou, Hui; Ji, Ning; Samuel, Oluwarotimi Williams; Cao, Yafei; Zhao, Zheyi; Chen, Shixiong; Li, Guanglin
2016-10-01
Real-time detection of gait events can be applied as a reliable input to control drop foot correction devices and lower-limb prostheses. Among the different sensors used to acquire the signals associated with walking for gait event detection, the accelerometer is considered as a preferable sensor due to its convenience of use, small size, low cost, reliability, and low power consumption. Based on the acceleration signals, different algorithms have been proposed to detect toe off (TO) and heel strike (HS) gait events in previous studies. While these algorithms could achieve a relatively reasonable performance in gait event detection, they suffer from limitations such as poor real-time performance and are less reliable in the cases of up stair and down stair terrains. In this study, a new algorithm is proposed to detect the gait events on three walking terrains in real-time based on the analysis of acceleration jerk signals with a time-frequency method to obtain gait parameters, and then the determination of the peaks of jerk signals using peak heuristics. The performance of the newly proposed algorithm was evaluated with eight healthy subjects when they were walking on level ground, up stairs, and down stairs. Our experimental results showed that the mean F1 scores of the proposed algorithm were above 0.98 for HS event detection and 0.95 for TO event detection on the three terrains. This indicates that the current algorithm would be robust and accurate for gait event detection on different terrains. Findings from the current study suggest that the proposed method may be a preferable option in some applications such as drop foot correction devices and leg prostheses.
Regenwetter, Michel; Ho, Moon-Ho R.; Tsetlin, Ilia
2007-01-01
This project reconciles historically distinct paradigms at the interface between individual and social choice theory, as well as between rational and behavioral decision theory. The authors combine a utility-maximizing prescriptive rule for sophisticated approval voting with the ignorance prior heuristic from behavioral decision research and two…
A hybrid approach for global sensitivity analysis
International Nuclear Information System (INIS)
Chakraborty, Souvik; Chowdhury, Rajib
2017-01-01
Distribution based sensitivity analysis (DSA) computes sensitivity of the input random variables with respect to the change in distribution of output response. Although DSA is widely appreciated as the best tool for sensitivity analysis, the computational issue associated with this method prohibits its use for complex structures involving costly finite element analysis. For addressing this issue, this paper presents a method that couples polynomial correlated function expansion (PCFE) with DSA. PCFE is a fully equivalent operational model which integrates the concepts of analysis of variance decomposition, extended bases and homotopy algorithm. By integrating PCFE into DSA, it is possible to considerably alleviate the computational burden. Three examples are presented to demonstrate the performance of the proposed approach for sensitivity analysis. For all the problems, proposed approach yields excellent results with significantly reduced computational effort. The results obtained, to some extent, indicate that proposed approach can be utilized for sensitivity analysis of large scale structures. - Highlights: • A hybrid approach for global sensitivity analysis is proposed. • Proposed approach integrates PCFE within distribution based sensitivity analysis. • Proposed approach is highly efficient.
A comparison of heuristic and model-based clustering methods for dietary pattern analysis.
Greve, Benjamin; Pigeot, Iris; Huybrechts, Inge; Pala, Valeria; Börnhorst, Claudia
2016-02-01
Cluster analysis is widely applied to identify dietary patterns. A new method based on Gaussian mixture models (GMM) seems to be more flexible compared with the commonly applied k-means and Ward's method. In the present paper, these clustering approaches are compared to find the most appropriate one for clustering dietary data. The clustering methods were applied to simulated data sets with different cluster structures to compare their performance knowing the true cluster membership of observations. Furthermore, the three methods were applied to FFQ data assessed in 1791 children participating in the IDEFICS (Identification and Prevention of Dietary- and Lifestyle-Induced Health Effects in Children and Infants) Study to explore their performance in practice. The GMM outperformed the other methods in the simulation study in 72 % up to 100 % of cases, depending on the simulated cluster structure. Comparing the computationally less complex k-means and Ward's methods, the performance of k-means was better in 64-100 % of cases. Applied to real data, all methods identified three similar dietary patterns which may be roughly characterized as a 'non-processed' cluster with a high consumption of fruits, vegetables and wholemeal bread, a 'balanced' cluster with only slight preferences of single foods and a 'junk food' cluster. The simulation study suggests that clustering via GMM should be preferred due to its higher flexibility regarding cluster volume, shape and orientation. The k-means seems to be a good alternative, being easier to use while giving similar results when applied to real data.
Sensitivity analysis of a PWR pressurizer
International Nuclear Information System (INIS)
Bruel, Renata Nunes
1997-01-01
A sensitivity analysis relative to the parameters and modelling of the physical process in a PWR pressurizer has been performed. The sensitivity analysis was developed by implementing the key parameters and theoretical model lings which generated a comprehensive matrix of influences of each changes analysed. The major influences that have been observed were the flashing phenomenon and the steam condensation on the spray drops. The present analysis is also applicable to the several theoretical and experimental areas. (author)
Sensitivity analysis for large-scale problems
Noor, Ahmed K.; Whitworth, Sandra L.
1987-01-01
The development of efficient techniques for calculating sensitivity derivatives is studied. The objective is to present a computational procedure for calculating sensitivity derivatives as part of performing structural reanalysis for large-scale problems. The scope is limited to framed type structures. Both linear static analysis and free-vibration eigenvalue problems are considered.
Sensitivity analysis in life cycle assessment
Groen, E.A.; Heijungs, R.; Bokkers, E.A.M.; Boer, de I.J.M.
2014-01-01
Life cycle assessments require many input parameters and many of these parameters are uncertain; therefore, a sensitivity analysis is an essential part of the final interpretation. The aim of this study is to compare seven sensitivity methods applied to three types of case stud-ies. Two
Ethical sensitivity in professional practice: concept analysis.
Weaver, Kathryn; Morse, Janice; Mitcham, Carl
2008-06-01
This paper is a report of a concept analysis of ethical sensitivity. Ethical sensitivity enables nurses and other professionals to respond morally to the suffering and vulnerability of those receiving professional care and services. Because of its significance to nursing and other professional practices, ethical sensitivity deserves more focused analysis. A criteria-based method oriented toward pragmatic utility guided the analysis of 200 papers and books from the fields of nursing, medicine, psychology, dentistry, clinical ethics, theology, education, law, accounting or business, journalism, philosophy, political and social sciences and women's studies. This literature spanned 1970 to 2006 and was sorted by discipline and concept dimensions and examined for concept structure and use across various contexts. The analysis was completed in September 2007. Ethical sensitivity in professional practice develops in contexts of uncertainty, client suffering and vulnerability, and through relationships characterized by receptivity, responsiveness and courage on the part of professionals. Essential attributes of ethical sensitivity are identified as moral perception, affectivity and dividing loyalties. Outcomes include integrity preserving decision-making, comfort and well-being, learning and professional transcendence. Our findings promote ethical sensitivity as a type of practical wisdom that pursues client comfort and professional satisfaction with care delivery. The analysis and resulting model offers an inclusive view of ethical sensitivity that addresses some of the limitations with prior conceptualizations.
LBLOCA sensitivity analysis using meta models
International Nuclear Information System (INIS)
Villamizar, M.; Sanchez-Saez, F.; Villanueva, J.F.; Carlos, S.; Sanchez, A.I.; Martorell, S.
2014-01-01
This paper presents an approach to perform the sensitivity analysis of the results of simulation of thermal hydraulic codes within a BEPU approach. Sensitivity analysis is based on the computation of Sobol' indices that makes use of a meta model, It presents also an application to a Large-Break Loss of Coolant Accident, LBLOCA, in the cold leg of a pressurized water reactor, PWR, addressing the results of the BEMUSE program and using the thermal-hydraulic code TRACE. (authors)
Pitfalls in Teaching Judgment Heuristics
Shepperd, James A.; Koch, Erika J.
2005-01-01
Demonstrations of judgment heuristics typically focus on how heuristics can lead to poor judgments. However, exclusive focus on the negative consequences of heuristics can prove problematic. We illustrate the problem with the representativeness heuristic and present a study (N = 45) that examined how examples influence understanding of the…
Sensitivity analysis in optimization and reliability problems
International Nuclear Information System (INIS)
Castillo, Enrique; Minguez, Roberto; Castillo, Carmen
2008-01-01
The paper starts giving the main results that allow a sensitivity analysis to be performed in a general optimization problem, including sensitivities of the objective function, the primal and the dual variables with respect to data. In particular, general results are given for non-linear programming, and closed formulas for linear programming problems are supplied. Next, the methods are applied to a collection of civil engineering reliability problems, which includes a bridge crane, a retaining wall and a composite breakwater. Finally, the sensitivity analysis formulas are extended to calculus of variations problems and a slope stability problem is used to illustrate the methods
Sensitivity analysis in optimization and reliability problems
Energy Technology Data Exchange (ETDEWEB)
Castillo, Enrique [Department of Applied Mathematics and Computational Sciences, University of Cantabria, Avda. Castros s/n., 39005 Santander (Spain)], E-mail: castie@unican.es; Minguez, Roberto [Department of Applied Mathematics, University of Castilla-La Mancha, 13071 Ciudad Real (Spain)], E-mail: roberto.minguez@uclm.es; Castillo, Carmen [Department of Civil Engineering, University of Castilla-La Mancha, 13071 Ciudad Real (Spain)], E-mail: mariacarmen.castillo@uclm.es
2008-12-15
The paper starts giving the main results that allow a sensitivity analysis to be performed in a general optimization problem, including sensitivities of the objective function, the primal and the dual variables with respect to data. In particular, general results are given for non-linear programming, and closed formulas for linear programming problems are supplied. Next, the methods are applied to a collection of civil engineering reliability problems, which includes a bridge crane, a retaining wall and a composite breakwater. Finally, the sensitivity analysis formulas are extended to calculus of variations problems and a slope stability problem is used to illustrate the methods.
Techniques for sensitivity analysis of SYVAC results
International Nuclear Information System (INIS)
Prust, J.O.
1985-05-01
Sensitivity analysis techniques may be required to examine the sensitivity of SYVAC model predictions to the input parameter values, the subjective probability distributions assigned to the input parameters and to the relationship between dose and the probability of fatal cancers plus serious hereditary disease in the first two generations of offspring of a member of the critical group. This report mainly considers techniques for determining the sensitivity of dose and risk to the variable input parameters. The performance of a sensitivity analysis technique may be improved by decomposing the model and data into subsets for analysis, making use of existing information on sensitivity and concentrating sampling in regions the parameter space that generates high doses or risks. A number of sensitivity analysis techniques are reviewed for their application to the SYVAC model including four techniques tested in an earlier study by CAP Scientific for the SYVAC project. This report recommends the development now of a method for evaluating the derivative of dose and parameter value and extending the Kruskal-Wallis technique to test for interactions between parameters. It is also recommended that the sensitivity of the output of each sub-model of SYVAC to input parameter values should be examined. (author)
International Nuclear Information System (INIS)
Castillo, Alejandro; Martín-del-Campo, Cecilia; Montes-Tadeo, José-Luis; François, Juan-Luis; Ortiz-Servin, Juan-José; Perusquía-del-Cueto, Raúl
2014-01-01
Highlights: • Different metaheuristic optimization techniques were compared. • The optimal enrichment and gadolinia distribution in a BWR fuel lattice was studied. • A decision making tool based on the Position Vector of Minimum Regret was applied. • Similar results were found for the different optimization techniques. - Abstract: In the present study a comparison of the performance of five heuristic techniques for optimization of combinatorial problems is shown. The techniques are: Ant Colony System, Artificial Neural Networks, Genetic Algorithms, Greedy Search and a hybrid of Path Relinking and Scatter Search. They were applied to obtain an “optimal” enrichment and gadolinia distribution in a fuel lattice of a boiling water reactor. All techniques used the same objective function for qualifying the different distributions created during the optimization process as well as the same initial conditions and restrictions. The parameters included in the objective function are the k-infinite multiplication factor, the maximum local power peaking factor, the average enrichment and the average gadolinia concentration of the lattice. The CASMO-4 code was used to obtain the neutronic parameters. The criteria for qualifying the optimization techniques include also the evaluation of the best lattice with burnup and the number of evaluations of the objective function needed to obtain the best solution. In conclusion all techniques obtain similar results, but there are methods that found better solutions faster than others. A decision analysis tool based on the Position Vector of Minimum Regret was applied to aggregate the criteria in order to rank the solutions according to three functions: neutronic grade at 0 burnup, neutronic grade with burnup and global cost which aggregates the computing time in the decision. According to the results Greedy Search found the best lattice in terms of the neutronic grade at 0 burnup and also with burnup. However, Greedy Search is
International Nuclear Information System (INIS)
Kauffman, L.H.
1990-01-01
This paper gives a heuristic derivation of the skein relation for the Homfly polynomial in an integral formalism. The derivation is formally correct but highly simplified. In the light of Witten's proposal for invariants of links via functional integrals, it is useful to have a formal pattern to compare with the complexities of the full approach. The formalism is a heuristic. However, it is closely related to the actual structure of the Witten functional integral
Multiple predictor smoothing methods for sensitivity analysis
International Nuclear Information System (INIS)
Helton, Jon Craig; Storlie, Curtis B.
2006-01-01
The use of multiple predictor smoothing methods in sampling-based sensitivity analyses of complex models is investigated. Specifically, sensitivity analysis procedures based on smoothing methods employing the stepwise application of the following nonparametric regression techniques are described: (1) locally weighted regression (LOESS), (2) additive models, (3) projection pursuit regression, and (4) recursive partitioning regression. The indicated procedures are illustrated with both simple test problems and results from a performance assessment for a radioactive waste disposal facility (i.e., the Waste Isolation Pilot Plant). As shown by the example illustrations, the use of smoothing procedures based on nonparametric regression techniques can yield more informative sensitivity analysis results than can be obtained with more traditional sensitivity analysis procedures based on linear regression, rank regression or quadratic regression when nonlinear relationships between model inputs and model predictions are present
Multiple predictor smoothing methods for sensitivity analysis.
Energy Technology Data Exchange (ETDEWEB)
Helton, Jon Craig; Storlie, Curtis B.
2006-08-01
The use of multiple predictor smoothing methods in sampling-based sensitivity analyses of complex models is investigated. Specifically, sensitivity analysis procedures based on smoothing methods employing the stepwise application of the following nonparametric regression techniques are described: (1) locally weighted regression (LOESS), (2) additive models, (3) projection pursuit regression, and (4) recursive partitioning regression. The indicated procedures are illustrated with both simple test problems and results from a performance assessment for a radioactive waste disposal facility (i.e., the Waste Isolation Pilot Plant). As shown by the example illustrations, the use of smoothing procedures based on nonparametric regression techniques can yield more informative sensitivity analysis results than can be obtained with more traditional sensitivity analysis procedures based on linear regression, rank regression or quadratic regression when nonlinear relationships between model inputs and model predictions are present.
Dynamic Resonance Sensitivity Analysis in Wind Farms
DEFF Research Database (Denmark)
Ebrahimzadeh, Esmaeil; Blaabjerg, Frede; Wang, Xiongfei
2017-01-01
(PFs) are calculated by critical eigenvalue sensitivity analysis versus the entries of the MIMO matrix. The PF analysis locates the most exciting bus of the resonances, where can be the best location to install the passive or active filters to reduce the harmonic resonance problems. Time...
International Nuclear Information System (INIS)
Greenspan, E.
1982-01-01
This chapter presents the mathematical basis for sensitivity functions, discusses their physical meaning and information they contain, and clarifies a number of issues concerning their application, including the definition of group sensitivities, the selection of sensitivity functions to be included in the analysis, and limitations of sensitivity theory. Examines the theoretical foundation; criticality reset sensitivities; group sensitivities and uncertainties; selection of sensitivities included in the analysis; and other uses and limitations of sensitivity functions. Gives the theoretical formulation of sensitivity functions pertaining to ''as-built'' designs for performance parameters of the form of ratios of linear flux functionals (such as reaction-rate ratios), linear adjoint functionals, bilinear functions (such as reactivity worth ratios), and for reactor reactivity. Offers a consistent procedure for reducing energy-dependent or fine-group sensitivities and uncertainties to broad group sensitivities and uncertainties. Provides illustrations of sensitivity functions as well as references to available compilations of such functions and of total sensitivities. Indicates limitations of sensitivity theory originating from the fact that this theory is based on a first-order perturbation theory
Heuristics and bias in rectal surgery.
MacDermid, Ewan; Young, Christopher J; Moug, Susan J; Anderson, Robert G; Shepherd, Heather L
2017-08-01
Deciding to defunction after anterior resection can be difficult, requiring cognitive tools or heuristics. From our previous work, increasing age and risk-taking propensity were identified as heuristic biases for surgeons in Australia and New Zealand (CSSANZ), and inversely proportional to the likelihood of creating defunctioning stomas. We aimed to assess these factors for colorectal surgeons in the British Isles, and identify other potential biases. The Association of Coloproctology of Great Britain and Ireland (ACPGBI) was invited to complete an online survey. Questions included demographics, risk-taking propensity, sensitivity to professional criticism, self-perception of anastomotic leak rate and propensity for creating defunctioning stomas. Chi-squared testing was used to assess differences between ACPGBI and CSSANZ respondents. Multiple regression analysis identified independent surgeon predictors of stoma formation. One hundred fifty (19.2%) eligible members of the ACPGBI replied. Demographics between ACPGBI and CSSANZ groups were well-matched. Significantly more ACPGBI surgeons admitted to anastomotic leak in the last year (p < 0.001). ACPGBI surgeon age over 50 (p = 0.02), higher risk-taking propensity across several domains (p = 0.044), self-belief in a lower-than-average anastomotic leak rate (p = 0.02) and belief that the average risk of leak after anterior resection is 8% or lower (p = 0.007) were all independent predictors of less frequent stoma formation. Sensitivity to criticism from colleagues was not a predictor of stoma formation. Unrecognised surgeon factors including age, everyday risk-taking, self-belief in surgical ability and lower probability bias of anastomotic leak appear to exert an effect on decision-making in rectal surgery.
Heuristic thinking makes a chemist smart.
Graulich, Nicole; Hopf, Henning; Schreiner, Peter R
2010-05-01
We focus on the virtually neglected use of heuristic principles in understanding and teaching of organic chemistry. As human thinking is not comparable to computer systems employing factual knowledge and algorithms--people rarely make decisions through careful considerations of every possible event and its probability, risks or usefulness--research in science and teaching must include psychological aspects of the human decision making processes. Intuitive analogical and associative reasoning and the ability to categorize unexpected findings typically demonstrated by experienced chemists should be made accessible to young learners through heuristic concepts. The psychology of cognition defines heuristics as strategies that guide human problem-solving and deciding procedures, for example with patterns, analogies, or prototypes. Since research in the field of artificial intelligence and current studies in the psychology of cognition have provided evidence for the usefulness of heuristics in discovery, the status of heuristics has grown into something useful and teachable. In this tutorial review, we present a heuristic analysis of a familiar fundamental process in organic chemistry--the cyclic six-electron case, and we show that this approach leads to a more conceptual insight in understanding, as well as in teaching and learning.
Heuristics as Bayesian inference under extreme priors.
Parpart, Paula; Jones, Matt; Love, Bradley C
2018-05-01
Simple heuristics are often regarded as tractable decision strategies because they ignore a great deal of information in the input data. One puzzle is why heuristics can outperform full-information models, such as linear regression, which make full use of the available information. These "less-is-more" effects, in which a relatively simpler model outperforms a more complex model, are prevalent throughout cognitive science, and are frequently argued to demonstrate an inherent advantage of simplifying computation or ignoring information. In contrast, we show at the computational level (where algorithmic restrictions are set aside) that it is never optimal to discard information. Through a formal Bayesian analysis, we prove that popular heuristics, such as tallying and take-the-best, are formally equivalent to Bayesian inference under the limit of infinitely strong priors. Varying the strength of the prior yields a continuum of Bayesian models with the heuristics at one end and ordinary regression at the other. Critically, intermediate models perform better across all our simulations, suggesting that down-weighting information with the appropriate prior is preferable to entirely ignoring it. Rather than because of their simplicity, our analyses suggest heuristics perform well because they implement strong priors that approximate the actual structure of the environment. We end by considering how new heuristics could be derived by infinitely strengthening the priors of other Bayesian models. These formal results have implications for work in psychology, machine learning and economics. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.
Probabilistic sensitivity analysis in health economics.
Baio, Gianluca; Dawid, A Philip
2015-12-01
Health economic evaluations have recently become an important part of the clinical and medical research process and have built upon more advanced statistical decision-theoretic foundations. In some contexts, it is officially required that uncertainty about both parameters and observable variables be properly taken into account, increasingly often by means of Bayesian methods. Among these, probabilistic sensitivity analysis has assumed a predominant role. The objective of this article is to review the problem of health economic assessment from the standpoint of Bayesian statistical decision theory with particular attention to the philosophy underlying the procedures for sensitivity analysis. © The Author(s) 2011.
TOLERANCE SENSITIVITY ANALYSIS: THIRTY YEARS LATER
Directory of Open Access Journals (Sweden)
Richard E. Wendell
2010-12-01
Full Text Available Tolerance sensitivity analysis was conceived in 1980 as a pragmatic approach to effectively characterize a parametric region over which objective function coefficients and right-hand-side terms in linear programming could vary simultaneously and independently while maintaining the same optimal basis. As originally proposed, the tolerance region corresponds to the maximum percentage by which coefficients or terms could vary from their estimated values. Over the last thirty years the original results have been extended in a number of ways and applied in a variety of applications. This paper is a critical review of tolerance sensitivity analysis, including extensions and applications.
A heuristic evaluation of the Facebook's advertising tool beacon
Jamal, A; Cole, M
2009-01-01
Interface usability is critical to the successful adoption of information systems. The aim of this study is to evaluate interface of Facebook's advertising tool Beacon by using privacy heuristics [4]. Beacon represents an interesting case study because of the negative media and user backlash it received. The findings of heuristic evaluation suggest violation of privacy heuristics [4]. Here, analysis identified concerns about user choice and consent, integrity and security of data, and awarene...
Sensitivity Analysis of Centralized Dynamic Cell Selection
DEFF Research Database (Denmark)
Lopez, Victor Fernandez; Alvarez, Beatriz Soret; Pedersen, Klaus I.
2016-01-01
and a suboptimal optimization algorithm that nearly achieves the performance of the optimal Hungarian assignment. Moreover, an exhaustive sensitivity analysis with different network and traffic configurations is carried out in order to understand what conditions are more appropriate for the use of the proposed...
Sensitivity analysis in a structural reliability context
International Nuclear Information System (INIS)
Lemaitre, Paul
2014-01-01
This thesis' subject is sensitivity analysis in a structural reliability context. The general framework is the study of a deterministic numerical model that allows to reproduce a complex physical phenomenon. The aim of a reliability study is to estimate the failure probability of the system from the numerical model and the uncertainties of the inputs. In this context, the quantification of the impact of the uncertainty of each input parameter on the output might be of interest. This step is called sensitivity analysis. Many scientific works deal with this topic but not in the reliability scope. This thesis' aim is to test existing sensitivity analysis methods, and to propose more efficient original methods. A bibliographical step on sensitivity analysis on one hand and on the estimation of small failure probabilities on the other hand is first proposed. This step raises the need to develop appropriate techniques. Two variables ranking methods are then explored. The first one proposes to make use of binary classifiers (random forests). The second one measures the departure, at each step of a subset method, between each input original density and the density given the subset reached. A more general and original methodology reflecting the impact of the input density modification on the failure probability is then explored. The proposed methods are then applied on the CWNR case, which motivates this thesis. (author)
Applications of advances in nonlinear sensitivity analysis
Energy Technology Data Exchange (ETDEWEB)
Werbos, P J
1982-01-01
The following paper summarizes the major properties and applications of a collection of algorithms involving differentiation and optimization at minimum cost. The areas of application include the sensitivity analysis of models, new work in statistical or econometric estimation, optimization, artificial intelligence and neuron modelling.
*Corresponding Author Sensitivity Analysis of a Physiochemical ...
African Journals Online (AJOL)
Michael Horsfall
The numerical method of sensitivity or the principle of parsimony ... analysis is a widely applied numerical method often being used in the .... Chemical Engineering Journal 128(2-3), 85-93. Amod S ... coupled 3-PG and soil organic matter.
Intelligent process mapping through systematic improvement of heuristics
Ieumwananonthachai, Arthur; Aizawa, Akiko N.; Schwartz, Steven R.; Wah, Benjamin W.; Yan, Jerry C.
1992-01-01
The present system for automatic learning/evaluation of novel heuristic methods applicable to the mapping of communication-process sets on a computer network has its basis in the testing of a population of competing heuristic methods within a fixed time-constraint. The TEACHER 4.1 prototype learning system implemented or learning new postgame analysis heuristic methods iteratively generates and refines the mappings of a set of communicating processes on a computer network. A systematic exploration of the space of possible heuristic methods is shown to promise significant improvement.
Sensitivity Analysis in Two-Stage DEA
Directory of Open Access Journals (Sweden)
Athena Forghani
2015-07-01
Full Text Available Data envelopment analysis (DEA is a method for measuring the efficiency of peer decision making units (DMUs which uses a set of inputs to produce a set of outputs. In some cases, DMUs have a two-stage structure, in which the first stage utilizes inputs to produce outputs used as the inputs of the second stage to produce final outputs. One important issue in two-stage DEA is the sensitivity of the results of an analysis to perturbations in the data. The current paper looks into combined model for two-stage DEA and applies the sensitivity analysis to DMUs on the entire frontier. In fact, necessary and sufficient conditions for preserving a DMU's efficiency classiffication are developed when various data changes are applied to all DMUs.
Sensitivity Analysis in Two-Stage DEA
Directory of Open Access Journals (Sweden)
Athena Forghani
2015-12-01
Full Text Available Data envelopment analysis (DEA is a method for measuring the efficiency of peer decision making units (DMUs which uses a set of inputs to produce a set of outputs. In some cases, DMUs have a two-stage structure, in which the first stage utilizes inputs to produce outputs used as the inputs of the second stage to produce final outputs. One important issue in two-stage DEA is the sensitivity of the results of an analysis to perturbations in the data. The current paper looks into combined model for two-stage DEA and applies the sensitivity analysis to DMUs on the entire frontier. In fact, necessary and sufficient conditions for preserving a DMU's efficiency classiffication are developed when various data changes are applied to all DMUs.
Sensitivity analysis and related analysis : A survey of statistical techniques
Kleijnen, J.P.C.
1995-01-01
This paper reviews the state of the art in five related types of analysis, namely (i) sensitivity or what-if analysis, (ii) uncertainty or risk analysis, (iii) screening, (iv) validation, and (v) optimization. The main question is: when should which type of analysis be applied; which statistical
Sensitivity Analysis in Sequential Decision Models.
Chen, Qiushi; Ayer, Turgay; Chhatwal, Jagpreet
2017-02-01
Sequential decision problems are frequently encountered in medical decision making, which are commonly solved using Markov decision processes (MDPs). Modeling guidelines recommend conducting sensitivity analyses in decision-analytic models to assess the robustness of the model results against the uncertainty in model parameters. However, standard methods of conducting sensitivity analyses cannot be directly applied to sequential decision problems because this would require evaluating all possible decision sequences, typically in the order of trillions, which is not practically feasible. As a result, most MDP-based modeling studies do not examine confidence in their recommended policies. In this study, we provide an approach to estimate uncertainty and confidence in the results of sequential decision models. First, we provide a probabilistic univariate method to identify the most sensitive parameters in MDPs. Second, we present a probabilistic multivariate approach to estimate the overall confidence in the recommended optimal policy considering joint uncertainty in the model parameters. We provide a graphical representation, which we call a policy acceptability curve, to summarize the confidence in the optimal policy by incorporating stakeholders' willingness to accept the base case policy. For a cost-effectiveness analysis, we provide an approach to construct a cost-effectiveness acceptability frontier, which shows the most cost-effective policy as well as the confidence in that for a given willingness to pay threshold. We demonstrate our approach using a simple MDP case study. We developed a method to conduct sensitivity analysis in sequential decision models, which could increase the credibility of these models among stakeholders.
Global sensitivity analysis by polynomial dimensional decomposition
Energy Technology Data Exchange (ETDEWEB)
Rahman, Sharif, E-mail: rahman@engineering.uiowa.ed [College of Engineering, The University of Iowa, Iowa City, IA 52242 (United States)
2011-07-15
This paper presents a polynomial dimensional decomposition (PDD) method for global sensitivity analysis of stochastic systems subject to independent random input following arbitrary probability distributions. The method involves Fourier-polynomial expansions of lower-variate component functions of a stochastic response by measure-consistent orthonormal polynomial bases, analytical formulae for calculating the global sensitivity indices in terms of the expansion coefficients, and dimension-reduction integration for estimating the expansion coefficients. Due to identical dimensional structures of PDD and analysis-of-variance decomposition, the proposed method facilitates simple and direct calculation of the global sensitivity indices. Numerical results of the global sensitivity indices computed for smooth systems reveal significantly higher convergence rates of the PDD approximation than those from existing methods, including polynomial chaos expansion, random balance design, state-dependent parameter, improved Sobol's method, and sampling-based methods. However, for non-smooth functions, the convergence properties of the PDD solution deteriorate to a great extent, warranting further improvements. The computational complexity of the PDD method is polynomial, as opposed to exponential, thereby alleviating the curse of dimensionality to some extent.
Demonstration sensitivity analysis for RADTRAN III
International Nuclear Information System (INIS)
Neuhauser, K.S.; Reardon, P.C.
1986-10-01
A demonstration sensitivity analysis was performed to: quantify the relative importance of 37 variables to the total incident free dose; assess the elasticity of seven dose subgroups to those same variables; develop density distributions for accident dose to combinations of accident data under wide-ranging variations; show the relationship between accident consequences and probabilities of occurrence; and develop limits for the variability of probability consequence curves
Conspicuous Waste and Representativeness Heuristic
Directory of Open Access Journals (Sweden)
Tatiana M. Shishkina
2017-12-01
Full Text Available The article deals with the similarities between conspicuous waste and representativeness heuristic. The conspicuous waste is analyzed according to the classic Veblen’ interpretation as a strategy to increase social status through conspicuous consumption and conspicuous leisure. In “The Theory of the Leisure Class” Veblen introduced two different types of utility – conspicuous and functional. The article focuses on the possible benefits of the analysis of conspicuous utility not only in terms of institutional economic theory, but also in terms of behavioral economics. To this end, the representativeness heuristics is considered, on the one hand, as a way to optimize the decision-making process, which allows to examine it in comparison with procedural rationality by Simon. On the other hand, it is also analyzed as cognitive bias within the Kahneman and Twersky’ approach. The article provides the analysis of the patterns in the deviations from the rational behavior strategy that could be observed in case of conspicuous waste both in modern market economies in the form of conspicuous consumption and in archaic economies in the form of gift-exchange. The article also focuses on the marketing strategies for luxury consumption’ advertisement. It highlights the impact of the symbolic capital (in Bourdieu’ interpretation on the social and symbolic payments that actors get from the act of conspicuous waste. This allows to perform a analysis of conspicuous consumption both as a rational way to get the particular kind of payments, and, at the same time, as a form of institutionalized cognitive bias.
Systemization of burnup sensitivity analysis code. 2
International Nuclear Information System (INIS)
Tatsumi, Masahiro; Hyoudou, Hideaki
2005-02-01
Towards the practical use of fast reactors, it is a very important subject to improve prediction accuracy for neutronic properties in LMFBR cores from the viewpoint of improvements on plant efficiency with rationally high performance cores and that on reliability and safety margins. A distinct improvement on accuracy in nuclear core design has been accomplished by the development of adjusted nuclear library using the cross-section adjustment method, in which the results of criticality experiments of JUPITER and so on are reflected. In the design of large LMFBR cores, however, it is important to accurately estimate not only neutronic characteristics, for example, reaction rate distribution and control rod worth but also burnup characteristics, for example, burnup reactivity loss, breeding ratio and so on. For this purpose, it is desired to improve prediction accuracy of burnup characteristics using the data widely obtained in actual core such as the experimental fast reactor 'JOYO'. The analysis of burnup characteristics is needed to effectively use burnup characteristics data in the actual cores based on the cross-section adjustment method. So far, a burnup sensitivity analysis code, SAGEP-BURN, has been developed and confirmed its effectiveness. However, there is a problem that analysis sequence become inefficient because of a big burden to users due to complexity of the theory of burnup sensitivity and limitation of the system. It is also desired to rearrange the system for future revision since it is becoming difficult to implement new functions in the existing large system. It is not sufficient to unify each computational component for the following reasons; the computational sequence may be changed for each item being analyzed or for purpose such as interpretation of physical meaning. Therefore, it is needed to systemize the current code for burnup sensitivity analysis with component blocks of functionality that can be divided or constructed on occasion. For
Automatic Single Event Effects Sensitivity Analysis of a 13-Bit Successive Approximation ADC
Márquez, F.; Muñoz, F.; Palomo, F. R.; Sanz, L.; López-Morillo, E.; Aguirre, M. A.; Jiménez, A.
2015-08-01
This paper presents Analog Fault Tolerant University of Seville Debugging System (AFTU), a tool to evaluate the Single-Event Effect (SEE) sensitivity of analog/mixed signal microelectronic circuits at transistor level. As analog cells can behave in an unpredictable way when critical areas interact with the particle hitting, there is a need for designers to have a software tool that allows an automatic and exhaustive analysis of Single-Event Effects influence. AFTU takes the test-bench SPECTRE design, emulates radiation conditions and automatically evaluates vulnerabilities using user-defined heuristics. To illustrate the utility of the tool, the SEE sensitivity of a 13-bits Successive Approximation Analog-to-Digital Converter (ADC) has been analysed. This circuit was selected not only because it was designed for space applications, but also due to the fact that a manual SEE sensitivity analysis would be too time-consuming. After a user-defined test campaign, it was detected that some voltage transients were propagated to a node where a parasitic diode was activated, affecting the offset cancelation, and therefore the whole resolution of the ADC. A simple modification of the scheme solved the problem, as it was verified with another automatic SEE sensitivity analysis.
Heuristic decision making in medicine
Marewski, Julian N.; Gigerenzer, Gerd
2012-01-01
Can less information be more helpful when it comes to making medical decisions? Contrary to the common intuition that more information is always better, the use of heuristics can help both physicians and patients to make sound decisions. Heuristics are simple decision strategies that ignore part of the available information, basing decisions on only a few relevant predictors. We discuss: (i) how doctors and patients use heuristics; and (ii) when heuristics outperform information-greedy methods, such as regressions in medical diagnosis. Furthermore, we outline those features of heuristics that make them useful in health care settings. These features include their surprising accuracy, transparency, and wide accessibility, as well as the low costs and little time required to employ them. We close by explaining one of the statistical reasons why heuristics are accurate, and by pointing to psychiatry as one area for future research on heuristics in health care. PMID:22577307
Heuristic decision making in medicine.
Marewski, Julian N; Gigerenzer, Gerd
2012-03-01
Can less information be more helpful when it comes to making medical decisions? Contrary to the common intuition that more information is always better, the use of heuristics can help both physicians and patients to make sound decisions. Heuristics are simple decision strategies that ignore part of the available information, basing decisions on only a few relevant predictors. We discuss: (i) how doctors and patients use heuristics; and (ii) when heuristics outperform information-greedy methods, such as regressions in medical diagnosis. Furthermore, we outline those features of heuristics that make them useful in health care settings. These features include their surprising accuracy, transparency, and wide accessibility, as well as the low costs and little time required to employ them. We close by explaining one of the statistical reasons why heuristics are accurate, and by pointing to psychiatry as one area for future research on heuristics in health care.
Swift and Smart Decision Making: Heuristics that Work
Hoy, Wayne K.; Tarter, C. J.
2010-01-01
Purpose: The aim of this paper is to examine the research literature on decision making and identify and develop a set of heuristics that work for school decision makers. Design/methodology/approach: This analysis is a synthesis of the research on decision-making heuristics that work. Findings: A set of nine rules for swift and smart decision…
Directory of Open Access Journals (Sweden)
Viktor Ivanovich Petrov
2017-01-01
Full Text Available The article considers the issues of civil aviation aircraft onboard computers data safety. Infor- mation security undeclared capabilities stand for technical equipment or software possibilities, which are not mentioned in the documentation. Documentation and tests content requirements are imposed during the software certification. Documentation requirements include documents composition and content of control (specification, description and program code, the source code. Test requirements include: static analysis of program codes (including the compliance of the sources with their loading modules monitoring; dynamic analysis of source code (including implementation of routes monitor- ing. Currently, there are no complex measures for checking onboard computer software. There are no rules and regulations that can allow controlling foreign production aircraft software, and the actual receiving of software is difficult. Consequently, the author suggests developing the basics of aviation rules and regulations, which allow to analyze the programs of CA aircraft onboard computers. If there are no software source codes the two approaches of code analysis are used: a structural static and dy- namic analysis of the source code; signature-heuristic analysis of potentially dangerous operations. Static analysis determines the behavior of the program by reading the program code (without running the program which is represented in the assembler language - disassembly listing. Program tracing is performed by the dynamic analysis. The analysis of aircraft software ability to detect undeclared capa- bilities using the interactive disassembler was considered in this article.
Systemization of burnup sensitivity analysis code
International Nuclear Information System (INIS)
Tatsumi, Masahiro; Hyoudou, Hideaki
2004-02-01
To practical use of fact reactors, it is a very important subject to improve prediction accuracy for neutronic properties in LMFBR cores from the viewpoints of improvements on plant efficiency with rationally high performance cores and that on reliability and safety margins. A distinct improvement on accuracy in nuclear core design has been accomplished by development of adjusted nuclear library using the cross-section adjustment method, in which the results of critical experiments of JUPITER and so on are reflected. In the design of large LMFBR cores, however, it is important to accurately estimate not only neutronic characteristics, for example, reaction rate distribution and control rod worth but also burnup characteristics, for example, burnup reactivity loss, breeding ratio and so on. For this purpose, it is desired to improve prediction accuracy of burnup characteristics using the data widely obtained in actual core such as the experimental fast reactor core 'JOYO'. The analysis of burnup characteristics is needed to effectively use burnup characteristics data in the actual cores based on the cross-section adjustment method. So far, development of a analysis code for burnup sensitivity, SAGEP-BURN, has been done and confirmed its effectiveness. However, there is a problem that analysis sequence become inefficient because of a big burden to user due to complexity of the theory of burnup sensitivity and limitation of the system. It is also desired to rearrange the system for future revision since it is becoming difficult to implement new functionalities in the existing large system. It is not sufficient to unify each computational component for some reasons; computational sequence may be changed for each item being analyzed or for purpose such as interpretation of physical meaning. Therefore it is needed to systemize the current code for burnup sensitivity analysis with component blocks of functionality that can be divided or constructed on occasion. For this
Morris, Graham P.; Simonov, Alexandr N.; Mashkina, Elena A.; Bordas, Rafel; Gillow, Kathryn; Baker, Ruth E.; Gavaghan, David J.; Bond, Alan M.
2013-01-01
Fully automated and computer assisted heuristic data analysis approaches have been applied to a series of AC voltammetric experiments undertaken on the [Fe(CN)6]3-/4- process at a glassy carbon electrode in 3 M KCl aqueous electrolyte. The recovered
International Nuclear Information System (INIS)
Barber, A. D.; Busch, R.
2009-01-01
The goal of this work is to obtain sensitivities from direct uncertainty analysis calculation and correlate those calculated values with the sensitivities produced from TSUNAMI-3D (Tools for Sensitivity and Uncertainty Analysis Methodology Implementation in Three Dimensions). A full sensitivity analysis is performed on a critical experiment to determine the overall uncertainty of the experiment. Small perturbation calculations are performed for all known uncertainties to obtain the total uncertainty of the experiment. The results from a critical experiment are only known as well as the geometric and material properties. The goal of this relationship is to simplify the uncertainty quantification process in assessing a critical experiment, while still considering all of the important parameters. (authors)
Sensitivity analysis of the Two Geometry Method
International Nuclear Information System (INIS)
Wichers, V.A.
1993-09-01
The Two Geometry Method (TGM) was designed specifically for the verification of the uranium enrichment of low enriched UF 6 gas in the presence of uranium deposits on the pipe walls. Complications can arise if the TGM is applied under extreme conditions, such as deposits larger than several times the gas activity, small pipe diameters less than 40 mm and low pressures less than 150 Pa. This report presents a comprehensive sensitivity analysis of the TGM. The impact of the various sources of uncertainty on the performance of the method is discussed. The application to a practical case is based on worst case conditions with regards to the measurement conditions, and on realistic conditions with respect to the false alarm probability and the non detection probability. Monte Carlo calculations were used to evaluate the sensitivity for sources of uncertainty which are experimentally inaccessible. (orig.)
A heuristic for the inventory management of smart vending machine systems
Directory of Open Access Journals (Sweden)
Yang-Byung Park
2012-12-01
Full Text Available Purpose: The purpose of this paper is to propose a heuristic for the inventory management of smart vending machine systems with product substitution under the replenishment point, order-up-to level policy and to evaluate its performance.Design/methodology/approach: The heuristic is developed on the basis of the decoupled approach. An integer linear mathematical model is built to determine the number of product storage compartments and replenishment threshold for each smart vending machine in the system and the Clarke and Wright’s savings algorithm is applied to route vehicles for inventory replenishments of smart vending machines that share the same delivery days. Computational experiments are conducted on several small-size test problems to compare the proposed heuristic with the integrated optimization mathematical model with respect to system profit. Furthermore, a sensitivity analysis is carried out on a medium-size test problem to evaluate the effect of the customer service level on system profit using a computer simulation.Findings: The results show that the proposed heuristic yielded pretty good solutions with 5.7% error rate on average compared to the optimal solutions. The proposed heuristic took about 3 CPU minutes on average in the test problems being consisted of 10 five-product smart vending machines. It was confirmed that the system profit is significantly affected by the customer service level.Originality/value: The inventory management of smart vending machine systems is newly treated. Product substitutions are explicitly considered in the model. The proposed heuristic is effective as well as efficient. It can be easily modified for application to various retail vending settings under a vendor-managed inventory scheme with POS system.
Sensitivity analysis of reactive ecological dynamics.
Verdy, Ariane; Caswell, Hal
2008-08-01
Ecological systems with asymptotically stable equilibria may exhibit significant transient dynamics following perturbations. In some cases, these transient dynamics include the possibility of excursions away from the equilibrium before the eventual return; systems that exhibit such amplification of perturbations are called reactive. Reactivity is a common property of ecological systems, and the amplification can be large and long-lasting. The transient response of a reactive ecosystem depends on the parameters of the underlying model. To investigate this dependence, we develop sensitivity analyses for indices of transient dynamics (reactivity, the amplification envelope, and the optimal perturbation) in both continuous- and discrete-time models written in matrix form. The sensitivity calculations require expressions, some of them new, for the derivatives of equilibria, eigenvalues, singular values, and singular vectors, obtained using matrix calculus. Sensitivity analysis provides a quantitative framework for investigating the mechanisms leading to transient growth. We apply the methodology to a predator-prey model and a size-structured food web model. The results suggest predator-driven and prey-driven mechanisms for transient amplification resulting from multispecies interactions.
Global sensitivity analysis using polynomial chaos expansions
International Nuclear Information System (INIS)
Sudret, Bruno
2008-01-01
Global sensitivity analysis (SA) aims at quantifying the respective effects of input random variables (or combinations thereof) onto the variance of the response of a physical or mathematical model. Among the abundant literature on sensitivity measures, the Sobol' indices have received much attention since they provide accurate information for most models. The paper introduces generalized polynomial chaos expansions (PCE) to build surrogate models that allow one to compute the Sobol' indices analytically as a post-processing of the PCE coefficients. Thus the computational cost of the sensitivity indices practically reduces to that of estimating the PCE coefficients. An original non intrusive regression-based approach is proposed, together with an experimental design of minimal size. Various application examples illustrate the approach, both from the field of global SA (i.e. well-known benchmark problems) and from the field of stochastic mechanics. The proposed method gives accurate results for various examples that involve up to eight input random variables, at a computational cost which is 2-3 orders of magnitude smaller than the traditional Monte Carlo-based evaluation of the Sobol' indices
Global sensitivity analysis using polynomial chaos expansions
Energy Technology Data Exchange (ETDEWEB)
Sudret, Bruno [Electricite de France, R and D Division, Site des Renardieres, F 77818 Moret-sur-Loing Cedex (France)], E-mail: bruno.sudret@edf.fr
2008-07-15
Global sensitivity analysis (SA) aims at quantifying the respective effects of input random variables (or combinations thereof) onto the variance of the response of a physical or mathematical model. Among the abundant literature on sensitivity measures, the Sobol' indices have received much attention since they provide accurate information for most models. The paper introduces generalized polynomial chaos expansions (PCE) to build surrogate models that allow one to compute the Sobol' indices analytically as a post-processing of the PCE coefficients. Thus the computational cost of the sensitivity indices practically reduces to that of estimating the PCE coefficients. An original non intrusive regression-based approach is proposed, together with an experimental design of minimal size. Various application examples illustrate the approach, both from the field of global SA (i.e. well-known benchmark problems) and from the field of stochastic mechanics. The proposed method gives accurate results for various examples that involve up to eight input random variables, at a computational cost which is 2-3 orders of magnitude smaller than the traditional Monte Carlo-based evaluation of the Sobol' indices.
Investigating the Impacts of Design Heuristics on Idea Initiation and Development
Kramer, Julia; Daly, Shanna R.; Yilmaz, Seda; Seifert, Colleen M.; Gonzalez, Richard
2015-01-01
This paper presents an analysis of engineering students' use of Design Heuristics as part of a team project in an undergraduate engineering design course. Design Heuristics are an empirically derived set of cognitive "rules of thumb" for use in concept generation. We investigated heuristic use in the initial concept generation phase,…
Contributions to sensitivity analysis and generalized discriminant analysis
International Nuclear Information System (INIS)
Jacques, J.
2005-12-01
Two topics are studied in this thesis: sensitivity analysis and generalized discriminant analysis. Global sensitivity analysis of a mathematical model studies how the output variables of this last react to variations of its inputs. The methods based on the study of the variance quantify the part of variance of the response of the model due to each input variable and each subset of input variables. The first subject of this thesis is the impact of a model uncertainty on results of a sensitivity analysis. Two particular forms of uncertainty are studied: that due to a change of the model of reference, and that due to the use of a simplified model with the place of the model of reference. A second problem was studied during this thesis, that of models with correlated inputs. Indeed, classical sensitivity indices not having significance (from an interpretation point of view) in the presence of correlation of the inputs, we propose a multidimensional approach consisting in expressing the sensitivity of the output of the model to groups of correlated variables. Applications in the field of nuclear engineering illustrate this work. Generalized discriminant analysis consists in classifying the individuals of a test sample in groups, by using information contained in a training sample, when these two samples do not come from the same population. This work extends existing methods in a Gaussian context to the case of binary data. An application in public health illustrates the utility of generalized discrimination models thus defined. (author)
Heuristics for Multidimensional Packing Problems
DEFF Research Database (Denmark)
Egeblad, Jens
for a minimum height container required for the items. The main contributions of the thesis are three new heuristics for strip-packing and knapsack packing problems where items are both rectangular and irregular. In the two first papers we describe a heuristic for the multidimensional strip-packing problem...... that is based on a relaxed placement principle. The heuristic starts with a random overlapping placement of items and large container dimensions. From the overlapping placement overlap is reduced iteratively until a non-overlapping placement is found and a new problem is solved with a smaller container size...... of this heuristic are among the best published in the literature both for two- and three-dimensional strip-packing problems for irregular shapes. In the third paper, we introduce a heuristic for two- and three-dimensional rectangular knapsack packing problems. The two-dimensional heuristic uses the sequence pair...
Simple Sensitivity Analysis for Orion GNC
Pressburger, Tom; Hoelscher, Brian; Martin, Rodney; Sricharan, Kumar
2013-01-01
The performance of Orion flight software, especially its GNC software, is being analyzed by running Monte Carlo simulations of Orion spacecraft flights. The simulated performance is analyzed for conformance with flight requirements, expressed as performance constraints. Flight requirements include guidance (e.g. touchdown distance from target) and control (e.g., control saturation) as well as performance (e.g., heat load constraints). The Monte Carlo simulations disperse hundreds of simulation input variables, for everything from mass properties to date of launch.We describe in this paper a sensitivity analysis tool (Critical Factors Tool or CFT) developed to find the input variables or pairs of variables which by themselves significantly influence satisfaction of requirements or significantly affect key performance metrics (e.g., touchdown distance from target). Knowing these factors can inform robustness analysis, can inform where engineering resources are most needed, and could even affect operations. The contributions of this paper include the introduction of novel sensitivity measures, such as estimating success probability, and a technique for determining whether pairs of factors are interacting dependently or independently. The tool found that input variables such as moments, mass, thrust dispersions, and date of launch were found to be significant factors for success of various requirements. Examples are shown in this paper as well as a summary and physics discussion of EFT-1 driving factors that the tool found.
Sensitivity analysis of floating offshore wind farms
International Nuclear Information System (INIS)
Castro-Santos, Laura; Diaz-Casas, Vicente
2015-01-01
Highlights: • Develop a sensitivity analysis of a floating offshore wind farm. • Influence on the life-cycle costs involved in a floating offshore wind farm. • Influence on IRR, NPV, pay-back period, LCOE and cost of power. • Important variables: distance, wind resource, electric tariff, etc. • It helps to investors to take decisions in the future. - Abstract: The future of offshore wind energy will be in deep waters. In this context, the main objective of the present paper is to develop a sensitivity analysis of a floating offshore wind farm. It will show how much the output variables can vary when the input variables are changing. For this purpose two different scenarios will be taken into account: the life-cycle costs involved in a floating offshore wind farm (cost of conception and definition, cost of design and development, cost of manufacturing, cost of installation, cost of exploitation and cost of dismantling) and the most important economic indexes in terms of economic feasibility of a floating offshore wind farm (internal rate of return, net present value, discounted pay-back period, levelized cost of energy and cost of power). Results indicate that the most important variables in economic terms are the number of wind turbines and the distance from farm to shore in the costs’ scenario, and the wind scale parameter and the electric tariff for the economic indexes. This study will help investors to take into account these variables in the development of floating offshore wind farms in the future
A Tutorial on Heuristic Methods
DEFF Research Database (Denmark)
Vidal, Rene Victor Valqui; Werra, D. de; Silver, E.
1980-01-01
In this paper we define a heuristic method as a procedure for solving a well-defined mathematical problem by an intuitive approach in which the structure of the problem can be interpreted and exploited intelligently to obtain a reasonable solution. Issues discussed include: (i) the measurement...... of the quality of a heuristic method, (ii) different types of heuristic procedures, (iii) the interactive role of human beings and (iv) factors that may influence the choice or testing of heuristic methods. A large number of references are included....
Pieterse, A.H.; de Vries, M.
2013-01-01
Background Increasingly, patient decision aids and values clarification methods (VCMs) are being developed to support patients in making preference-sensitive health-care decisions. Many VCMs encourage extensive deliberation about options, without solid theoretical or empirical evidence showing that
Sensitivity analysis of a modified energy model
International Nuclear Information System (INIS)
Suganthi, L.; Jagadeesan, T.R.
1997-01-01
Sensitivity analysis is carried out to validate model formulation. A modified model has been developed to predict the future energy requirement of coal, oil and electricity, considering price, income, technological and environmental factors. The impact and sensitivity of the independent variables on the dependent variable are analysed. The error distribution pattern in the modified model as compared to a conventional time series model indicated the absence of clusters. The residual plot of the modified model showed no distinct pattern of variation. The percentage variation of error in the conventional time series model for coal and oil ranges from -20% to +20%, while for electricity it ranges from -80% to +20%. However, in the case of the modified model the percentage variation in error is greatly reduced - for coal it ranges from -0.25% to +0.15%, for oil -0.6% to +0.6% and for electricity it ranges from -10% to +10%. The upper and lower limit consumption levels at 95% confidence is determined. The consumption at varying percentage changes in price and population are analysed. The gap between the modified model predictions at varying percentage changes in price and population over the years from 1990 to 2001 is found to be increasing. This is because of the increasing rate of energy consumption over the years and also the confidence level decreases as the projection is made far into the future. (author)
Sensitivity Analysis for Design Optimization Integrated Software Tools, Phase I
National Aeronautics and Space Administration — The objective of this proposed project is to provide a new set of sensitivity analysis theory and codes, the Sensitivity Analysis for Design Optimization Integrated...
THE HEURISTIC FUNCTION OF SPORT
Directory of Open Access Journals (Sweden)
Adam Petrović
2012-09-01
Full Text Available Being a significant area of human activity, sport has multiple functions. One of the more important functions of sport, especially top sport, is the inventive heuristic function. Creative work, being a process of creating new values, represents a significant possibility for advancement of sport. This paper aims at pointing at the various dimensions of human creative work, at the creative work which can be seen in sport (in a narrow sense and at the scientific and practical areas which borderline sport. The method of theoretical analysis of different approaches to the phenomenon of creative work , both in general and in sport, was applied in this paper. This area can be systematized according to various criterion : the level of creative work, different fields where it appears, the subjects of creative work - creators etc. Case analysis shows that the field of creative work in sport is widening and deepening constantly. There are different levels of creativity not only in the system of training and competition, but in a wider social context of sport as well. As a process of human spirit and mind the creative work belongs not just to athletes and coaches, but also to all the people and social groups who's creative power manifests itself in sport. The classification of creative work in sport according to various criterion allows for heuristic function of sport to be explained comprehensively and to create an image how do the sparks of human spirit improve the micro cosmos of sport. A thorough classification of creative work in sport allows for a detailed analysis of all the elements of creative work and each of it’s area in sport. In this way the progress in sport , as a consequence of innovations in both competitions and athletes’ training and of everything that goes with those activities, can be guided into the needed direction more easily as well as studied and applied.
About the use of rank transformation in sensitivity analysis of model output
International Nuclear Information System (INIS)
Saltelli, Andrea; Sobol', Ilya M
1995-01-01
Rank transformations are frequently employed in numerical experiments involving a computational model, especially in the context of sensitivity and uncertainty analyses. Response surface replacement and parameter screening are tasks which may benefit from a rank transformation. Ranks can cope with nonlinear (albeit monotonic) input-output distributions, allowing the use of linear regression techniques. Rank transformed statistics are more robust, and provide a useful solution in the presence of long tailed input and output distributions. As is known to practitioners, care must be employed when interpreting the results of such analyses, as any conclusion drawn using ranks does not translate easily to the original model. In the present note an heuristic approach is taken, to explore, by way of practical examples, the effect of a rank transformation on the outcome of a sensitivity analysis. An attempt is made to identify trends, and to correlate these effects to a model taxonomy. Employing sensitivity indices, whereby the total variance of the model output is decomposed into a sum of terms of increasing dimensionality, we show that the main effect of the rank transformation is to increase the relative weight of the first order terms (the 'main effects'), at the expense of the 'interactions' and 'higher order interactions'. As a result the influence of those parameters which influence the output mostly by way of interactions may be overlooked in an analysis based on the ranks. This difficulty increases with the dimensionality of the problem, and may lead to the failure of a rank based sensitivity analysis. We suggest that the models can be ranked, with respect to the complexity of their input-output relationship, by mean of an 'Association' index I y . I y may complement the usual model coefficient of determination R y 2 as a measure of model complexity for the purpose of uncertainty and sensitivity analysis
Sensitivity analysis approaches applied to systems biology models.
Zi, Z
2011-11-01
With the rising application of systems biology, sensitivity analysis methods have been widely applied to study the biological systems, including metabolic networks, signalling pathways and genetic circuits. Sensitivity analysis can provide valuable insights about how robust the biological responses are with respect to the changes of biological parameters and which model inputs are the key factors that affect the model outputs. In addition, sensitivity analysis is valuable for guiding experimental analysis, model reduction and parameter estimation. Local and global sensitivity analysis approaches are the two types of sensitivity analysis that are commonly applied in systems biology. Local sensitivity analysis is a classic method that studies the impact of small perturbations on the model outputs. On the other hand, global sensitivity analysis approaches have been applied to understand how the model outputs are affected by large variations of the model input parameters. In this review, the author introduces the basic concepts of sensitivity analysis approaches applied to systems biology models. Moreover, the author discusses the advantages and disadvantages of different sensitivity analysis methods, how to choose a proper sensitivity analysis approach, the available sensitivity analysis tools for systems biology models and the caveats in the interpretation of sensitivity analysis results.
A new importance measure for sensitivity analysis
International Nuclear Information System (INIS)
Liu, Qiao; Homma, Toshimitsu
2010-01-01
Uncertainty is an integral part of risk assessment of complex engineering systems, such as nuclear power plants and space crafts. The aim of sensitivity analysis is to identify the contribution of the uncertainty in model inputs to the uncertainty in the model output. In this study, a new importance measure that characterizes the influence of the entire input distribution on the entire output distribution was proposed. It represents the expected deviation of the cumulative distribution function (CDF) of the model output that would be obtained when one input parameter of interest were known. The applicability of this importance measure was tested with two models, a nonlinear nonmonotonic mathematical model and a risk model. In addition, a comparison of this new importance measure with several other importance measures was carried out and the differences between these measures were explained. (author)
DEA Sensitivity Analysis for Parallel Production Systems
Directory of Open Access Journals (Sweden)
J. Gerami
2011-06-01
Full Text Available In this paper, we introduce systems consisting of several production units, each of which include several subunits working in parallel. Meanwhile, each subunit is working independently. The input and output of each production unit are the sums of the inputs and outputs of its subunits, respectively. We consider each of these subunits as an independent decision making unit(DMU and create the production possibility set(PPS produced by these DMUs, in which the frontier points are considered as efficient DMUs. Then we introduce models for obtaining the efficiency of the production subunits. Using super-efficiency models, we categorize all efficient subunits into different efficiency classes. Then we follow by presenting the sensitivity analysis and stability problem for efficient subunits, including extreme efficient and non-extreme efficient subunits, assuming simultaneous perturbations in all inputs and outputs of subunits such that the efficiency of the subunit under evaluation declines while the efficiencies of other subunits improve.
Sensitivity of SBLOCA analysis to model nodalization
International Nuclear Information System (INIS)
Lee, C.; Ito, T.; Abramson, P.B.
1983-01-01
The recent Semiscale test S-UT-8 indicates the possibility for primary liquid to hang up in the steam generators during a SBLOCA, permitting core uncovery prior to loop-seal clearance. In analysis of Small Break Loss of Coolant Accidents with RELAP5, it is found that resultant transient behavior is quite sensitive to the selection of nodalization for the steam generators. Although global parameters such as integrated mass loss, primary inventory and primary pressure are relatively insensitive to the nodalization, it is found that the predicted distribution of inventory around the primary is significantly affected by nodalization. More detailed nodalization predicts that more of the inventory tends to remain in the steam generators, resulting in less inventory in the reactor vessel and therefore causing earlier and more severe core uncovery
Subset simulation for structural reliability sensitivity analysis
International Nuclear Information System (INIS)
Song Shufang; Lu Zhenzhou; Qiao Hongwei
2009-01-01
Based on two procedures for efficiently generating conditional samples, i.e. Markov chain Monte Carlo (MCMC) simulation and importance sampling (IS), two reliability sensitivity (RS) algorithms are presented. On the basis of reliability analysis of Subset simulation (Subsim), the RS of the failure probability with respect to the distribution parameter of the basic variable is transformed as a set of RS of conditional failure probabilities with respect to the distribution parameter of the basic variable. By use of the conditional samples generated by MCMC simulation and IS, procedures are established to estimate the RS of the conditional failure probabilities. The formulae of the RS estimator, its variance and its coefficient of variation are derived in detail. The results of the illustrations show high efficiency and high precision of the presented algorithms, and it is suitable for highly nonlinear limit state equation and structural system with single and multiple failure modes
Heuristics Reasoning in Diagnostic Judgment.
O'Neill, Eileen S.
1995-01-01
Describes three heuristics--short-cut mental strategies that streamline information--relevant to diagnostic reasoning: accessibility, similarity, and anchoring and adjustment. Analyzes factors thought to influence heuristic reasoning and presents interventions to be tested for nursing practice and education. (JOW)
Reexamining Our Bias against Heuristics
McLaughlin, Kevin; Eva, Kevin W.; Norman, Geoff R.
2014-01-01
Using heuristics offers several cognitive advantages, such as increased speed and reduced effort when making decisions, in addition to allowing us to make decision in situations where missing data do not allow for formal reasoning. But the traditional view of heuristics is that they trade accuracy for efficiency. Here the authors discuss sources…
HEURISTIC APPROACHES FOR PORTFOLIO OPTIMIZATION
Manfred Gilli, Evis Kellezi
2000-01-01
The paper first compares the use of optimization heuristics to the classical optimization techniques for the selection of optimal portfolios. Second, the heuristic approach is applied to problems other than those in the standard mean-variance framework where the classical optimization fails.
Calibration, validation, and sensitivity analysis: What's what
International Nuclear Information System (INIS)
Trucano, T.G.; Swiler, L.P.; Igusa, T.; Oberkampf, W.L.; Pilch, M.
2006-01-01
One very simple interpretation of calibration is to adjust a set of parameters associated with a computational science and engineering code so that the model agreement is maximized with respect to a set of experimental data. One very simple interpretation of validation is to quantify our belief in the predictive capability of a computational code through comparison with a set of experimental data. Uncertainty in both the data and the code are important and must be mathematically understood to correctly perform both calibration and validation. Sensitivity analysis, being an important methodology in uncertainty analysis, is thus important to both calibration and validation. In this paper, we intend to clarify the language just used and express some opinions on the associated issues. We will endeavor to identify some technical challenges that must be resolved for successful validation of a predictive modeling capability. One of these challenges is a formal description of a 'model discrepancy' term. Another challenge revolves around the general adaptation of abstract learning theory as a formalism that potentially encompasses both calibration and validation in the face of model uncertainty
Heuristics structure and pervade formal risk assessment.
MacGillivray, Brian H
2014-04-01
Lay perceptions of risk appear rooted more in heuristics than in reason. A major concern of the risk regulation literature is that such "error-strewn" perceptions may be replicated in policy, as governments respond to the (mis)fears of the citizenry. This has led many to advocate a relatively technocratic approach to regulating risk, characterized by high reliance on formal risk and cost-benefit analysis. However, through two studies of chemicals regulation, we show that the formal assessment of risk is pervaded by its own set of heuristics. These include rules to categorize potential threats, define what constitutes valid data, guide causal inference, and to select and apply formal models. Some of these heuristics lay claim to theoretical or empirical justifications, others are more back-of-the-envelope calculations, while still more purport not to reflect some truth but simply to constrain discretion or perform a desk-clearing function. These heuristics can be understood as a way of authenticating or formalizing risk assessment as a scientific practice, representing a series of rules for bounding problems, collecting data, and interpreting evidence (a methodology). Heuristics are indispensable elements of induction. And so they are not problematic per se, but they can become so when treated as laws rather than as contingent and provisional rules. Pitfalls include the potential for systematic error, masking uncertainties, strategic manipulation, and entrenchment. Our central claim is that by studying the rules of risk assessment qua rules, we develop a novel representation of the methods, conventions, and biases of the prior art. © 2013 Society for Risk Analysis.
Global sensitivity analysis in wind energy assessment
Tsvetkova, O.; Ouarda, T. B.
2012-12-01
Wind energy is one of the most promising renewable energy sources. Nevertheless, it is not yet a common source of energy, although there is enough wind potential to supply world's energy demand. One of the most prominent obstacles on the way of employing wind energy is the uncertainty associated with wind energy assessment. Global sensitivity analysis (SA) studies how the variation of input parameters in an abstract model effects the variation of the variable of interest or the output variable. It also provides ways to calculate explicit measures of importance of input variables (first order and total effect sensitivity indices) in regard to influence on the variation of the output variable. Two methods of determining the above mentioned indices were applied and compared: the brute force method and the best practice estimation procedure In this study a methodology for conducting global SA of wind energy assessment at a planning stage is proposed. Three sampling strategies which are a part of SA procedure were compared: sampling based on Sobol' sequences (SBSS), Latin hypercube sampling (LHS) and pseudo-random sampling (PRS). A case study of Masdar City, a showcase of sustainable living in the UAE, is used to exemplify application of the proposed methodology. Sources of uncertainty in wind energy assessment are very diverse. In the case study the following were identified as uncertain input parameters: the Weibull shape parameter, the Weibull scale parameter, availability of a wind turbine, lifetime of a turbine, air density, electrical losses, blade losses, ineffective time losses. Ineffective time losses are defined as losses during the time when the actual wind speed is lower than the cut-in speed or higher than the cut-out speed. The output variable in the case study is the lifetime energy production. Most influential factors for lifetime energy production are identified with the ranking of the total effect sensitivity indices. The results of the present
Theory of Randomized Search Heuristics in Combinatorial Optimization
DEFF Research Database (Denmark)
The rigorous mathematical analysis of randomized search heuristics(RSHs) with respect to their expected runtime is a growing research area where many results have been obtained in recent years. This class of heuristics includes well-known approaches such as Randomized Local Search (RLS), the Metr......The rigorous mathematical analysis of randomized search heuristics(RSHs) with respect to their expected runtime is a growing research area where many results have been obtained in recent years. This class of heuristics includes well-known approaches such as Randomized Local Search (RLS...... analysis of randomized algorithms to RSHs. Mostly, the expected runtime of RSHs on selected problems is analzyed. Thereby, we understand why and when RSHs are efficient optimizers and, conversely, when they cannot be efficient. The tutorial will give an overview on the analysis of RSHs for solving...
Frontier Assignment for Sensitivity Analysis of Data Envelopment Analysis
Naito, Akio; Aoki, Shingo; Tsuji, Hiroshi
To extend the sensitivity analysis capability for DEA (Data Envelopment Analysis), this paper proposes frontier assignment based DEA (FA-DEA). The basic idea of FA-DEA is to allow a decision maker to decide frontier intentionally while the traditional DEA and Super-DEA decide frontier computationally. The features of FA-DEA are as follows: (1) provides chances to exclude extra-influential DMU (Decision Making Unit) and finds extra-ordinal DMU, and (2) includes the function of the traditional DEA and Super-DEA so that it is able to deal with sensitivity analysis more flexibly. Simple numerical study has shown the effectiveness of the proposed FA-DEA and the difference from the traditional DEA.
Sensitivity analysis of Smith's AMRV model
International Nuclear Information System (INIS)
Ho, Chih-Hsiang
1995-01-01
Multiple-expert hazard/risk assessments have considerable precedent, particularly in the Yucca Mountain site characterization studies. In this paper, we present a Bayesian approach to statistical modeling in volcanic hazard assessment for the Yucca Mountain site. Specifically, we show that the expert opinion on the site disruption parameter p is elicited on the prior distribution, π (p), based on geological information that is available. Moreover, π (p) can combine all available geological information motivated by conflicting but realistic arguments (e.g., simulation, cluster analysis, structural control, etc.). The incorporated uncertainties about the probability of repository disruption p, win eventually be averaged out by taking the expectation over π (p). We use the following priors in the analysis: priors chosen for mathematical convenience: Beta (r, s) for (r, s) = (2, 2), (3, 3), (5, 5), (2, 1), (2, 8), (8, 2), and (1, 1); and three priors motivated by expert knowledge. Sensitivity analysis is performed for each prior distribution. Estimated values of hazard based on the priors chosen for mathematical simplicity are uniformly higher than those obtained based on the priors motivated by expert knowledge. And, the model using the prior, Beta (8,2), yields the highest hazard (= 2.97 X 10 -2 ). The minimum hazard is produced by the open-quotes three-expert priorclose quotes (i.e., values of p are equally likely at 10 -3 10 -2 , and 10 -1 ). The estimate of the hazard is 1.39 x which is only about one order of magnitude smaller than the maximum value. The term, open-quotes hazardclose quotes, is defined as the probability of at least one disruption of a repository at the Yucca Mountain site by basaltic volcanism for the next 10,000 years
Directory of Open Access Journals (Sweden)
M. Omidvari
2015-09-01
Full Text Available Introduction: Occupational accidents are of the main issues in industries. It is necessary to identify the main root causes of accidents for their control. Several models have been proposed for determining the accidents root causes. FTA is one of the most widely used models which could graphically establish the root causes of accidents. The non-linear function is one of the main challenges in FTA compliance and in order to obtain the exact number, the meta-heuristic algorithms can be used. Material and Method: The present research was done in power plant industries in construction phase. In this study, a pattern for the analysis of human error in work-related accidents was provided by combination of neural network algorithms and FTA analytical model. Finally, using this pattern, the potential rate of all causes was determined. Result: The results showed that training, age, and non-compliance with safety principals in the workplace were the most important factors influencing human error in the occupational accident. Conclusion: According to the obtained results, it can be concluded that human errors can be greatly reduced by training, right choice of workers with regard to the type of occupations, and provision of appropriate safety conditions in the work place.
Heuristics to Evaluate Interactive Systems for Children with Autism Spectrum Disorder (ASD).
Khowaja, Kamran; Salim, Siti Salwah; Asemi, Adeleh
2015-01-01
In this paper, we adapted and expanded a set of guidelines, also known as heuristics, to evaluate the usability of software to now be appropriate for software aimed at children with autism spectrum disorder (ASD). We started from the heuristics developed by Nielsen in 1990 and developed a modified set of 15 heuristics. The first 5 heuristics of this set are the same as those of the original Nielsen set, the next 5 heuristics are improved versions of Nielsen's, whereas the last 5 heuristics are new. We present two evaluation studies of our new heuristics. In the first, two groups compared Nielsen's set with the modified set of heuristics, with each group evaluating two interactive systems. The Nielsen's heuristics were assigned to the control group while the experimental group was given the modified set of heuristics, and a statistical analysis was conducted to determine the effectiveness of the modified set, the contribution of 5 new heuristics and the impact of 5 improved heuristics. The results show that the modified set is significantly more effective than the original, and we found a significant difference between the five improved heuristics and their corresponding heuristics in the original set. The five new heuristics are effective in problem identification using the modified set. The second study was conducted using a system which was developed to ascertain if the modified set was effective at identifying usability problems that could be fixed before the release of software. The post-study analysis revealed that the majority of the usability problems identified by the experts were fixed in the updated version of the system.
Heuristics to Evaluate Interactive Systems for Children with Autism Spectrum Disorder (ASD.
Directory of Open Access Journals (Sweden)
Kamran Khowaja
Full Text Available In this paper, we adapted and expanded a set of guidelines, also known as heuristics, to evaluate the usability of software to now be appropriate for software aimed at children with autism spectrum disorder (ASD. We started from the heuristics developed by Nielsen in 1990 and developed a modified set of 15 heuristics. The first 5 heuristics of this set are the same as those of the original Nielsen set, the next 5 heuristics are improved versions of Nielsen's, whereas the last 5 heuristics are new. We present two evaluation studies of our new heuristics. In the first, two groups compared Nielsen's set with the modified set of heuristics, with each group evaluating two interactive systems. The Nielsen's heuristics were assigned to the control group while the experimental group was given the modified set of heuristics, and a statistical analysis was conducted to determine the effectiveness of the modified set, the contribution of 5 new heuristics and the impact of 5 improved heuristics. The results show that the modified set is significantly more effective than the original, and we found a significant difference between the five improved heuristics and their corresponding heuristics in the original set. The five new heuristics are effective in problem identification using the modified set. The second study was conducted using a system which was developed to ascertain if the modified set was effective at identifying usability problems that could be fixed before the release of software. The post-study analysis revealed that the majority of the usability problems identified by the experts were fixed in the updated version of the system.
Wear-Out Sensitivity Analysis Project Abstract
Harris, Adam
2015-01-01
During the course of the Summer 2015 internship session, I worked in the Reliability and Maintainability group of the ISS Safety and Mission Assurance department. My project was a statistical analysis of how sensitive ORU's (Orbital Replacement Units) are to a reliability parameter called the wear-out characteristic. The intended goal of this was to determine a worst case scenario of how many spares would be needed if multiple systems started exhibiting wear-out characteristics simultaneously. The goal was also to determine which parts would be most likely to do so. In order to do this, my duties were to take historical data of operational times and failure times of these ORU's and use them to build predictive models of failure using probability distribution functions, mainly the Weibull distribution. Then, I ran Monte Carlo Simulations to see how an entire population of these components would perform. From here, my final duty was to vary the wear-out characteristic from the intrinsic value, to extremely high wear-out values and determine how much the probability of sufficiency of the population would shift. This was done for around 30 different ORU populations on board the ISS.
Supercritical extraction of oleaginous: parametric sensitivity analysis
Directory of Open Access Journals (Sweden)
Santos M.M.
2000-01-01
Full Text Available The economy has become universal and competitive, thus the industries of vegetable oil extraction must advance in the sense of minimising production costs and, at the same time, generating products that obey more rigorous patterns of quality, including solutions that do not damage the environment. The conventional oilseed processing uses hexane as solvent. However, this solvent is toxic and highly flammable. Thus the search of substitutes for hexane in oleaginous extraction process has increased in the last years. The supercritical carbon dioxide is a potential substitute for hexane, but it is necessary more detailed studies to understand the phenomena taking place in such process. Thus, in this work a diffusive model for semi-continuous (batch for the solids and continuous for the solvent isothermal and isobaric extraction process using supercritical carbon dioxide is presented and submitted to a parametric sensitivity analysis by means of a factorial design in two levels. The model parameters were disturbed and their main effects analysed, so that it is possible to propose strategies for high performance operation.
Sensitivity analysis of ranked data: from order statistics to quantiles
Heidergott, B.F.; Volk-Makarewicz, W.
2015-01-01
In this paper we provide the mathematical theory for sensitivity analysis of order statistics of continuous random variables, where the sensitivity is with respect to a distributional parameter. Sensitivity analysis of order statistics over a finite number of observations is discussed before
SENSIT: a cross-section and design sensitivity and uncertainty analysis code
International Nuclear Information System (INIS)
Gerstl, S.A.W.
1980-01-01
SENSIT computes the sensitivity and uncertainty of a calculated integral response (such as a dose rate) due to input cross sections and their uncertainties. Sensitivity profiles are computed for neutron and gamma-ray reaction cross sections of standard multigroup cross section sets and for secondary energy distributions (SEDs) of multigroup scattering matrices. In the design sensitivity mode, SENSIT computes changes in an integral response due to design changes and gives the appropriate sensitivity coefficients. Cross section uncertainty analyses are performed for three types of input data uncertainties: cross-section covariance matrices for pairs of multigroup reaction cross sections, spectral shape uncertainty parameters for secondary energy distributions (integral SED uncertainties), and covariance matrices for energy-dependent response functions. For all three types of data uncertainties SENSIT computes the resulting variance and estimated standard deviation in an integral response of interest, on the basis of generalized perturbation theory. SENSIT attempts to be more comprehensive than earlier sensitivity analysis codes, such as SWANLAKE
Multitarget global sensitivity analysis of n-butanol combustion.
Zhou, Dingyu D Y; Davis, Michael J; Skodje, Rex T
2013-05-02
A model for the combustion of butanol is studied using a recently developed theoretical method for the systematic improvement of the kinetic mechanism. The butanol mechanism includes 1446 reactions, and we demonstrate that it is straightforward and computationally feasible to implement a full global sensitivity analysis incorporating all the reactions. In addition, we extend our previous analysis of ignition-delay targets to include species targets. The combination of species and ignition targets leads to multitarget global sensitivity analysis, which allows for a more complete mechanism validation procedure than we previously implemented. The inclusion of species sensitivity analysis allows for a direct comparison between reaction pathway analysis and global sensitivity analysis.
Sensitivity analysis in multi-parameter probabilistic systems
International Nuclear Information System (INIS)
Walker, J.R.
1987-01-01
Probabilistic methods involving the use of multi-parameter Monte Carlo analysis can be applied to a wide range of engineering systems. The output from the Monte Carlo analysis is a probabilistic estimate of the system consequence, which can vary spatially and temporally. Sensitivity analysis aims to examine how the output consequence is influenced by the input parameter values. Sensitivity analysis provides the necessary information so that the engineering properties of the system can be optimized. This report details a package of sensitivity analysis techniques that together form an integrated methodology for the sensitivity analysis of probabilistic systems. The techniques have known confidence limits and can be applied to a wide range of engineering problems. The sensitivity analysis methodology is illustrated by performing the sensitivity analysis of the MCROC rock microcracking model
Heuristics, biases and traps in managerial decision making
Directory of Open Access Journals (Sweden)
Peter Gál
2013-01-01
Full Text Available The aim of the paper is to demonstrate the impact of heuristics, biases and psychological traps on the decision making. Heuristics are unconscious routines people use to cope with the complexity inherent in most decision situations. They serve as mental shortcuts that help people to simplify and structure the information encountered in the world. These heuristics could be quite useful in some situations, while in others they can lead to severe and systematic errors, based on significant deviations from the fundamental principles of statistics, probability and sound judgment. This paper focuses on illustrating the existence of the anchoring, availability, and representativeness heuristics, originally described by Tversky & Kahneman in the early 1970’s. The anchoring heuristic is a tendency to focus on the initial information, estimate or perception (even random or irrelevant number as a starting point. People tend to give disproportionate weight to the initial information they receive. The availability heuristic explains why highly imaginable or vivid information have a disproportionate effect on people’s decisions. The representativeness heuristic causes that people rely on highly specific scenarios, ignore base rates, draw conclusions based on small samples and neglect scope. Mentioned phenomena are illustrated and supported by evidence based on the statistical analysis of the results of a questionnaire.
An ESDIRK Method with Sensitivity Analysis Capabilities
DEFF Research Database (Denmark)
Kristensen, Morten Rode; Jørgensen, John Bagterp; Thomsen, Per Grove
2004-01-01
of the sensitivity equations. A key feature is the reuse of information already computed for the state integration, hereby minimizing the extra effort required for sensitivity integration. Through case studies the new algorithm is compared to an extrapolation method and to the more established BDF based approaches...
Sensitivity Analysis of Fire Dynamics Simulation
DEFF Research Database (Denmark)
Brohus, Henrik; Nielsen, Peter V.; Petersen, Arnkell J.
2007-01-01
(Morris method). The parameters considered are selected among physical parameters and program specific parameters. The influence on the calculation result as well as the CPU time is considered. It is found that the result is highly sensitive to many parameters even though the sensitivity varies...
Paranoid thinking as a heuristic.
Preti, Antonio; Cella, Matteo
2010-08-01
Paranoid thinking can be viewed as a human heuristic used by individuals to deal with uncertainty during stressful situations. Under stress, individuals are likely to emphasize the threatening value of neutral stimuli and increase the reliance on paranoia-based heuristic to interpreter events and guide their decisions. Paranoid thinking can also be activated by stress arising from the possibility of losing a good opportunity; this may result in an abnormal allocation of attentional resources to social agents. A better understanding of the interplay between cognitive heuristics and emotional processes may help to detect situations in which paranoid thinking is likely to exacerbate and improve intervention for individuals with delusional disorders.
Superconducting Accelerating Cavity Pressure Sensitivity Analysis
International Nuclear Information System (INIS)
Rodnizki, J.; Horvits, Z.; Ben Aliz, Y.; Grin, A.; Weissman, L.
2014-01-01
The measured sensitivity of the cavity was evaluated and it is full consistent with the measured values. It was explored that the tuning system (the fog structure) has a significant contribution to the cavity sensitivity. By using ribs or by modifying the rigidity of the fog we may reduce the HWR sensitivity. During cool down and warming up we have to analyze the stresses on the HWR to avoid plastic deformation to the HWR since the Niobium yield is an order of magnitude lower in room temperature
Derivative based sensitivity analysis of gamma index
Directory of Open Access Journals (Sweden)
Biplab Sarkar
2015-01-01
Full Text Available Originally developed as a tool for patient-specific quality assurance in advanced treatment delivery methods to compare between measured and calculated dose distributions, the gamma index (γ concept was later extended to compare between any two dose distributions. It takes into effect both the dose difference (DD and distance-to-agreement (DTA measurements in the comparison. Its strength lies in its capability to give a quantitative value for the analysis, unlike other methods. For every point on the reference curve, if there is at least one point in the evaluated curve that satisfies the pass criteria (e.g., δDD = 1%, δDTA = 1 mm, the point is included in the quantitative score as "pass." Gamma analysis does not account for the gradient of the evaluated curve - it looks at only the minimum gamma value, and if it is <1, then the point passes, no matter what the gradient of evaluated curve is. In this work, an attempt has been made to present a derivative-based method for the identification of dose gradient. A mathematically derived reference profile (RP representing the penumbral region of 6 MV 10 cm × 10 cm field was generated from an error function. A general test profile (GTP was created from this RP by introducing 1 mm distance error and 1% dose error at each point. This was considered as the first of the two evaluated curves. By its nature, this curve is a smooth curve and would satisfy the pass criteria for all points in it. The second evaluated profile was generated as a sawtooth test profile (STTP which again would satisfy the pass criteria for every point on the RP. However, being a sawtooth curve, it is not a smooth one and would be obviously poor when compared with the smooth profile. Considering the smooth GTP as an acceptable profile when it passed the gamma pass criteria (1% DD and 1 mm DTA against the RP, the first and second order derivatives of the DDs (δD', δD" between these two curves were derived and used as the
Structural Sustainability - Heuristic Approach
Rostański, Krzysztof
2017-10-01
Nowadays, we are faced with a challenge of having to join building structures with elements of nature, which seems to be the paradigm of modern planning and design. The questions arise, however, with reference to the following categories: the leading idea, the relation between elements of nature and buildings, the features of a structure combining such elements and, finally, our perception of this structure. If we consider both the overwhelming globalization and our attempts to preserve local values, the only reasonable solution is to develop naturalistic greenery. It can add its uniqueness to any building and to any developed area. Our holistic model, presented in this paper, contains the above mentioned categories within the scope of naturalism. The model is divided into principles, actions related, and possible effects to be obtained. It provides a useful tool for determining the ways and priorities of our design. Although it is not possible to consider all possible actions and solutions in order to support sustainability in any particular design, we can choose, however, a proper mode for our design according to the local conditions by turning to the heuristic method, which helps to choose priorities and targets. Our approach is an attempt to follow the ways of nature as in the natural environment it is optimal solutions that appear and survive, idealism being the domain of mankind only. We try to describe various natural processes in a manner comprehensible to us, which is always a generalization. Such definitions, however, called artificial by naturalists, are presented as art or the current state of knowledge by artists and engineers. Reality, in fact, is always more complicated than its definitions. The heuristic method demonstrates the way how to optimize our design. It requires that all possible information about the local environment should be gathered, as the more is known, the fewer mistakes are made. Following the unquestionable principles, we can
MOVES2010a regional level sensitivity analysis
2012-12-10
This document discusses the sensitivity of various input parameter effects on emission rates using the US Environmental Protection Agencys (EPAs) MOVES2010a model at the regional level. Pollutants included in the study are carbon monoxide (CO),...
Heuristic introduction to gravitational waves
International Nuclear Information System (INIS)
Sandberg, V.D.
1982-01-01
The purpose of this article is to provide a rough and somewhat heuristic theoretical background and introduction to gravitational radiation, its generation, and its detection based on Einstein's general theory of relativity
Heuristic reasoning and relative incompleteness
Treur, J.
1993-01-01
In this paper an approach is presented in which heuristic reasoning is interpreted as strategic reasoning. This type of reasoning enables one to derive which hypothesis to investigate, and which observable information to acquire next (to be able to verify the chosen hypothesis). A compositional architecture for reasoning systems that perform such heuristic reasoning is introduced, called SIX (for Strategic Interactive eXpert systems). This compositional architecture enables user interaction a...
Kia, Seyed Mostafa; Vega Pons, Sandro; Weisz, Nathan; Passerini, Andrea
2016-01-01
Brain decoding is a popular multivariate approach for hypothesis testing in neuroimaging. Linear classifiers are widely employed in the brain decoding paradigm to discriminate among experimental conditions. Then, the derived linear weights are visualized in the form of multivariate brain maps to further study spatio-temporal patterns of underlying neural activities. It is well known that the brain maps derived from weights of linear classifiers are hard to interpret because of high correlations between predictors, low signal to noise ratios, and the high dimensionality of neuroimaging data. Therefore, improving the interpretability of brain decoding approaches is of primary interest in many neuroimaging studies. Despite extensive studies of this type, at present, there is no formal definition for interpretability of multivariate brain maps. As a consequence, there is no quantitative measure for evaluating the interpretability of different brain decoding methods. In this paper, first, we present a theoretical definition of interpretability in brain decoding; we show that the interpretability of multivariate brain maps can be decomposed into their reproducibility and representativeness. Second, as an application of the proposed definition, we exemplify a heuristic for approximating the interpretability in multivariate analysis of evoked magnetoencephalography (MEG) responses. Third, we propose to combine the approximated interpretability and the generalization performance of the brain decoding into a new multi-objective criterion for model selection. Our results, for the simulated and real MEG data, show that optimizing the hyper-parameters of the regularized linear classifier based on the proposed criterion results in more informative multivariate brain maps. More importantly, the presented definition provides the theoretical background for quantitative evaluation of interpretability, and hence, facilitates the development of more effective brain decoding algorithms
A Heuristic Model for Supporting Users’ Decision-Making in Privacy Disclosure for Recommendation
Directory of Open Access Journals (Sweden)
Hongchen Wu
2018-01-01
Full Text Available Privacy issues have become a major concern in the web of resource sharing, and users often have difficulty managing their information disclosure in the context of high-quality experiences from social media and Internet of Things. Recent studies have shown that users’ disclosure decisions may be influenced by heuristics from the crowds, leading to inconsistency in the disclosure volumes and reduction of the prediction accuracy. Therefore, an analysis of why this influence occurs and how to optimize the user experience is highly important. We propose a novel heuristic model that defines the data structures of items and participants in social media, utilizes a modified decision-tree classifier that can predict participants’ disclosures, and puts forward a correlation analysis for detecting disclosure inconsistences. The heuristic model is applied to real-time dataset to evaluate the behavioral effects. Decision-tree classifier and correlation analysis indeed prove that some participants’ behaviors in information disclosures became decreasingly correlated during item requesting. Participants can be “persuaded” to change their disclosure behaviors, and the users’ answers to the mildly sensitive items tend to be more variable and less predictable. Using this approach, recommender systems in social media can thus know the users better and provide service with higher prediction accuracy.
International Nuclear Information System (INIS)
Ragheb, M.; Gvillo, D.; Makowitz, H.
1987-01-01
HAL-1987 is a general-purpose tool for the construction of production-rule analysis systems. It uses the rule-based paradigm from the part of artificial intelligence concerned with knowledge engineering. It uses backward-chaining and forward-chaining in an antecedent-consequent logic, and is programmed in Portable Standard Lisp (PSL). The inference engine is flexible and accommodates general additions and modifications to the knowledge base. The system is used in coupled symbolic-procedural programming adaptive methodologies for stochastic simulations. In Monte Carlo simulations of particle transport, the system considers the pre-processing of the input data to the simulation and adaptively controls the variance reduction process as the simulation progresses. This is accomplished through the use of a knowledge base of rules which encompass the user's expertise in the variance reduction process. It is also applied to the construction of model-based systems for monitoring, fault-diagnosis and crisis-alert in engineering devices, particularly in the field of nuclear reactor safety analysis
NPV Sensitivity Analysis: A Dynamic Excel Approach
Mangiero, George A.; Kraten, Michael
2017-01-01
Financial analysts generally create static formulas for the computation of NPV. When they do so, however, it is not readily apparent how sensitive the value of NPV is to changes in multiple interdependent and interrelated variables. It is the aim of this paper to analyze this variability by employing a dynamic, visually graphic presentation using…
Sensitivity Analysis for Multidisciplinary Systems (SAMS)
2016-12-01
release. Distribution is unlimited. 14 Server and Client Code Server from geometry import Point, Geometry import math import zmq class Server...public release; Distribution is unlimited. DISTRIBUTION STATEMENT A: Approved for public release. Distribution is unlimited. 19 Example Application Boeing...Materials Conference, 2011. Cross, D. M., Local continuum sensitivity method for shape design derivatives using spatial gradient reconstruction. Diss
Heuristic space diversity management in a meta-hyper-heuristic framework
CSIR Research Space (South Africa)
Grobler, J
2014-07-01
Full Text Available This paper introduces the concept of heuristic space diversity and investigates various strategies for the management of heuristic space diversity within the context of a meta-hyper-heuristic algorithm. Evaluation on a diverse set of floating...
Heuristic space diversity control for improved meta-hyper-heuristic performance
CSIR Research Space (South Africa)
Grobler, J
2015-04-01
Full Text Available This paper expands on the concept of heuristic space diversity and investigates various strategies for the management of heuristic space diversity within the context of a meta-hyper-heuristic algorithm in search of greater performance benefits...
Extended forward sensitivity analysis of one-dimensional isothermal flow
International Nuclear Information System (INIS)
Johnson, M.; Zhao, H.
2013-01-01
Sensitivity analysis and uncertainty quantification is an important part of nuclear safety analysis. In this work, forward sensitivity analysis is used to compute solution sensitivities on 1-D fluid flow equations typical of those found in system level codes. Time step sensitivity analysis is included as a method for determining the accumulated error from time discretization. The ability to quantify numerical error arising from the time discretization is a unique and important feature of this method. By knowing the relative sensitivity of time step with other physical parameters, the simulation is allowed to run at optimized time steps without affecting the confidence of the physical parameter sensitivity results. The time step forward sensitivity analysis method can also replace the traditional time step convergence studies that are a key part of code verification with much less computational cost. One well-defined benchmark problem with manufactured solutions is utilized to verify the method; another test isothermal flow problem is used to demonstrate the extended forward sensitivity analysis process. Through these sample problems, the paper shows the feasibility and potential of using the forward sensitivity analysis method to quantify uncertainty in input parameters and time step size for a 1-D system-level thermal-hydraulic safety code. (authors)
The role of sensitivity analysis in probabilistic safety assessment
International Nuclear Information System (INIS)
Hirschberg, S.; Knochenhauer, M.
1987-01-01
The paper describes several items suitable for close examination by means of application of sensitivity analysis, when performing a level 1 PSA. Sensitivity analyses are performed with respect to; (1) boundary conditions, (2) operator actions, and (3) treatment of common cause failures (CCFs). The items of main interest are identified continuously in the course of performing a PSA, as well as by scrutinising the final results. The practical aspects of sensitivity analysis are illustrated by several applications from a recent PSA study (ASEA-ATOM BWR 75). It is concluded that sensitivity analysis leads to insights important for analysts, reviewers and decision makers. (orig./HP)
Automated sensitivity analysis using the GRESS language
International Nuclear Information System (INIS)
Pin, F.G.; Oblow, E.M.; Wright, R.Q.
1986-04-01
An automated procedure for performing large-scale sensitivity studies based on the use of computer calculus is presented. The procedure is embodied in a FORTRAN precompiler called GRESS, which automatically processes computer models and adds derivative-taking capabilities to the normal calculated results. In this report, the GRESS code is described, tested against analytic and numerical test problems, and then applied to a major geohydrological modeling problem. The SWENT nuclear waste repository modeling code is used as the basis for these studies. Results for all problems are discussed in detail. Conclusions are drawn as to the applicability of GRESS in the problems at hand and for more general large-scale modeling sensitivity studies
Sensitivity Analysis of a Simplified Fire Dynamic Model
DEFF Research Database (Denmark)
Sørensen, Lars Schiøtt; Nielsen, Anker
2015-01-01
This paper discusses a method for performing a sensitivity analysis of parameters used in a simplified fire model for temperature estimates in the upper smoke layer during a fire. The results from the sensitivity analysis can be used when individual parameters affecting fire safety are assessed...
The affect heuristic in occupational safety.
Savadori, Lucia; Caovilla, Jessica; Zaniboni, Sara; Fraccaroli, Franco
2015-07-08
The affect heuristic is a rule of thumb according to which, in the process of making a judgment or decision, people use affect as a cue. If a stimulus elicits positive affect then risks associated to that stimulus are viewed as low and benefits as high; conversely, if the stimulus elicits negative affect, then risks are perceived as high and benefits as low. The basic tenet of this study is that affect heuristic guides worker's judgment and decision making in a risk situation. The more the worker likes her/his organization the less she/he will perceive the risks as high. A sample of 115 employers and 65 employees working in small family agricultural businesses completed a questionnaire measuring perceived safety costs, psychological safety climate, affective commitment and safety compliance. A multi-sample structural analysis supported the thesis that safety compliance can be explained through an affect-based heuristic reasoning, but only for employers. Positive affective commitment towards their family business reduced employers' compliance with safety procedures by increasing the perceived cost of implementing them.
When decision heuristics and science collide.
Yu, Erica C; Sprenger, Amber M; Thomas, Rick P; Dougherty, Michael R
2014-04-01
The ongoing discussion among scientists about null-hypothesis significance testing and Bayesian data analysis has led to speculation about the practices and consequences of "researcher degrees of freedom." This article advances this debate by asking the broader questions that we, as scientists, should be asking: How do scientists make decisions in the course of doing research, and what is the impact of these decisions on scientific conclusions? We asked practicing scientists to collect data in a simulated research environment, and our findings show that some scientists use data collection heuristics that deviate from prescribed methodology. Monte Carlo simulations show that data collection heuristics based on p values lead to biases in estimated effect sizes and Bayes factors and to increases in both false-positive and false-negative rates, depending on the specific heuristic. We also show that using Bayesian data collection methods does not eliminate these biases. Thus, our study highlights the little appreciated fact that the process of doing science is a behavioral endeavor that can bias statistical description and inference in a manner that transcends adherence to any particular statistical framework.
Energy Technology Data Exchange (ETDEWEB)
Gonzalez C, J.; Martin del Campo M, C.; Francois L, J.L. [Facultad de Ingenieria, UNAM, Paseo Cuauhnahuac 8532, 62550 Jiutepec, Morelos (Mexico)
2004-07-01
The objective of this work is to verify the validity of the heuristic rules that have been applied in the processes of radial optimization of fuel cells. It was examined the rule with respect to the accommodation of fuel in the corners of the cell and it became special attention on the influence of the position and concentration of those pellets with gadolinium in the reactivity of the cell and the safety parameters. The evaluation behaved on designed cells violating the heuristic rules. For both cases the cells were analyzed between infinite using the HELIOS code. Additionally, for the second case, it was behaved a stage more exhaustive where it was used one of the studied cells that it completed those safety parameters and of reactivity to generate the design of an assemble that was used to calculate with CM-PRESTO the behavior of the nucleus during three operation cycles. (Author)
Development of Heuristic Bias Detection in Elementary School
De Neys, Wim; Feremans, Vicky
2013-01-01
Although human reasoning is often biased by intuitive heuristics, recent studies have shown that adults and adolescents detect the biased nature of their judgments. The present study focused on the development of this critical bias sensitivity by examining the detection skills of young children in elementary school. Third and 6th graders were…
New insights into diversification of hyper-heuristics.
Ren, Zhilei; Jiang, He; Xuan, Jifeng; Hu, Yan; Luo, Zhongxuan
2014-10-01
There has been a growing research trend of applying hyper-heuristics for problem solving, due to their ability of balancing the intensification and the diversification with low level heuristics. Traditionally, the diversification mechanism is mostly realized by perturbing the incumbent solutions to escape from local optima. In this paper, we report our attempt toward providing a new diversification mechanism, which is based on the concept of instance perturbation. In contrast to existing approaches, the proposed mechanism achieves the diversification by perturbing the instance under solving, rather than the solutions. To tackle the challenge of incorporating instance perturbation into hyper-heuristics, we also design a new hyper-heuristic framework HIP-HOP (recursive acronym of HIP-HOP is an instance perturbation-based hyper-heuristic optimization procedure), which employs a grammar guided high level strategy to manipulate the low level heuristics. With the expressive power of the grammar, the constraints, such as the feasibility of the output solution could be easily satisfied. Numerical results and statistical tests over both the Ising spin glass problem and the p -median problem instances show that HIP-HOP is able to achieve promising performances. Furthermore, runtime distribution analysis reveals that, although being relatively slow at the beginning, HIP-HOP is able to achieve competitive solutions once given sufficient time.
Heuristic errors in clinical reasoning.
Rylander, Melanie; Guerrasio, Jeannette
2016-08-01
Errors in clinical reasoning contribute to patient morbidity and mortality. The purpose of this study was to determine the types of heuristic errors made by third-year medical students and first-year residents. This study surveyed approximately 150 clinical educators inquiring about the types of heuristic errors they observed in third-year medical students and first-year residents. Anchoring and premature closure were the two most common errors observed amongst third-year medical students and first-year residents. There was no difference in the types of errors observed in the two groups. Errors in clinical reasoning contribute to patient morbidity and mortality Clinical educators perceived that both third-year medical students and first-year residents committed similar heuristic errors, implying that additional medical knowledge and clinical experience do not affect the types of heuristic errors made. Further work is needed to help identify methods that can be used to reduce heuristic errors early in a clinician's education. © 2015 John Wiley & Sons Ltd.
Global Sensitivity Analysis of Environmental Models: Convergence, Robustness and Validation
Sarrazin, Fanny; Pianosi, Francesca; Khorashadi Zadeh, Farkhondeh; Van Griensven, Ann; Wagener, Thorsten
2015-04-01
Global Sensitivity Analysis aims to characterize the impact that variations in model input factors (e.g. the parameters) have on the model output (e.g. simulated streamflow). In sampling-based Global Sensitivity Analysis, the sample size has to be chosen carefully in order to obtain reliable sensitivity estimates while spending computational resources efficiently. Furthermore, insensitive parameters are typically identified through the definition of a screening threshold: the theoretical value of their sensitivity index is zero but in a sampling-base framework they regularly take non-zero values. There is little guidance available for these two steps in environmental modelling though. The objective of the present study is to support modellers in making appropriate choices, regarding both sample size and screening threshold, so that a robust sensitivity analysis can be implemented. We performed sensitivity analysis for the parameters of three hydrological models with increasing level of complexity (Hymod, HBV and SWAT), and tested three widely used sensitivity analysis methods (Elementary Effect Test or method of Morris, Regional Sensitivity Analysis, and Variance-Based Sensitivity Analysis). We defined criteria based on a bootstrap approach to assess three different types of convergence: the convergence of the value of the sensitivity indices, of the ranking (the ordering among the parameters) and of the screening (the identification of the insensitive parameters). We investigated the screening threshold through the definition of a validation procedure. The results showed that full convergence of the value of the sensitivity indices is not necessarily needed to rank or to screen the model input factors. Furthermore, typical values of the sample sizes that are reported in the literature can be well below the sample sizes that actually ensure convergence of ranking and screening.
M. Omidvari; M. R. Gharmaroudi
2015-01-01
Introduction: Occupational accidents are of the main issues in industries. It is necessary to identify the main root causes of accidents for their control. Several models have been proposed for determining the accidents root causes. FTA is one of the most widely used models which could graphically establish the root causes of accidents. The non-linear function is one of the main challenges in FTA compliance and in order to obtain the exact number, the meta-heuristic algorithms can be used. ...
Automating sensitivity analysis of computer models using computer calculus
International Nuclear Information System (INIS)
Oblow, E.M.; Pin, F.G.
1986-01-01
An automated procedure for performing sensitivity analysis has been developed. The procedure uses a new FORTRAN compiler with computer calculus capabilities to generate the derivatives needed to set up sensitivity equations. The new compiler is called GRESS - Gradient Enhanced Software System. Application of the automated procedure with direct and adjoint sensitivity theory for the analysis of non-linear, iterative systems of equations is discussed. Calculational efficiency consideration and techniques for adjoint sensitivity analysis are emphasized. The new approach is found to preserve the traditional advantages of adjoint theory while removing the tedious human effort previously needed to apply this theoretical methodology. Conclusions are drawn about the applicability of the automated procedure in numerical analysis and large-scale modelling sensitivity studies
Accelerated Sensitivity Analysis in High-Dimensional Stochastic Reaction Networks.
Arampatzis, Georgios; Katsoulakis, Markos A; Pantazis, Yannis
2015-01-01
Existing sensitivity analysis approaches are not able to handle efficiently stochastic reaction networks with a large number of parameters and species, which are typical in the modeling and simulation of complex biochemical phenomena. In this paper, a two-step strategy for parametric sensitivity analysis for such systems is proposed, exploiting advantages and synergies between two recently proposed sensitivity analysis methodologies for stochastic dynamics. The first method performs sensitivity analysis of the stochastic dynamics by means of the Fisher Information Matrix on the underlying distribution of the trajectories; the second method is a reduced-variance, finite-difference, gradient-type sensitivity approach relying on stochastic coupling techniques for variance reduction. Here we demonstrate that these two methods can be combined and deployed together by means of a new sensitivity bound which incorporates the variance of the quantity of interest as well as the Fisher Information Matrix estimated from the first method. The first step of the proposed strategy labels sensitivities using the bound and screens out the insensitive parameters in a controlled manner. In the second step of the proposed strategy, a finite-difference method is applied only for the sensitivity estimation of the (potentially) sensitive parameters that have not been screened out in the first step. Results on an epidermal growth factor network with fifty parameters and on a protein homeostasis with eighty parameters demonstrate that the proposed strategy is able to quickly discover and discard the insensitive parameters and in the remaining potentially sensitive parameters it accurately estimates the sensitivities. The new sensitivity strategy can be several times faster than current state-of-the-art approaches that test all parameters, especially in "sloppy" systems. In particular, the computational acceleration is quantified by the ratio between the total number of parameters over the
Accelerated Sensitivity Analysis in High-Dimensional Stochastic Reaction Networks.
Directory of Open Access Journals (Sweden)
Georgios Arampatzis
Full Text Available Existing sensitivity analysis approaches are not able to handle efficiently stochastic reaction networks with a large number of parameters and species, which are typical in the modeling and simulation of complex biochemical phenomena. In this paper, a two-step strategy for parametric sensitivity analysis for such systems is proposed, exploiting advantages and synergies between two recently proposed sensitivity analysis methodologies for stochastic dynamics. The first method performs sensitivity analysis of the stochastic dynamics by means of the Fisher Information Matrix on the underlying distribution of the trajectories; the second method is a reduced-variance, finite-difference, gradient-type sensitivity approach relying on stochastic coupling techniques for variance reduction. Here we demonstrate that these two methods can be combined and deployed together by means of a new sensitivity bound which incorporates the variance of the quantity of interest as well as the Fisher Information Matrix estimated from the first method. The first step of the proposed strategy labels sensitivities using the bound and screens out the insensitive parameters in a controlled manner. In the second step of the proposed strategy, a finite-difference method is applied only for the sensitivity estimation of the (potentially sensitive parameters that have not been screened out in the first step. Results on an epidermal growth factor network with fifty parameters and on a protein homeostasis with eighty parameters demonstrate that the proposed strategy is able to quickly discover and discard the insensitive parameters and in the remaining potentially sensitive parameters it accurately estimates the sensitivities. The new sensitivity strategy can be several times faster than current state-of-the-art approaches that test all parameters, especially in "sloppy" systems. In particular, the computational acceleration is quantified by the ratio between the total number of
Perceived breast cancer risk: Heuristic reasoning and search for a dominance structure
Katapodi, M. C.; Facione, N. C.; Humphreys, J. C.; Dodd, MJ.
2005-01-01
Studies suggest that people construct their risk perceptions by using inferential rules called heuristics. The purpose of this study was to identify heuristics that influence perceived breast cancer risk. We examined 11 interviews from women of diverse ethnic/cultural backgrounds who were recruited from community settings. Narratives in which women elaborated about their own breast cancer risk were analyzed with Argument and Heuristic Reasoning Analysis methodology, which is based on applied ...
The impact of choice context on consumers' choice heuristics
DEFF Research Database (Denmark)
Mueller Loose, Simone; Scholderer, Joachim; Corsi, Armando M.
2012-01-01
Context effects in choice settings have received recent attention but little is known about the impact of context on choice consistency and the extent to which consumers apply choice heuristics. The sequence of alternatives in a choice set is examined here as one specific context effect. We compare...... how a change from a typical price order to a sensory order in wine menus affects consumer choice. We use pre-specified latent heuristic classes to analyse the existence of different choice processes, which begins to untangle the ‘black box’ of how consumers choose. Our findings indicate...... that in the absence of price order, consumers are less price-sensitive, pay more attention to visually salient cues, are less consistent in their choices and employ other simple choice heuristics more frequently than price. Implications for consumer research, marketing and consumer policy are discussed....
Sensitivity Analysis Based on Markovian Integration by Parts Formula
Directory of Open Access Journals (Sweden)
Yongsheng Hang
2017-10-01
Full Text Available Sensitivity analysis is widely applied in financial risk management and engineering; it describes the variations brought by the changes of parameters. Since the integration by parts technique for Markov chains is well developed in recent years, in this paper we apply it for computation of sensitivity and show the closed-form expressions for two commonly-used time-continuous Markovian models. By comparison, we conclude that our approach outperforms the existing technique of computing sensitivity on Markovian models.
Advanced Fuel Cycle Economic Sensitivity Analysis
Energy Technology Data Exchange (ETDEWEB)
David Shropshire; Kent Williams; J.D. Smith; Brent Boore
2006-12-01
A fuel cycle economic analysis was performed on four fuel cycles to provide a baseline for initial cost comparison using the Gen IV Economic Modeling Work Group G4 ECON spreadsheet model, Decision Programming Language software, the 2006 Advanced Fuel Cycle Cost Basis report, industry cost data, international papers, the nuclear power related cost study from MIT, Harvard, and the University of Chicago. The analysis developed and compared the fuel cycle cost component of the total cost of energy for a wide range of fuel cycles including: once through, thermal with fast recycle, continuous fast recycle, and thermal recycle.
The role of sensitivity analysis in assessing uncertainty
International Nuclear Information System (INIS)
Crick, M.J.; Hill, M.D.
1987-01-01
Outside the specialist world of those carrying out performance assessments considerable confusion has arisen about the meanings of sensitivity analysis and uncertainty analysis. In this paper we attempt to reduce this confusion. We then go on to review approaches to sensitivity analysis within the context of assessing uncertainty, and to outline the types of test available to identify sensitive parameters, together with their advantages and disadvantages. The views expressed in this paper are those of the authors; they have not been formally endorsed by the National Radiological Protection Board and should not be interpreted as Board advice
Analysis of Sensitivity Experiments - An Expanded Primer
2017-03-08
conducted with this purpose in mind. Due diligence must be paid to the structure of the dosage levels and to the number of trials. The chosen data...analysis. System reliability is of paramount importance for protecting both the investment of funding and human life . Failing to accurately estimate
Sensitivity analysis of hybrid thermoelastic techniques
W.A. Samad; J.M. Considine
2017-01-01
Stress functions have been used as a complementary tool to support experimental techniques, such as thermoelastic stress analysis (TSA) and digital image correlation (DIC), in an effort to evaluate the complete and separate full-field stresses of loaded structures. The need for such coupling between experimental data and stress functions is due to the fact that...
Automating sensitivity analysis of computer models using computer calculus
International Nuclear Information System (INIS)
Oblow, E.M.; Pin, F.G.
1985-01-01
An automated procedure for performing sensitivity analyses has been developed. The procedure uses a new FORTRAN compiler with computer calculus capabilities to generate the derivatives needed to set up sensitivity equations. The new compiler is called GRESS - Gradient Enhanced Software System. Application of the automated procedure with ''direct'' and ''adjoint'' sensitivity theory for the analysis of non-linear, iterative systems of equations is discussed. Calculational efficiency consideration and techniques for adjoint sensitivity analysis are emphasized. The new approach is found to preserve the traditional advantages of adjoint theory while removing the tedious human effort previously needed to apply this theoretical methodology. Conclusions are drawn about the applicability of the automated procedure in numerical analysis and large-scale modelling sensitivity studies. 24 refs., 2 figs
Sensitivity Analysis of the Critical Speed in Railway Vehicle Dynamics
DEFF Research Database (Denmark)
Bigoni, Daniele; True, Hans; Engsig-Karup, Allan Peter
2014-01-01
We present an approach to global sensitivity analysis aiming at the reduction of its computational cost without compromising the results. The method is based on sampling methods, cubature rules, High-Dimensional Model Representation and Total Sensitivity Indices. The approach has a general applic...
Global and Local Sensitivity Analysis Methods for a Physical System
Morio, Jerome
2011-01-01
Sensitivity analysis is the study of how the different input variations of a mathematical model influence the variability of its output. In this paper, we review the principle of global and local sensitivity analyses of a complex black-box system. A simulated case of application is given at the end of this paper to compare both approaches.…
Adjoint sensitivity analysis of high frequency structures with Matlab
Bakr, Mohamed; Demir, Veysel
2017-01-01
This book covers the theory of adjoint sensitivity analysis and uses the popular FDTD (finite-difference time-domain) method to show how wideband sensitivities can be efficiently estimated for different types of materials and structures. It includes a variety of MATLAB® examples to help readers absorb the content more easily.
Dispersion sensitivity analysis & consistency improvement of APFSDS
Directory of Open Access Journals (Sweden)
Sangeeta Sharma Panda
2017-08-01
In Bore Balloting Motion simulation shows that reduction in residual spin by about 5% results in drastic 56% reduction in first maximum yaw. A correlation between first maximum yaw and residual spin is observed. Results of data analysis are used in design modification for existing ammunition. Number of designs are evaluated numerically before freezing five designs for further soundings. These designs are critically assessed in terms of their comparative performance during In-bore travel & external ballistics phase. Results are validated by free flight trials for the finalised design.
Adjoint sensitivity analysis of plasmonic structures using the FDTD method.
Zhang, Yu; Ahmed, Osman S; Bakr, Mohamed H
2014-05-15
We present an adjoint variable method for estimating the sensitivities of arbitrary responses with respect to the parameters of dispersive discontinuities in nanoplasmonic devices. Our theory is formulated in terms of the electric field components at the vicinity of perturbed discontinuities. The adjoint sensitivities are computed using at most one extra finite-difference time-domain (FDTD) simulation regardless of the number of parameters. Our approach is illustrated through the sensitivity analysis of an add-drop coupler consisting of a square ring resonator between two parallel waveguides. The computed adjoint sensitivities of the scattering parameters are compared with those obtained using the accurate but computationally expensive central finite difference approach.
Sensitivity analysis of the RESRAD, a dose assessment code
International Nuclear Information System (INIS)
Yu, C.; Cheng, J.J.; Zielen, A.J.
1991-01-01
The RESRAD code is a pathway analysis code that is designed to calculate radiation doses and derive soil cleanup criteria for the US Department of Energy's environmental restoration and waste management program. the RESRAD code uses various pathway and consumption-rate parameters such as soil properties and food ingestion rates in performing such calculations and derivations. As with any predictive model, the accuracy of the predictions depends on the accuracy of the input parameters. This paper summarizes the results of a sensitivity analysis of RESRAD input parameters. Three methods were used to perform the sensitivity analysis: (1) Gradient Enhanced Software System (GRESS) sensitivity analysis software package developed at oak Ridge National Laboratory; (2) direct perturbation of input parameters; and (3) built-in graphic package that shows parameter sensitivities while the RESRAD code is operational
A sensitivity analysis approach to optical parameters of scintillation detectors
International Nuclear Information System (INIS)
Ghal-Eh, N.; Koohi-Fayegh, R.
2008-01-01
In this study, an extended version of the Monte Carlo light transport code, PHOTRACK, has been used for a sensitivity analysis to estimate the importance of different wavelength-dependent parameters in the modelling of light collection process in scintillators
sensitivity analysis on flexible road pavement life cycle cost model
African Journals Online (AJOL)
user
of sensitivity analysis on a developed flexible pavement life cycle cost model using varying discount rate. The study .... organizations and specific projects needs based. Life-cycle ... developed and completed urban road infrastructure corridor ...
Sobol’ sensitivity analysis for stressor impacts on honeybee colonies
We employ Monte Carlo simulation and nonlinear sensitivity analysis techniques to describe the dynamics of a bee exposure model, VarroaPop. Daily simulations are performed of hive population trajectories, taking into account queen strength, foraging success, mite impacts, weather...
Heuristic Biases in Mathematical Reasoning
Inglis, Matthew; Simpson, Adrian
2005-01-01
In this paper we briefly describe the dual process account of reasoning, and explain the role of heuristic biases in human thought. Concentrating on the so-called matching bias effect, we describe a piece of research that indicates a correlation between success at advanced level mathematics and an ability to override innate and misleading…
Heuristic reasoning and relative incompleteness
Treur, J.
1993-01-01
In this paper an approach is presented in which heuristic reasoning is interpreted as strategic reasoning. This type of reasoning enables one to derive which hypothesis to investigate, and which observable information to acquire next (to be able to verify the chosen hypothesis). A compositional
Experimental Design for Sensitivity Analysis of Simulation Models
Kleijnen, J.P.C.
2001-01-01
This introductory tutorial gives a survey on the use of statistical designs for what if-or sensitivity analysis in simulation.This analysis uses regression analysis to approximate the input/output transformation that is implied by the simulation model; the resulting regression model is also known as
Sensitivity analysis of numerical solutions for environmental fluid problems
International Nuclear Information System (INIS)
Tanaka, Nobuatsu; Motoyama, Yasunori
2003-01-01
In this study, we present a new numerical method to quantitatively analyze the error of numerical solutions by using the sensitivity analysis. If a reference case of typical parameters is one calculated with the method, no additional calculation is required to estimate the results of the other numerical parameters such as more detailed solutions. Furthermore, we can estimate the strict solution from the sensitivity analysis results and can quantitatively evaluate the reliability of the numerical solution by calculating the numerical error. (author)
Using heuristic search for optimizing maintenance plans
International Nuclear Information System (INIS)
Mutanen, Teemu
2012-01-01
This work addresses the maintenance action selection process. Maintenance personnel need to evaluate maintenance actions and costs to keep the machines in working condition. Group of actions are evaluated together as maintenance plans. The maintenance plans as output provide information to the user about which actions to take if any and what future actions should be prepared for. The heuristic search method is implemented as part of general use toolbox for analysis of measurements from movable work machines. Impacts from machine's usage restrictions and maintenance activities are analysed. The results show that once put on a temporal perspective, the prioritized order of the actions is different and provide additional information to the user.
Advances in heuristic signal processing and applications
Chatterjee, Amitava; Siarry, Patrick
2013-01-01
There have been significant developments in the design and application of algorithms for both one-dimensional signal processing and multidimensional signal processing, namely image and video processing, with the recent focus changing from a step-by-step procedure of designing the algorithm first and following up with in-depth analysis and performance improvement to instead applying heuristic-based methods to solve signal-processing problems. In this book the contributing authors demonstrate both general-purpose algorithms and those aimed at solving specialized application problems, with a spec
Adkins, Daniel E.; McClay, Joseph L.; Vunck, Sarah A.; Batman, Angela M.; Vann, Robert E.; Clark, Shaunna L.; Souza, Renan P.; Crowley, James J.; Sullivan, Patrick F.; van den Oord, Edwin J.C.G.; Beardsley, Patrick M.
2014-01-01
Behavioral sensitization has been widely studied in animal models and is theorized to reflect neural modifications associated with human psychostimulant addiction. While the mesolimbic dopaminergic pathway is known to play a role, the neurochemical mechanisms underlying behavioral sensitization remain incompletely understood. In the present study, we conducted the first metabolomics analysis to globally characterize neurochemical differences associated with behavioral sensitization. Methamphetamine-induced sensitization measures were generated by statistically modeling longitudinal activity data for eight inbred strains of mice. Subsequent to behavioral testing, nontargeted liquid and gas chromatography-mass spectrometry profiling was performed on 48 brain samples, yielding 301 metabolite levels per sample after quality control. Association testing between metabolite levels and three primary dimensions of behavioral sensitization (total distance, stereotypy and margin time) showed four robust, significant associations at a stringent metabolome-wide significance threshold (false discovery rate < 0.05). Results implicated homocarnosine, a dipeptide of GABA and histidine, in total distance sensitization, GABA metabolite 4-guanidinobutanoate and pantothenate in stereotypy sensitization, and myo-inositol in margin time sensitization. Secondary analyses indicated that these associations were independent of concurrent methamphetamine levels and, with the exception of the myo-inositol association, suggest a mechanism whereby strain-based genetic variation produces specific baseline neurochemical differences that substantially influence the magnitude of MA-induced sensitization. These findings demonstrate the utility of mouse metabolomics for identifying novel biomarkers, and developing more comprehensive neurochemical models, of psychostimulant sensitization. PMID:24034544
Risk and sensitivity analysis in relation to external events
International Nuclear Information System (INIS)
Alzbutas, R.; Urbonas, R.; Augutis, J.
2001-01-01
This paper presents risk and sensitivity analysis of external events impacts on the safe operation in general and in particular the Ignalina Nuclear Power Plant safety systems. Analysis is based on the deterministic and probabilistic assumptions and assessment of the external hazards. The real statistic data are used as well as initial external event simulation. The preliminary screening criteria are applied. The analysis of external event impact on the NPP safe operation, assessment of the event occurrence, sensitivity analysis, and recommendations for safety improvements are performed for investigated external hazards. Such events as aircraft crash, extreme rains and winds, forest fire and flying parts of the turbine are analysed. The models are developed and probabilities are calculated. As an example for sensitivity analysis the model of aircraft impact is presented. The sensitivity analysis takes into account the uncertainty features raised by external event and its model. Even in case when the external events analysis show rather limited danger, the sensitivity analysis can determine the highest influence causes. These possible variations in future can be significant for safety level and risk based decisions. Calculations show that external events cannot significantly influence the safety level of the Ignalina NPP operation, however the events occurrence and propagation can be sufficiently uncertain.(author)
High sensitivity analysis of atmospheric gas elements
International Nuclear Information System (INIS)
Miwa, Shiro; Nomachi, Ichiro; Kitajima, Hideo
2006-01-01
We have investigated the detection limit of H, C and O in Si, GaAs and InP using a Cameca IMS-4f instrument equipped with a modified vacuum system to improve the detection limit with a lower sputtering rate We found that the detection limits for H, O and C are improved by employing a primary ion bombardment before the analysis. Background levels of 1 x 10 17 atoms/cm 3 for H, of 3 x 10 16 atoms/cm 3 for C and of 2 x 10 16 atoms/cm 3 for O could be achieved in silicon with a sputtering rate of 2 nm/s after a primary ion bombardment for 160 h. We also found that the use of a 20 K He cryo-panel near the sample holder was effective for obtaining better detection limits in a shorter time, although the final detection limits using the panel are identical to those achieved without it
High sensitivity analysis of atmospheric gas elements
Energy Technology Data Exchange (ETDEWEB)
Miwa, Shiro [Materials Analysis Lab., Sony Corporation, 4-16-1 Okata, Atsugi 243-0021 (Japan)]. E-mail: Shiro.Miwa@jp.sony.com; Nomachi, Ichiro [Materials Analysis Lab., Sony Corporation, 4-16-1 Okata, Atsugi 243-0021 (Japan); Kitajima, Hideo [Nanotechnos Corp., 5-4-30 Nishihashimoto, Sagamihara 229-1131 (Japan)
2006-07-30
We have investigated the detection limit of H, C and O in Si, GaAs and InP using a Cameca IMS-4f instrument equipped with a modified vacuum system to improve the detection limit with a lower sputtering rate We found that the detection limits for H, O and C are improved by employing a primary ion bombardment before the analysis. Background levels of 1 x 10{sup 17} atoms/cm{sup 3} for H, of 3 x 10{sup 16} atoms/cm{sup 3} for C and of 2 x 10{sup 16} atoms/cm{sup 3} for O could be achieved in silicon with a sputtering rate of 2 nm/s after a primary ion bombardment for 160 h. We also found that the use of a 20 K He cryo-panel near the sample holder was effective for obtaining better detection limits in a shorter time, although the final detection limits using the panel are identical to those achieved without it.
Sensitivity Analysis of BLISK Airfoil Wear †
Directory of Open Access Journals (Sweden)
Andreas Kellersmann
2018-05-01
Full Text Available The decreasing performance of jet engines during operation is a major concern for airlines and maintenance companies. Among other effects, the erosion of high-pressure compressor (HPC blades is a critical one and leads to a changed aerodynamic behavior, and therefore to a change in performance. The maintenance of BLISKs (blade-integrated-disks is especially challenging because the blade arrangement cannot be changed and individual blades cannot be replaced. Thus, coupled deteriorated blades have a complex aerodynamic behavior which can have a stronger influence on compressor performance than a conventional HPC. To ensure effective maintenance for BLISKs, the impact of coupled misshaped blades are the key factor. The present study addresses these effects on the aerodynamic performance of a first-stage BLISK of a high-pressure compressor. Therefore, a design of experiments (DoE is done to identify the geometric properties which lead to a reduction in performance. It is shown that the effect of coupled variances is dependent on the operating point. Based on the DoE analysis, the thickness-related parameters, the stagger angle, and the max. profile camber as coupled parameters are identified as the most important parameters for all operating points.
Hasegawa, Raiden; Small, Dylan
2017-12-01
In matched observational studies where treatment assignment is not randomized, sensitivity analysis helps investigators determine how sensitive their estimated treatment effect is to some unmeasured confounder. The standard approach calibrates the sensitivity analysis according to the worst case bias in a pair. This approach will result in a conservative sensitivity analysis if the worst case bias does not hold in every pair. In this paper, we show that for binary data, the standard approach can be calibrated in terms of the average bias in a pair rather than worst case bias. When the worst case bias and average bias differ, the average bias interpretation results in a less conservative sensitivity analysis and more power. In many studies, the average case calibration may also carry a more natural interpretation than the worst case calibration and may also allow researchers to incorporate additional data to establish an empirical basis with which to calibrate a sensitivity analysis. We illustrate this with a study of the effects of cellphone use on the incidence of automobile accidents. Finally, we extend the average case calibration to the sensitivity analysis of confidence intervals for attributable effects. © 2017, The International Biometric Society.
Application of Stochastic Sensitivity Analysis to Integrated Force Method
Directory of Open Access Journals (Sweden)
X. F. Wei
2012-01-01
Full Text Available As a new formulation in structural analysis, Integrated Force Method has been successfully applied to many structures for civil, mechanical, and aerospace engineering due to the accurate estimate of forces in computation. Right now, it is being further extended to the probabilistic domain. For the assessment of uncertainty effect in system optimization and identification, the probabilistic sensitivity analysis of IFM was further investigated in this study. A set of stochastic sensitivity analysis formulation of Integrated Force Method was developed using the perturbation method. Numerical examples are presented to illustrate its application. Its efficiency and accuracy were also substantiated with direct Monte Carlo simulations and the reliability-based sensitivity method. The numerical algorithm was shown to be readily adaptable to the existing program since the models of stochastic finite element and stochastic design sensitivity are almost identical.
The EVEREST project: sensitivity analysis of geological disposal systems
International Nuclear Information System (INIS)
Marivoet, Jan; Wemaere, Isabelle; Escalier des Orres, Pierre; Baudoin, Patrick; Certes, Catherine; Levassor, Andre; Prij, Jan; Martens, Karl-Heinz; Roehlig, Klaus
1997-01-01
The main objective of the EVEREST project is the evaluation of the sensitivity of the radiological consequences associated with the geological disposal of radioactive waste to the different elements in the performance assessment. Three types of geological host formations are considered: clay, granite and salt. The sensitivity studies that have been carried out can be partitioned into three categories according to the type of uncertainty taken into account: uncertainty in the model parameters, uncertainty in the conceptual models and uncertainty in the considered scenarios. Deterministic as well as stochastic calculational approaches have been applied for the sensitivity analyses. For the analysis of the sensitivity to parameter values, the reference technique, which has been applied in many evaluations, is stochastic and consists of a Monte Carlo simulation followed by a linear regression. For the analysis of conceptual model uncertainty, deterministic and stochastic approaches have been used. For the analysis of uncertainty in the considered scenarios, mainly deterministic approaches have been applied
Multiple predictor smoothing methods for sensitivity analysis: Description of techniques
International Nuclear Information System (INIS)
Storlie, Curtis B.; Helton, Jon C.
2008-01-01
The use of multiple predictor smoothing methods in sampling-based sensitivity analyses of complex models is investigated. Specifically, sensitivity analysis procedures based on smoothing methods employing the stepwise application of the following nonparametric regression techniques are described: (i) locally weighted regression (LOESS), (ii) additive models, (iii) projection pursuit regression, and (iv) recursive partitioning regression. Then, in the second and concluding part of this presentation, the indicated procedures are illustrated with both simple test problems and results from a performance assessment for a radioactive waste disposal facility (i.e., the Waste Isolation Pilot Plant). As shown by the example illustrations, the use of smoothing procedures based on nonparametric regression techniques can yield more informative sensitivity analysis results than can be obtained with more traditional sensitivity analysis procedures based on linear regression, rank regression or quadratic regression when nonlinear relationships between model inputs and model predictions are present
Multiple predictor smoothing methods for sensitivity analysis: Example results
International Nuclear Information System (INIS)
Storlie, Curtis B.; Helton, Jon C.
2008-01-01
The use of multiple predictor smoothing methods in sampling-based sensitivity analyses of complex models is investigated. Specifically, sensitivity analysis procedures based on smoothing methods employing the stepwise application of the following nonparametric regression techniques are described in the first part of this presentation: (i) locally weighted regression (LOESS), (ii) additive models, (iii) projection pursuit regression, and (iv) recursive partitioning regression. In this, the second and concluding part of the presentation, the indicated procedures are illustrated with both simple test problems and results from a performance assessment for a radioactive waste disposal facility (i.e., the Waste Isolation Pilot Plant). As shown by the example illustrations, the use of smoothing procedures based on nonparametric regression techniques can yield more informative sensitivity analysis results than can be obtained with more traditional sensitivity analysis procedures based on linear regression, rank regression or quadratic regression when nonlinear relationships between model inputs and model predictions are present
Carbon dioxide capture processes: Simulation, design and sensitivity analysis
DEFF Research Database (Denmark)
Zaman, Muhammad; Lee, Jay Hyung; Gani, Rafiqul
2012-01-01
equilibrium and associated property models are used. Simulations are performed to investigate the sensitivity of the process variables to change in the design variables including process inputs and disturbances in the property model parameters. Results of the sensitivity analysis on the steady state...... performance of the process to the L/G ratio to the absorber, CO2 lean solvent loadings, and striper pressure are presented in this paper. Based on the sensitivity analysis process optimization problems have been defined and solved and, a preliminary control structure selection has been made.......Carbon dioxide is the main greenhouse gas and its major source is combustion of fossil fuels for power generation. The objective of this study is to carry out the steady-state sensitivity analysis for chemical absorption of carbon dioxide capture from flue gas using monoethanolamine solvent. First...
Global sensitivity analysis in stochastic simulators of uncertain reaction networks.
Navarro Jimenez, M; Le Maître, O P; Knio, O M
2016-12-28
Stochastic models of chemical systems are often subjected to uncertainties in kinetic parameters in addition to the inherent random nature of their dynamics. Uncertainty quantification in such systems is generally achieved by means of sensitivity analyses in which one characterizes the variability with the uncertain kinetic parameters of the first statistical moments of model predictions. In this work, we propose an original global sensitivity analysis method where the parametric and inherent variability sources are both treated through Sobol's decomposition of the variance into contributions from arbitrary subset of uncertain parameters and stochastic reaction channels. The conceptual development only assumes that the inherent and parametric sources are independent, and considers the Poisson processes in the random-time-change representation of the state dynamics as the fundamental objects governing the inherent stochasticity. A sampling algorithm is proposed to perform the global sensitivity analysis, and to estimate the partial variances and sensitivity indices characterizing the importance of the various sources of variability and their interactions. The birth-death and Schlögl models are used to illustrate both the implementation of the algorithm and the richness of the proposed analysis method. The output of the proposed sensitivity analysis is also contrasted with a local derivative-based sensitivity analysis method classically used for this type of systems.
Sensitivity Analysis for Urban Drainage Modeling Using Mutual Information
Directory of Open Access Journals (Sweden)
Chuanqi Li
2014-11-01
Full Text Available The intention of this paper is to evaluate the sensitivity of the Storm Water Management Model (SWMM output to its input parameters. A global parameter sensitivity analysis is conducted in order to determine which parameters mostly affect the model simulation results. Two different methods of sensitivity analysis are applied in this study. The first one is the partial rank correlation coefficient (PRCC which measures nonlinear but monotonic relationships between model inputs and outputs. The second one is based on the mutual information which provides a general measure of the strength of the non-monotonic association between two variables. Both methods are based on the Latin Hypercube Sampling (LHS of the parameter space, and thus the same datasets can be used to obtain both measures of sensitivity. The utility of the PRCC and the mutual information analysis methods are illustrated by analyzing a complex SWMM model. The sensitivity analysis revealed that only a few key input variables are contributing significantly to the model outputs; PRCCs and mutual information are calculated and used to determine and rank the importance of these key parameters. This study shows that the partial rank correlation coefficient and mutual information analysis can be considered effective methods for assessing the sensitivity of the SWMM model to the uncertainty in its input parameters.
Global sensitivity analysis in stochastic simulators of uncertain reaction networks
Navarro, María
2016-12-26
Stochastic models of chemical systems are often subjected to uncertainties in kinetic parameters in addition to the inherent random nature of their dynamics. Uncertainty quantification in such systems is generally achieved by means of sensitivity analyses in which one characterizes the variability with the uncertain kinetic parameters of the first statistical moments of model predictions. In this work, we propose an original global sensitivity analysis method where the parametric and inherent variability sources are both treated through Sobol’s decomposition of the variance into contributions from arbitrary subset of uncertain parameters and stochastic reaction channels. The conceptual development only assumes that the inherent and parametric sources are independent, and considers the Poisson processes in the random-time-change representation of the state dynamics as the fundamental objects governing the inherent stochasticity. A sampling algorithm is proposed to perform the global sensitivity analysis, and to estimate the partial variances and sensitivity indices characterizing the importance of the various sources of variability and their interactions. The birth-death and Schlögl models are used to illustrate both the implementation of the algorithm and the richness of the proposed analysis method. The output of the proposed sensitivity analysis is also contrasted with a local derivative-based sensitivity analysis method classically used for this type of systems.
Concentrated Hitting Times of Randomized Search Heuristics with Variable Drift
DEFF Research Database (Denmark)
Lehre, Per Kristian; Witt, Carsten
2014-01-01
Drift analysis is one of the state-of-the-art techniques for the runtime analysis of randomized search heuristics (RSHs) such as evolutionary algorithms (EAs), simulated annealing etc. The vast majority of existing drift theorems yield bounds on the expected value of the hitting time for a target...
Netlist Oriented Sensitivity Evaluation (NOSE)
2017-03-01
representing the official policies or endorsements, either expressed or implied, of Air Force Research Laboratory (AFRL) and the Defense Advanced Research... Heuristics for generating an alternative netlist implementation for the same logic function to achieve a better robustness measure 2...sensitivity study: 1. Tools to calculate sensitivity of netlist nodes (signals) and heuristics for generating alternative netlist implementations
Allergen Sensitization Pattern by Sex: A Cluster Analysis in Korea.
Ohn, Jungyoon; Paik, Seung Hwan; Doh, Eun Jin; Park, Hyun-Sun; Yoon, Hyun-Sun; Cho, Soyun
2017-12-01
Allergens tend to sensitize simultaneously. Etiology of this phenomenon has been suggested to be allergen cross-reactivity or concurrent exposure. However, little is known about specific allergen sensitization patterns. To investigate the allergen sensitization characteristics according to gender. Multiple allergen simultaneous test (MAST) is widely used as a screening tool for detecting allergen sensitization in dermatologic clinics. We retrospectively reviewed the medical records of patients with MAST results between 2008 and 2014 in our Department of Dermatology. A cluster analysis was performed to elucidate the allergen-specific immunoglobulin (Ig)E cluster pattern. The results of MAST (39 allergen-specific IgEs) from 4,360 cases were analyzed. By cluster analysis, 39items were grouped into 8 clusters. Each cluster had characteristic features. When compared with female, the male group tended to be sensitized more frequently to all tested allergens, except for fungus allergens cluster. The cluster and comparative analysis results demonstrate that the allergen sensitization is clustered, manifesting allergen similarity or co-exposure. Only the fungus cluster allergens tend to sensitize female group more frequently than male group.
A general first-order global sensitivity analysis method
International Nuclear Information System (INIS)
Xu Chonggang; Gertner, George Zdzislaw
2008-01-01
Fourier amplitude sensitivity test (FAST) is one of the most popular global sensitivity analysis techniques. The main mechanism of FAST is to assign each parameter with a characteristic frequency through a search function. Then, for a specific parameter, the variance contribution can be singled out of the model output by the characteristic frequency. Although FAST has been widely applied, there are two limitations: (1) the aliasing effect among parameters by using integer characteristic frequencies and (2) the suitability for only models with independent parameters. In this paper, we synthesize the improvement to overcome the aliasing effect limitation [Tarantola S, Gatelli D, Mara TA. Random balance designs for the estimation of first order global sensitivity indices. Reliab Eng Syst Safety 2006; 91(6):717-27] and the improvement to overcome the independence limitation [Xu C, Gertner G. Extending a global sensitivity analysis technique to models with correlated parameters. Comput Stat Data Anal 2007, accepted for publication]. In this way, FAST can be a general first-order global sensitivity analysis method for linear/nonlinear models with as many correlated/uncorrelated parameters as the user specifies. We apply the general FAST to four test cases with correlated parameters. The results show that the sensitivity indices derived by the general FAST are in good agreement with the sensitivity indices derived by the correlation ratio method, which is a non-parametric method for models with correlated parameters
Familiarity and recollection in heuristic decision making.
Schwikert, Shane R; Curran, Tim
2014-12-01
Heuristics involve the ability to utilize memory to make quick judgments by exploiting fundamental cognitive abilities. In the current study we investigated the memory processes that contribute to the recognition heuristic and the fluency heuristic, which are both presumed to capitalize on the byproducts of memory to make quick decisions. In Experiment 1, we used a city-size comparison task while recording event-related potentials (ERPs) to investigate the potential contributions of familiarity and recollection to the 2 heuristics. ERPs were markedly different for recognition heuristic-based decisions and fluency heuristic-based decisions, suggesting a role for familiarity in the recognition heuristic and recollection in the fluency heuristic. In Experiment 2, we coupled the same city-size comparison task with measures of subjective preexperimental memory for each stimulus in the task. Although previous literature suggests the fluency heuristic relies on recognition speed alone, our results suggest differential contributions of recognition speed and recollected knowledge to these decisions, whereas the recognition heuristic relies on familiarity. Based on these results, we created a new theoretical framework that explains decisions attributed to both heuristics based on the underlying memory associated with the choice options. PsycINFO Database Record (c) 2014 APA, all rights reserved.
Sensitivity Analysis of Criticality for Different Nuclear Fuel Shapes
International Nuclear Information System (INIS)
Kang, Hyun Sik; Jang, Misuk; Kim, Seoung Rae
2016-01-01
Rod-type nuclear fuel was mainly developed in the past, but recent study has been extended to plate-type nuclear fuel. Therefore, this paper reviews the sensitivity of criticality according to different shapes of nuclear fuel types. Criticality analysis was performed using MCNP5. MCNP5 is well-known Monte Carlo codes for criticality analysis and a general-purpose Monte Carlo N-Particle code that can be used for neutron, photon, electron or coupled neutron / photon / electron transport, including the capability to calculate eigenvalues for critical systems. We performed the sensitivity analysis of criticality for different fuel shapes. In sensitivity analysis for simple fuel shapes, the criticality is proportional to the surface area. But for fuel Assembly types, it is not proportional to the surface area. In sensitivity analysis for intervals between plates, the criticality is greater as the interval increases, but if the interval is greater than 8mm, it showed an opposite trend that the criticality decrease by a larger interval. As a result, it has failed to obtain the logical content to be described in common for all cases. The sensitivity analysis of Criticality would be always required whenever subject to be analyzed is changed
Sensitivity Analysis of Criticality for Different Nuclear Fuel Shapes
Energy Technology Data Exchange (ETDEWEB)
Kang, Hyun Sik; Jang, Misuk; Kim, Seoung Rae [NESS, Daejeon (Korea, Republic of)
2016-10-15
Rod-type nuclear fuel was mainly developed in the past, but recent study has been extended to plate-type nuclear fuel. Therefore, this paper reviews the sensitivity of criticality according to different shapes of nuclear fuel types. Criticality analysis was performed using MCNP5. MCNP5 is well-known Monte Carlo codes for criticality analysis and a general-purpose Monte Carlo N-Particle code that can be used for neutron, photon, electron or coupled neutron / photon / electron transport, including the capability to calculate eigenvalues for critical systems. We performed the sensitivity analysis of criticality for different fuel shapes. In sensitivity analysis for simple fuel shapes, the criticality is proportional to the surface area. But for fuel Assembly types, it is not proportional to the surface area. In sensitivity analysis for intervals between plates, the criticality is greater as the interval increases, but if the interval is greater than 8mm, it showed an opposite trend that the criticality decrease by a larger interval. As a result, it has failed to obtain the logical content to be described in common for all cases. The sensitivity analysis of Criticality would be always required whenever subject to be analyzed is changed.
Global sensitivity analysis of computer models with functional inputs
International Nuclear Information System (INIS)
Iooss, Bertrand; Ribatet, Mathieu
2009-01-01
Global sensitivity analysis is used to quantify the influence of uncertain model inputs on the response variability of a numerical model. The common quantitative methods are appropriate with computer codes having scalar model inputs. This paper aims at illustrating different variance-based sensitivity analysis techniques, based on the so-called Sobol's indices, when some model inputs are functional, such as stochastic processes or random spatial fields. In this work, we focus on large cpu time computer codes which need a preliminary metamodeling step before performing the sensitivity analysis. We propose the use of the joint modeling approach, i.e., modeling simultaneously the mean and the dispersion of the code outputs using two interlinked generalized linear models (GLMs) or generalized additive models (GAMs). The 'mean model' allows to estimate the sensitivity indices of each scalar model inputs, while the 'dispersion model' allows to derive the total sensitivity index of the functional model inputs. The proposed approach is compared to some classical sensitivity analysis methodologies on an analytical function. Lastly, the new methodology is applied to an industrial computer code that simulates the nuclear fuel irradiation.
A tool model for predicting atmospheric kinetics with sensitivity analysis
Institute of Scientific and Technical Information of China (English)
无
2001-01-01
A package( a tool model) for program of predicting atmospheric chemical kinetics with sensitivity analysis is presented. The new direct method of calculating the first order sensitivity coefficients using sparse matrix technology to chemical kinetics is included in the tool model, it is only necessary to triangularize the matrix related to the Jacobian matrix of the model equation. The Gear type procedure is used to integrate amodel equation and its coupled auxiliary sensitivity coefficient equations. The FORTRAN subroutines of the model equation, the sensitivity coefficient equations, and their Jacobian analytical expressions are generated automatically from a chemical mechanism. The kinetic representation for the model equation and its sensitivity coefficient equations, and their Jacobian matrix is presented. Various FORTRAN subroutines in packages, such as SLODE, modified MA28, Gear package, with which the program runs in conjunction are recommended.The photo-oxidation of dimethyl disulfide is used for illustration.
Sensitivity analysis of the nuclear data for MYRRHA reactor modelling
International Nuclear Information System (INIS)
Stankovskiy, Alexey; Van den Eynde, Gert; Cabellos, Oscar; Diez, Carlos J.; Schillebeeckx, Peter; Heyse, Jan
2014-01-01
A global sensitivity analysis of effective neutron multiplication factor k eff to the change of nuclear data library revealed that JEFF-3.2T2 neutron-induced evaluated data library produces closer results to ENDF/B-VII.1 than does JEFF-3.1.2. The analysis of contributions of individual evaluations into k eff sensitivity allowed establishing the priority list of nuclides for which uncertainties on nuclear data must be improved. Detailed sensitivity analysis has been performed for two nuclides from this list, 56 Fe and 238 Pu. The analysis was based on a detailed survey of the evaluations and experimental data. To track the origin of the differences in the evaluations and their impact on k eff , the reaction cross-sections and multiplicities in one evaluation have been substituted by the corresponding data from other evaluations. (authors)
Deterministic Local Sensitivity Analysis of Augmented Systems - I: Theory
International Nuclear Information System (INIS)
Cacuci, Dan G.; Ionescu-Bujor, Mihaela
2005-01-01
This work provides the theoretical foundation for the modular implementation of the Adjoint Sensitivity Analysis Procedure (ASAP) for large-scale simulation systems. The implementation of the ASAP commences with a selected code module and then proceeds by augmenting the size of the adjoint sensitivity system, module by module, until the entire system is completed. Notably, the adjoint sensitivity system for the augmented system can often be solved by using the same numerical methods used for solving the original, nonaugmented adjoint system, particularly when the matrix representation of the adjoint operator for the augmented system can be inverted by partitioning
The identification of model effective dimensions using global sensitivity analysis
International Nuclear Information System (INIS)
Kucherenko, Sergei; Feil, Balazs; Shah, Nilay; Mauntz, Wolfgang
2011-01-01
It is shown that the effective dimensions can be estimated at reasonable computational costs using variance based global sensitivity analysis. Namely, the effective dimension in the truncation sense can be found by using the Sobol' sensitivity indices for subsets of variables. The effective dimension in the superposition sense can be estimated by using the first order effects and the total Sobol' sensitivity indices. The classification of some important classes of integrable functions based on their effective dimension is proposed. It is shown that it can be used for the prediction of the QMC efficiency. Results of numerical tests verify the prediction of the developed techniques.
The identification of model effective dimensions using global sensitivity analysis
Energy Technology Data Exchange (ETDEWEB)
Kucherenko, Sergei, E-mail: s.kucherenko@ic.ac.u [CPSE, Imperial College London, South Kensington Campus, London SW7 2AZ (United Kingdom); Feil, Balazs [Department of Process Engineering, University of Pannonia, Veszprem (Hungary); Shah, Nilay [CPSE, Imperial College London, South Kensington Campus, London SW7 2AZ (United Kingdom); Mauntz, Wolfgang [Lehrstuhl fuer Anlagensteuerungstechnik, Fachbereich Chemietechnik, Universitaet Dortmund (Germany)
2011-04-15
It is shown that the effective dimensions can be estimated at reasonable computational costs using variance based global sensitivity analysis. Namely, the effective dimension in the truncation sense can be found by using the Sobol' sensitivity indices for subsets of variables. The effective dimension in the superposition sense can be estimated by using the first order effects and the total Sobol' sensitivity indices. The classification of some important classes of integrable functions based on their effective dimension is proposed. It is shown that it can be used for the prediction of the QMC efficiency. Results of numerical tests verify the prediction of the developed techniques.
Application of Sensitivity Analysis in Design of Sustainable Buildings
DEFF Research Database (Denmark)
Heiselberg, Per; Brohus, Henrik; Rasmussen, Henrik
2009-01-01
satisfies the design objectives and criteria. In the design of sustainable buildings, it is beneficial to identify the most important design parameters in order to more efficiently develop alternative design solutions or reach optimized design solutions. Sensitivity analyses make it possible to identify...... possible to influence the most important design parameters. A methodology of sensitivity analysis is presented and an application example is given for design of an office building in Denmark....
Sensitivity Analysis of the Integrated Medical Model for ISS Programs
Goodenow, D. A.; Myers, J. G.; Arellano, J.; Boley, L.; Garcia, Y.; Saile, L.; Walton, M.; Kerstman, E.; Reyes, D.; Young, M.
2016-01-01
Sensitivity analysis estimates the relative contribution of the uncertainty in input values to the uncertainty of model outputs. Partial Rank Correlation Coefficient (PRCC) and Standardized Rank Regression Coefficient (SRRC) are methods of conducting sensitivity analysis on nonlinear simulation models like the Integrated Medical Model (IMM). The PRCC method estimates the sensitivity using partial correlation of the ranks of the generated input values to each generated output value. The partial part is so named because adjustments are made for the linear effects of all the other input values in the calculation of correlation between a particular input and each output. In SRRC, standardized regression-based coefficients measure the sensitivity of each input, adjusted for all the other inputs, on each output. Because the relative ranking of each of the inputs and outputs is used, as opposed to the values themselves, both methods accommodate the nonlinear relationship of the underlying model. As part of the IMM v4.0 validation study, simulations are available that predict 33 person-missions on ISS and 111 person-missions on STS. These simulated data predictions feed the sensitivity analysis procedures. The inputs to the sensitivity procedures include the number occurrences of each of the one hundred IMM medical conditions generated over the simulations and the associated IMM outputs: total quality time lost (QTL), number of evacuations (EVAC), and number of loss of crew lives (LOCL). The IMM team will report the results of using PRCC and SRRC on IMM v4.0 predictions of the ISS and STS missions created as part of the external validation study. Tornado plots will assist in the visualization of the condition-related input sensitivities to each of the main outcomes. The outcomes of this sensitivity analysis will drive review focus by identifying conditions where changes in uncertainty could drive changes in overall model output uncertainty. These efforts are an integral
Sensitivity analysis of network DEA illustrated in branch banking
N. Avkiran
2010-01-01
Users of data envelopment analysis (DEA) often presume efficiency estimates to be robust. While traditional DEA has been exposed to various sensitivity studies, network DEA (NDEA) has so far escaped similar scrutiny. Thus, there is a need to investigate the sensitivity of NDEA, further compounded by the recent attention it has been receiving in literature. NDEA captures the underlying performance information found in a firm?s interacting divisions or sub-processes that would otherwise remain ...
Special relativity a heuristic approach
Hassani, Sadri
2017-01-01
Special Relativity: A Heuristic Approach provides a qualitative exposition of relativity theory on the basis of the constancy of the speed of light. Using Einstein's signal velocity as the defining idea for the notion of simultaneity and the fact that the speed of light is independent of the motion of its source, chapters delve into a qualitative exposition of the relativity of time and length, discuss the time dilation formula using the standard light clock, explore the Minkowski four-dimensional space-time distance based on how the time dilation formula is derived, and define the components of the two-dimensional space-time velocity, amongst other topics. Provides a heuristic derivation of the Minkowski distance formula Uses relativistic photography to see Lorentz transformation and vector algebra manipulation in action Includes worked examples to elucidate and complement the topic being discussed Written in a very accessible style
Sensitivity analysis of periodic errors in heterodyne interferometry
International Nuclear Information System (INIS)
Ganguly, Vasishta; Kim, Nam Ho; Kim, Hyo Soo; Schmitz, Tony
2011-01-01
Periodic errors in heterodyne displacement measuring interferometry occur due to frequency mixing in the interferometer. These nonlinearities are typically characterized as first- and second-order periodic errors which cause a cyclical (non-cumulative) variation in the reported displacement about the true value. This study implements an existing analytical periodic error model in order to identify sensitivities of the first- and second-order periodic errors to the input parameters, including rotational misalignments of the polarizing beam splitter and mixing polarizer, non-orthogonality of the two laser frequencies, ellipticity in the polarizations of the two laser beams, and different transmission coefficients in the polarizing beam splitter. A local sensitivity analysis is first conducted to examine the sensitivities of the periodic errors with respect to each input parameter about the nominal input values. Next, a variance-based approach is used to study the global sensitivities of the periodic errors by calculating the Sobol' sensitivity indices using Monte Carlo simulation. The effect of variation in the input uncertainty on the computed sensitivity indices is examined. It is seen that the first-order periodic error is highly sensitive to non-orthogonality of the two linearly polarized laser frequencies, while the second-order error is most sensitive to the rotational misalignment between the laser beams and the polarizing beam splitter. A particle swarm optimization technique is finally used to predict the possible setup imperfections based on experimentally generated values for periodic errors
Sensitivity analysis of periodic errors in heterodyne interferometry
Ganguly, Vasishta; Kim, Nam Ho; Kim, Hyo Soo; Schmitz, Tony
2011-03-01
Periodic errors in heterodyne displacement measuring interferometry occur due to frequency mixing in the interferometer. These nonlinearities are typically characterized as first- and second-order periodic errors which cause a cyclical (non-cumulative) variation in the reported displacement about the true value. This study implements an existing analytical periodic error model in order to identify sensitivities of the first- and second-order periodic errors to the input parameters, including rotational misalignments of the polarizing beam splitter and mixing polarizer, non-orthogonality of the two laser frequencies, ellipticity in the polarizations of the two laser beams, and different transmission coefficients in the polarizing beam splitter. A local sensitivity analysis is first conducted to examine the sensitivities of the periodic errors with respect to each input parameter about the nominal input values. Next, a variance-based approach is used to study the global sensitivities of the periodic errors by calculating the Sobol' sensitivity indices using Monte Carlo simulation. The effect of variation in the input uncertainty on the computed sensitivity indices is examined. It is seen that the first-order periodic error is highly sensitive to non-orthogonality of the two linearly polarized laser frequencies, while the second-order error is most sensitive to the rotational misalignment between the laser beams and the polarizing beam splitter. A particle swarm optimization technique is finally used to predict the possible setup imperfections based on experimentally generated values for periodic errors.
Generalized perturbation theory (GPT) methods. A heuristic approach
International Nuclear Information System (INIS)
Gandini, A.
1987-01-01
Wigner first proposed a perturbation theory as early as 1945 to study fundamental quantities such as the reactivity worths of different materials. The first formulation, CPT, for conventional perturbation theory is based on universal quantum mechanics concepts. Since that early conception, significant contributions have been made to CPT, in particular, Soodak, who rendered a heuristic interpretation of the adjoint function, (referred to as the GPT method for generalized perturbation theory). The author illustrates the GPT methodology in a variety of linear and nonlinear domains encountered in nuclear reactor analysis. The author begins with the familiar linear neutron field and then generalizes the methodology to other linear and nonlinear fields, using heuristic arguments. The author believes that the inherent simplicity and elegance of the heuristic derivation, although intended here for reactor physics problems might be usefully adopted in collateral fields and includes such examples
Heuristic versus statistical physics approach to optimization problems
International Nuclear Information System (INIS)
Jedrzejek, C.; Cieplinski, L.
1995-01-01
Optimization is a crucial ingredient of many calculation schemes in science and engineering. In this paper we assess several classes of methods: heuristic algorithms, methods directly relying on statistical physics such as the mean-field method and simulated annealing; and Hopfield-type neural networks and genetic algorithms partly related to statistical physics. We perform the analysis for three types of problems: (1) the Travelling Salesman Problem, (2) vector quantization, and (3) traffic control problem in multistage interconnection network. In general, heuristic algorithms perform better (except for genetic algorithms) and much faster but have to be specific for every problem. The key to improving the performance could be to include heuristic features into general purpose statistical physics methods. (author)
2012-01-01
OVERVIEW OF PRESENTATION : Evaluation Parameters : EPAs Sensitivity Analysis : Comparison to Baseline Case : MOVES Sensitivity Run Specification : MOVES Sensitivity Input Parameters : Results : Uses of Study
Sensitivity analysis of the reactor safety study. Final report
International Nuclear Information System (INIS)
Parkinson, W.J.; Rasmussen, N.C.; Hinkle, W.D.
1979-01-01
The Reactor Safety Study (RSS) or Wash 1400 developed a methodology estimating the public risk from light water nuclear reactors. In order to give further insights into this study, a sensitivity analysis has been performed to determine the significant contributors to risk for both the PWR and BWR. The sensitivity to variation of the point values of the failure probabilities reported in the RSS was determined for the safety systems identified therein, as well as for many of the generic classes from which individual failures contributed to system failures. Increasing as well as decreasing point values were considered. An analysis of the sensitivity to increasing uncertainty in system failure probabilities was also performed. The sensitivity parameters chosen were release category probabilities, core melt probability, and the risk parameters of early fatalities, latent cancers and total property damage. The latter three are adequate for describing all public risks identified in the RSS. The results indicate reductions of public risk by less than a factor of two for factor reductions in system or generic failure probabilities as high as one hundred. There also appears to be more benefit in monitoring the most sensitive systems to verify adherence to RSS failure rates than to backfitting present reactors. The sensitivity analysis results do indicate, however, possible benefits in reducing human error rates
Sensitivity analysis technique for application to deterministic models
International Nuclear Information System (INIS)
Ishigami, T.; Cazzoli, E.; Khatib-Rahbar, M.; Unwin, S.D.
1987-01-01
The characterization of sever accident source terms for light water reactors should include consideration of uncertainties. An important element of any uncertainty analysis is an evaluation of the sensitivity of the output probability distributions reflecting source term uncertainties to assumptions regarding the input probability distributions. Historically, response surface methods (RSMs) were developed to replace physical models using, for example, regression techniques, with simplified models for example, regression techniques, with simplified models for extensive calculations. The purpose of this paper is to present a new method for sensitivity analysis that does not utilize RSM, but instead relies directly on the results obtained from the original computer code calculations. The merits of this approach are demonstrated by application of the proposed method to the suppression pool aerosol removal code (SPARC), and the results are compared with those obtained by sensitivity analysis with (a) the code itself, (b) a regression model, and (c) Iman's method
Probabilistic Sensitivities for Fatigue Analysis of Turbine Engine Disks
Directory of Open Access Journals (Sweden)
Harry R. Millwater
2006-01-01
Full Text Available A methodology is developed and applied that determines the sensitivities of the probability-of-fracture of a gas turbine disk fatigue analysis with respect to the parameters of the probability distributions describing the random variables. The disk material is subject to initial anomalies, in either low- or high-frequency quantities, such that commonly used materials (titanium, nickel, powder nickel and common damage mechanisms (inherent defects or surface damage can be considered. The derivation is developed for Monte Carlo sampling such that the existing failure samples are used and the sensitivities are obtained with minimal additional computational time. Variance estimates and confidence bounds of the sensitivity estimates are developed. The methodology is demonstrated and verified using a multizone probabilistic fatigue analysis of a gas turbine compressor disk analysis considering stress scatter, crack growth propagation scatter, and initial crack size as random variables.
Application of sensitivity analysis for optimized piping support design
International Nuclear Information System (INIS)
Tai, K.; Nakatogawa, T.; Hisada, T.; Noguchi, H.; Ichihashi, I.; Ogo, H.
1993-01-01
The objective of this study was to see if recent developments in non-linear sensitivity analysis could be applied to the design of nuclear piping systems which use non-linear supports and to develop a practical method of designing such piping systems. In the study presented in this paper, the seismic response of a typical piping system was analyzed using a dynamic non-linear FEM and a sensitivity analysis was carried out. Then optimization for the design of the piping system supports was investigated, selecting the support location and yield load of the non-linear supports (bi-linear model) as main design parameters. It was concluded that the optimized design was a matter of combining overall system reliability with the achievement of an efficient damping effect from the non-linear supports. The analysis also demonstrated sensitivity factors are useful in the planning stage of support design. (author)
Sensitivity and uncertainty analysis of the PATHWAY radionuclide transport model
International Nuclear Information System (INIS)
Otis, M.D.
1983-01-01
Procedures were developed for the uncertainty and sensitivity analysis of a dynamic model of radionuclide transport through human food chains. Uncertainty in model predictions was estimated by propagation of parameter uncertainties using a Monte Carlo simulation technique. Sensitivity of model predictions to individual parameters was investigated using the partial correlation coefficient of each parameter with model output. Random values produced for the uncertainty analysis were used in the correlation analysis for sensitivity. These procedures were applied to the PATHWAY model which predicts concentrations of radionuclides in foods grown in Nevada and Utah and exposed to fallout during the period of atmospheric nuclear weapons testing in Nevada. Concentrations and time-integrated concentrations of iodine-131, cesium-136, and cesium-137 in milk and other foods were investigated. 9 figs., 13 tabs
Discrete non-parametric kernel estimation for global sensitivity analysis
International Nuclear Information System (INIS)
Senga Kiessé, Tristan; Ventura, Anne
2016-01-01
This work investigates the discrete kernel approach for evaluating the contribution of the variance of discrete input variables to the variance of model output, via analysis of variance (ANOVA) decomposition. Until recently only the continuous kernel approach has been applied as a metamodeling approach within sensitivity analysis framework, for both discrete and continuous input variables. Now the discrete kernel estimation is known to be suitable for smoothing discrete functions. We present a discrete non-parametric kernel estimator of ANOVA decomposition of a given model. An estimator of sensitivity indices is also presented with its asymtotic convergence rate. Some simulations on a test function analysis and a real case study from agricultural have shown that the discrete kernel approach outperforms the continuous kernel one for evaluating the contribution of moderate or most influential discrete parameters to the model output. - Highlights: • We study a discrete kernel estimation for sensitivity analysis of a model. • A discrete kernel estimator of ANOVA decomposition of the model is presented. • Sensitivity indices are calculated for discrete input parameters. • An estimator of sensitivity indices is also presented with its convergence rate. • An application is realized for improving the reliability of environmental models.
Sensitivity analysis for missing data in regulatory submissions.
Permutt, Thomas
2016-07-30
The National Research Council Panel on Handling Missing Data in Clinical Trials recommended that sensitivity analyses have to be part of the primary reporting of findings from clinical trials. Their specific recommendations, however, seem not to have been taken up rapidly by sponsors of regulatory submissions. The NRC report's detailed suggestions are along rather different lines than what has been called sensitivity analysis in the regulatory setting up to now. Furthermore, the role of sensitivity analysis in regulatory decision-making, although discussed briefly in the NRC report, remains unclear. This paper will examine previous ideas of sensitivity analysis with a view to explaining how the NRC panel's recommendations are different and possibly better suited to coping with present problems of missing data in the regulatory setting. It will also discuss, in more detail than the NRC report, the relevance of sensitivity analysis to decision-making, both for applicants and for regulators. Published 2015. This article is a U.S. Government work and is in the public domain in the USA. Published 2015. This article is a U.S. Government work and is in the public domain in the USA.
Sobol' sensitivity analysis for stressor impacts on honeybee ...
We employ Monte Carlo simulation and nonlinear sensitivity analysis techniques to describe the dynamics of a bee exposure model, VarroaPop. Daily simulations are performed of hive population trajectories, taking into account queen strength, foraging success, mite impacts, weather, colony resources, population structure, and other important variables. This allows us to test the effects of defined pesticide exposure scenarios versus controlled simulations that lack pesticide exposure. The daily resolution of the model also allows us to conditionally identify sensitivity metrics. We use the variancebased global decomposition sensitivity analysis method, Sobol’, to assess firstand secondorder parameter sensitivities within VarroaPop, allowing us to determine how variance in the output is attributed to each of the input variables across different exposure scenarios. Simulations with VarroaPop indicate queen strength, forager life span and pesticide toxicity parameters are consistent, critical inputs for colony dynamics. Further analysis also reveals that the relative importance of these parameters fluctuates throughout the simulation period according to the status of other inputs. Our preliminary results show that model variability is conditional and can be attributed to different parameters depending on different timescales. By using sensitivity analysis to assess model output and variability, calibrations of simulation models can be better informed to yield more
Variance estimation for sensitivity analysis of poverty and inequality measures
Directory of Open Access Journals (Sweden)
Christian Dudel
2017-04-01
Full Text Available Estimates of poverty and inequality are often based on application of a single equivalence scale, despite the fact that a large number of different equivalence scales can be found in the literature. This paper describes a framework for sensitivity analysis which can be used to account for the variability of equivalence scales and allows to derive variance estimates of results of sensitivity analysis. Simulations show that this method yields reliable estimates. An empirical application reveals that accounting for both variability of equivalence scales and sampling variance leads to confidence intervals which are wide.
Sensitivity analysis of water consumption in an office building
Suchacek, Tomas; Tuhovcak, Ladislav; Rucka, Jan
2018-02-01
This article deals with sensitivity analysis of real water consumption in an office building. During a long-term real study, reducing of pressure in its water connection was simulated. A sensitivity analysis of uneven water demand was conducted during working time at various provided pressures and at various time step duration. Correlations between maximal coefficients of water demand variation during working time and provided pressure were suggested. The influence of provided pressure in the water connection on mean coefficients of water demand variation was pointed out, altogether for working hours of all days and separately for days with identical working hours.
Probabilistic and sensitivity analysis of Botlek Bridge structures
Directory of Open Access Journals (Sweden)
Králik Juraj
2017-01-01
Full Text Available This paper deals with the probabilistic and sensitivity analysis of the largest movable lift bridge of the world. The bridge system consists of six reinforced concrete pylons and two steel decks 4000 tons weight each connected through ropes with counterweights. The paper focuses the probabilistic and sensitivity analysis as the base of dynamic study in design process of the bridge. The results had a high importance for practical application and design of the bridge. The model and resistance uncertainties were taken into account in LHS simulation method.
Applying DEA sensitivity analysis to efficiency measurement of Vietnamese universities
Directory of Open Access Journals (Sweden)
Thi Thanh Huyen Nguyen
2015-11-01
Full Text Available The primary purpose of this study is to measure the technical efficiency of 30 doctorate-granting universities, the universities or the higher education institutes with PhD training programs, in Vietnam, applying the sensitivity analysis of data envelopment analysis (DEA. The study uses eight sets of input-output specifications using the replacement as well as aggregation/disaggregation of variables. The measurement results allow us to examine the sensitivity of the efficiency of these universities with the sets of variables. The findings also show the impact of variables on their efficiency and its “sustainability”.
Seismic analysis of steam generator and parameter sensitivity studies
International Nuclear Information System (INIS)
Qian Hao; Xu Dinggen; Yang Ren'an; Liang Xingyun
2013-01-01
Background: The steam generator (SG) serves as the primary means for removing the heat generated within the reactor core and is part of the reactor coolant system (RCS) pressure boundary. Purpose: Seismic analysis in required for SG, whose seismic category is Cat. I. Methods: The analysis model of SG is created with moisture separator assembly and tube bundle assembly herein. The seismic analysis is performed with RCS pipe and Reactor Pressure Vessel (RPV). Results: The seismic stress results of SG are obtained. In addition, parameter sensitivities of seismic analysis results are studied, such as the effect of another SG, support, anti-vibration bars (AVBs), and so on. Our results show that seismic results are sensitive to support and AVBs setting. Conclusions: The guidance and comments on these parameters are summarized for equipment design and analysis, which should be focused on in future new type NPP SG's research and design. (authors)
A Geographical Heuristic Routing Protocol for VANETs
Urquiza-Aguiar, Luis; Tripp-Barba, Carolina; Aguilar Igartua, Mónica
2016-01-01
Vehicular ad hoc networks (VANETs) leverage the communication system of Intelligent Transportation Systems (ITS). Recently, Delay-Tolerant Network (DTN) routing protocols have increased their popularity among the research community for being used in non-safety VANET applications and services like traffic reporting. Vehicular DTN protocols use geographical and local information to make forwarding decisions. However, current proposals only consider the selection of the best candidate based on a local-search. In this paper, we propose a generic Geographical Heuristic Routing (GHR) protocol that can be applied to any DTN geographical routing protocol that makes forwarding decisions hop by hop. GHR includes in its operation adaptations simulated annealing and Tabu-search meta-heuristics, which have largely been used to improve local-search results in discrete optimization. We include a complete performance evaluation of GHR in a multi-hop VANET simulation scenario for a reporting service. Our study analyzes all of the meaningful configurations of GHR and offers a statistical analysis of our findings by means of MANOVA tests. Our results indicate that the use of a Tabu list contributes to improving the packet delivery ratio by around 5% to 10%. Moreover, if Tabu is used, then the simulated annealing routing strategy gets a better performance than the selection of the best node used with carry and forwarding (default operation). PMID:27669254
A Heuristic Process for GUI Widget Matching Across Application Versions
Molnar, Arthur-Jozsef
2017-01-01
This paper introduces an automated heuristic process able to achieve high accuracy when matching graphical user interface widgets across multiple versions of a target application. The proposed implementation is flexible as it allows full customization of the process and easy integration with existing tools for long term graphical user interface test case maintenance, software visualization and analysis.
Automated differentiation of computer models for sensitivity analysis
International Nuclear Information System (INIS)
Worley, B.A.
1990-01-01
Sensitivity analysis of reactor physics computer models is an established discipline after more than twenty years of active development of generalized perturbations theory based on direct and adjoint methods. Many reactor physics models have been enhanced to solve for sensitivities of model results to model data. The calculated sensitivities are usually normalized first derivatives although some codes are capable of solving for higher-order sensitivities. The purpose of this paper is to report on the development and application of the GRESS system for automating the implementation of the direct and adjoint techniques into existing FORTRAN computer codes. The GRESS system was developed at ORNL to eliminate the costly man-power intensive effort required to implement the direct and adjoint techniques into already-existing FORTRAN codes. GRESS has been successfully tested for a number of codes over a wide range of applications and presently operates on VAX machines under both VMS and UNIX operating systems
Automated differentiation of computer models for sensitivity analysis
International Nuclear Information System (INIS)
Worley, B.A.
1991-01-01
Sensitivity analysis of reactor physics computer models is an established discipline after more than twenty years of active development of generalized perturbations theory based on direct and adjoint methods. Many reactor physics models have been enhanced to solve for sensitivities of model results to model data. The calculated sensitivities are usually normalized first derivatives, although some codes are capable of solving for higher-order sensitivities. The purpose of this paper is to report on the development and application of the GRESS system for automating the implementation of the direct and adjoint techniques into existing FORTRAN computer codes. The GRESS system was developed at ORNL to eliminate the costly man-power intensive effort required to implement the direct and adjoint techniques into already-existing FORTRAN codes. GRESS has been successfully tested for a number of codes over a wide range of applications and presently operates on VAX machines under both VMS and UNIX operating systems. (author). 9 refs, 1 tab
A Global Sensitivity Analysis Methodology for Multi-physics Applications
Energy Technology Data Exchange (ETDEWEB)
Tong, C H; Graziani, F R
2007-02-02
Experiments are conducted to draw inferences about an entire ensemble based on a selected number of observations. This applies to both physical experiments as well as computer experiments, the latter of which are performed by running the simulation models at different input configurations and analyzing the output responses. Computer experiments are instrumental in enabling model analyses such as uncertainty quantification and sensitivity analysis. This report focuses on a global sensitivity analysis methodology that relies on a divide-and-conquer strategy and uses intelligent computer experiments. The objective is to assess qualitatively and/or quantitatively how the variabilities of simulation output responses can be accounted for by input variabilities. We address global sensitivity analysis in three aspects: methodology, sampling/analysis strategies, and an implementation framework. The methodology consists of three major steps: (1) construct credible input ranges; (2) perform a parameter screening study; and (3) perform a quantitative sensitivity analysis on a reduced set of parameters. Once identified, research effort should be directed to the most sensitive parameters to reduce their uncertainty bounds. This process is repeated with tightened uncertainty bounds for the sensitive parameters until the output uncertainties become acceptable. To accommodate the needs of multi-physics application, this methodology should be recursively applied to individual physics modules. The methodology is also distinguished by an efficient technique for computing parameter interactions. Details for each step will be given using simple examples. Numerical results on large scale multi-physics applications will be available in another report. Computational techniques targeted for this methodology have been implemented in a software package called PSUADE.
Automated sensitivity analysis: New tools for modeling complex dynamic systems
International Nuclear Information System (INIS)
Pin, F.G.
1987-01-01
Sensitivity analysis is an established methodology used by researchers in almost every field to gain essential insight in design and modeling studies and in performance assessments of complex systems. Conventional sensitivity analysis methodologies, however, have not enjoyed the widespread use they deserve considering the wealth of information they can provide, partly because of their prohibitive cost or the large initial analytical investment they require. Automated systems have recently been developed at ORNL to eliminate these drawbacks. Compilers such as GRESS and EXAP now allow automatic and cost effective calculation of sensitivities in FORTRAN computer codes. In this paper, these and other related tools are described and their impact and applicability in the general areas of modeling, performance assessment and decision making for radioactive waste isolation problems are discussed
The Volatility of Data Space: Topology Oriented Sensitivity Analysis
Du, Jing; Ligmann-Zielinska, Arika
2015-01-01
Despite the difference among specific methods, existing Sensitivity Analysis (SA) technologies are all value-based, that is, the uncertainties in the model input and output are quantified as changes of values. This paradigm provides only limited insight into the nature of models and the modeled systems. In addition to the value of data, a potentially richer information about the model lies in the topological difference between pre-model data space and post-model data space. This paper introduces an innovative SA method called Topology Oriented Sensitivity Analysis, which defines sensitivity as the volatility of data space. It extends SA into a deeper level that lies in the topology of data. PMID:26368929
Interactive Building Design Space Exploration Using Regionalized Sensitivity Analysis
DEFF Research Database (Denmark)
Østergård, Torben; Jensen, Rasmus Lund; Maagaard, Steffen
2017-01-01
simulation inputs are most important and which have negligible influence on the model output. Popular sensitivity methods include the Morris method, variance-based methods (e.g. Sobol’s), and regression methods (e.g. SRC). However, all these methods only address one output at a time, which makes it difficult...... in combination with the interactive parallel coordinate plot (PCP). The latter is an effective tool to explore stochastic simulations and to find high-performing building designs. The proposed methods help decision makers to focus their attention to the most important design parameters when exploring......Monte Carlo simulations combined with regionalized sensitivity analysis provide the means to explore a vast, multivariate design space in building design. Typically, sensitivity analysis shows how the variability of model output relates to the uncertainties in models inputs. This reveals which...
Sensitization trajectories in childhood revealed by using a cluster analysis
DEFF Research Database (Denmark)
Schoos, Ann-Marie M.; Chawes, Bo L.; Melen, Erik
2017-01-01
Prospective Studies on Asthma in Childhood 2000 (COPSAC2000) birth cohort with specific IgE against 13 common food and inhalant allergens at the ages of ½, 1½, 4, and 6 years. An unsupervised cluster analysis for 3-dimensional data (nonnegative sparse parallel factor analysis) was used to extract latent......BACKGROUND: Assessment of sensitization at a single time point during childhood provides limited clinical information. We hypothesized that sensitization develops as specific patterns with respect to age at debut, development over time, and involved allergens and that such patterns might be more...... biologically and clinically relevant. OBJECTIVE: We sought to explore latent patterns of sensitization during the first 6 years of life and investigate whether such patterns associate with the development of asthma, rhinitis, and eczema. METHODS: We investigated 398 children from the at-risk Copenhagen...
Time-dependent reliability sensitivity analysis of motion mechanisms
International Nuclear Information System (INIS)
Wei, Pengfei; Song, Jingwen; Lu, Zhenzhou; Yue, Zhufeng
2016-01-01
Reliability sensitivity analysis aims at identifying the source of structure/mechanism failure, and quantifying the effects of each random source or their distribution parameters on failure probability or reliability. In this paper, the time-dependent parametric reliability sensitivity (PRS) analysis as well as the global reliability sensitivity (GRS) analysis is introduced for the motion mechanisms. The PRS indices are defined as the partial derivatives of the time-dependent reliability w.r.t. the distribution parameters of each random input variable, and they quantify the effect of the small change of each distribution parameter on the time-dependent reliability. The GRS indices are defined for quantifying the individual, interaction and total contributions of the uncertainty in each random input variable to the time-dependent reliability. The envelope function method combined with the first order approximation of the motion error function is introduced for efficiently estimating the time-dependent PRS and GRS indices. Both the time-dependent PRS and GRS analysis techniques can be especially useful for reliability-based design. This significance of the proposed methods as well as the effectiveness of the envelope function method for estimating the time-dependent PRS and GRS indices are demonstrated with a four-bar mechanism and a car rack-and-pinion steering linkage. - Highlights: • Time-dependent parametric reliability sensitivity analysis is presented. • Time-dependent global reliability sensitivity analysis is presented for mechanisms. • The proposed method is especially useful for enhancing the kinematic reliability. • An envelope method is introduced for efficiently implementing the proposed methods. • The proposed method is demonstrated by two real planar mechanisms.
Probabilistic sensitivity analysis of system availability using Gaussian processes
International Nuclear Information System (INIS)
Daneshkhah, Alireza; Bedford, Tim
2013-01-01
The availability of a system under a given failure/repair process is a function of time which can be determined through a set of integral equations and usually calculated numerically. We focus here on the issue of carrying out sensitivity analysis of availability to determine the influence of the input parameters. The main purpose is to study the sensitivity of the system availability with respect to the changes in the main parameters. In the simplest case that the failure repair process is (continuous time/discrete state) Markovian, explicit formulae are well known. Unfortunately, in more general cases availability is often a complicated function of the parameters without closed form solution. Thus, the computation of sensitivity measures would be time-consuming or even infeasible. In this paper, we show how Sobol and other related sensitivity measures can be cheaply computed to measure how changes in the model inputs (failure/repair times) influence the outputs (availability measure). We use a Bayesian framework, called the Bayesian analysis of computer code output (BACCO) which is based on using the Gaussian process as an emulator (i.e., an approximation) of complex models/functions. This approach allows effective sensitivity analysis to be achieved by using far smaller numbers of model runs than other methods. The emulator-based sensitivity measure is used to examine the influence of the failure and repair densities' parameters on the system availability. We discuss how to apply the methods practically in the reliability context, considering in particular the selection of parameters and prior distributions and how we can ensure these may be considered independent—one of the key assumptions of the Sobol approach. The method is illustrated on several examples, and we discuss the further implications of the technique for reliability and maintenance analysis
Analytic uncertainty and sensitivity analysis of models with input correlations
Zhu, Yueying; Wang, Qiuping A.; Li, Wei; Cai, Xu
2018-03-01
Probabilistic uncertainty analysis is a common means of evaluating mathematical models. In mathematical modeling, the uncertainty in input variables is specified through distribution laws. Its contribution to the uncertainty in model response is usually analyzed by assuming that input variables are independent of each other. However, correlated parameters are often happened in practical applications. In the present paper, an analytic method is built for the uncertainty and sensitivity analysis of models in the presence of input correlations. With the method, it is straightforward to identify the importance of the independence and correlations of input variables in determining the model response. This allows one to decide whether or not the input correlations should be considered in practice. Numerical examples suggest the effectiveness and validation of our analytic method in the analysis of general models. A practical application of the method is also proposed to the uncertainty and sensitivity analysis of a deterministic HIV model.
The emotional reasoning heuristic in children.
Muris, P; Merckelbach, H; van Spauwen, I
2003-03-01
A previous study by Arntz, Rauner, and Van den Hout (1995; Behaviour Research and Therapy, 33, 917-925) has shown that adult anxiety patients tend to infer danger not only on the basis of objective danger information, but also on the basis of anxiety response information. The current study examined whether this so-called emotional reasoning phenomenon also occurs in children. Normal primary school children (N = 101) first completed scales tapping anxiety disorders symptoms, anxiety sensitivity, and trait anxiety. Next, they were asked to rate danger levels of scripts in which objective danger versus objective safety and anxiety response versus no anxiety response were systematically varied. Evidence was found for a general emotional reasoning effect. That is, children's danger ratings were not only a function of objective danger information, but also, in the case of objective safety scripts, by anxiety response information. This emotional reasoning effect was predicted by levels of anxiety sensitivity and trait anxiety. More specifically, high levels of anxiety sensitivity and trait anxiety were accompanied by a greater tendency to use anxiety-response information as an heuristic for assessing dangerousness of safety scripts. Implications of these findings are briefly discussed.
Sensitivity Analysis Applied in Design of Low Energy Office Building
DEFF Research Database (Denmark)
Heiselberg, Per; Brohus, Henrik
2008-01-01
satisfies the design requirements and objectives. In the design of sustainable Buildings it is beneficial to identify the most important design parameters in order to develop more efficiently alternative design solutions or reach optimized design solutions. A sensitivity analysis makes it possible...
Application of Sensitivity Analysis in Design of Sustainable Buildings
DEFF Research Database (Denmark)
Heiselberg, Per; Brohus, Henrik; Hesselholt, Allan Tind
2007-01-01
satisfies the design requirements and objectives. In the design of sustainable Buildings it is beneficial to identify the most important design parameters in order to develop more efficiently alternative design solutions or reach optimized design solutions. A sensitivity analysis makes it possible...
Sensitivity analysis of physiochemical interaction model: which pair ...
African Journals Online (AJOL)
... of two model parameters at a time on the solution trajectory of physiochemical interaction over a time interval. Our aim is to use this powerful mathematical technique to select the important pair of parameters of this physical process which is cost-effective. Keywords: Passivation Rate, Sensitivity Analysis, ODE23, ODE45 ...
Bayesian Sensitivity Analysis of Statistical Models with Missing Data.
Zhu, Hongtu; Ibrahim, Joseph G; Tang, Niansheng
2014-04-01
Methods for handling missing data depend strongly on the mechanism that generated the missing values, such as missing completely at random (MCAR) or missing at random (MAR), as well as other distributional and modeling assumptions at various stages. It is well known that the resulting estimates and tests may be sensitive to these assumptions as well as to outlying observations. In this paper, we introduce various perturbations to modeling assumptions and individual observations, and then develop a formal sensitivity analysis to assess these perturbations in the Bayesian analysis of statistical models with missing data. We develop a geometric framework, called the Bayesian perturbation manifold, to characterize the intrinsic structure of these perturbations. We propose several intrinsic influence measures to perform sensitivity analysis and quantify the effect of various perturbations to statistical models. We use the proposed sensitivity analysis procedure to systematically investigate the tenability of the non-ignorable missing at random (NMAR) assumption. Simulation studies are conducted to evaluate our methods, and a dataset is analyzed to illustrate the use of our diagnostic measures.
Sensitivity analysis for contagion effects in social networks
VanderWeele, Tyler J.
2014-01-01
Analyses of social network data have suggested that obesity, smoking, happiness and loneliness all travel through social networks. Individuals exert “contagion effects” on one another through social ties and association. These analyses have come under critique because of the possibility that homophily from unmeasured factors may explain these statistical associations and because similar findings can be obtained when the same methodology is applied to height, acne and head-aches, for which the conclusion of contagion effects seems somewhat less plausible. We use sensitivity analysis techniques to assess the extent to which supposed contagion effects for obesity, smoking, happiness and loneliness might be explained away by homophily or confounding and the extent to which the critique using analysis of data on height, acne and head-aches is relevant. Sensitivity analyses suggest that contagion effects for obesity and smoking cessation are reasonably robust to possible latent homophily or environmental confounding; those for happiness and loneliness are somewhat less so. Supposed effects for height, acne and head-aches are all easily explained away by latent homophily and confounding. The methodology that has been employed in past studies for contagion effects in social networks, when used in conjunction with sensitivity analysis, may prove useful in establishing social influence for various behaviors and states. The sensitivity analysis approach can be used to address the critique of latent homophily as a possible explanation of associations interpreted as contagion effects. PMID:25580037
Sensitivity Analysis of a Horizontal Earth Electrode under Impulse ...
African Journals Online (AJOL)
This paper presents the sensitivity analysis of an earthing conductor under the influence of impulse current arising from a lightning stroke. The approach is based on the 2nd order finite difference time domain (FDTD). The earthing conductor is regarded as a lossy transmission line where it is divided into series connected ...
Beyond the GUM: variance-based sensitivity analysis in metrology
International Nuclear Information System (INIS)
Lira, I
2016-01-01
Variance-based sensitivity analysis is a well established tool for evaluating the contribution of the uncertainties in the inputs to the uncertainty in the output of a general mathematical model. While the literature on this subject is quite extensive, it has not found widespread use in metrological applications. In this article we present a succinct review of the fundamentals of sensitivity analysis, in a form that should be useful to most people familiarized with the Guide to the Expression of Uncertainty in Measurement (GUM). Through two examples, it is shown that in linear measurement models, no new knowledge is gained by using sensitivity analysis that is not already available after the terms in the so-called ‘law of propagation of uncertainties’ have been computed. However, if the model behaves non-linearly in the neighbourhood of the best estimates of the input quantities—and if these quantities are assumed to be statistically independent—sensitivity analysis is definitely advantageous for gaining insight into how they can be ranked according to their importance in establishing the uncertainty of the measurand. (paper)
Sensitivity analysis of the Ohio phosphorus risk index
The Phosphorus (P) Index is a widely used tool for assessing the vulnerability of agricultural fields to P loss; yet, few of the P Indices developed in the U.S. have been evaluated for their accuracy. Sensitivity analysis is one approach that can be used prior to calibration and field-scale testing ...
Sensitivity analysis for oblique incidence reflectometry using Monte Carlo simulations
DEFF Research Database (Denmark)
Kamran, Faisal; Andersen, Peter E.
2015-01-01
profiles. This article presents a sensitivity analysis of the technique in turbid media. Monte Carlo simulations are used to investigate the technique and its potential to distinguish the small changes between different levels of scattering. We present various regions of the dynamic range of optical...
Omitted Variable Sensitivity Analysis with the Annotated Love Plot
Hansen, Ben B.; Fredrickson, Mark M.
2014-01-01
The goal of this research is to make sensitivity analysis accessible not only to empirical researchers but also to the various stakeholders for whom educational evaluations are conducted. To do this it derives anchors for the omitted variable (OV)-program participation association intrinsically, using the Love plot to present a wide range of…
Weighting-Based Sensitivity Analysis in Causal Mediation Studies
Hong, Guanglei; Qin, Xu; Yang, Fan
2018-01-01
Through a sensitivity analysis, the analyst attempts to determine whether a conclusion of causal inference could be easily reversed by a plausible violation of an identification assumption. Analytic conclusions that are harder to alter by such a violation are expected to add a higher value to scientific knowledge about causality. This article…
Sensitivity analysis of railpad parameters on vertical railway track dynamics
Oregui Echeverria-Berreyarza, M.; Nunez Vicencio, Alfredo; Dollevoet, R.P.B.J.; Li, Z.
2016-01-01
This paper presents a sensitivity analysis of railpad parameters on vertical railway track dynamics, incorporating the nonlinear behavior of the fastening (i.e., downward forces compress the railpad whereas upward forces are resisted by the clamps). For this purpose, solid railpads, rail-railpad
Methods for global sensitivity analysis in life cycle assessment
Groen, Evelyne A.; Bokkers, Eddy; Heijungs, Reinout; Boer, de Imke J.M.
2017-01-01
Purpose: Input parameters required to quantify environmental impact in life cycle assessment (LCA) can be uncertain due to e.g. temporal variability or unknowns about the true value of emission factors. Uncertainty of environmental impact can be analysed by means of a global sensitivity analysis to
Sensitivity analysis on ultimate strength of aluminium stiffened panels
DEFF Research Database (Denmark)
Rigo, P.; Sarghiuta, R.; Estefen, S.
2003-01-01
This paper presents the results of an extensive sensitivity analysis carried out by the Committee III.1 "Ultimate Strength" of ISSC?2003 in the framework of a benchmark on the ultimate strength of aluminium stiffened panels. Previously, different benchmarks were presented by ISSC committees on ul...
Sensitivity and specificity of coherence and phase synchronization analysis
International Nuclear Information System (INIS)
Winterhalder, Matthias; Schelter, Bjoern; Kurths, Juergen; Schulze-Bonhage, Andreas; Timmer, Jens
2006-01-01
In this Letter, we show that coherence and phase synchronization analysis are sensitive but not specific in detecting the correct class of underlying dynamics. We propose procedures to increase specificity and demonstrate the power of the approach by application to paradigmatic dynamic model systems
Sensitivity Analysis of Structures by Virtual Distortion Method
DEFF Research Database (Denmark)
Gierlinski, J.T.; Holnicki-Szulc, J.; Sørensen, John Dalsgaard
1991-01-01
are used in structural optimization, see Haftka [4]. The recently developed Virtual Distortion Method (VDM) is a numerical technique which offers an efficient approach to calculation of the sensitivity derivatives. This method has been orginally applied to structural remodelling and collapse analysis, see...
Design tradeoff studies and sensitivity analysis. Appendix B
Energy Technology Data Exchange (ETDEWEB)
1979-05-25
The results of the design trade-off studies and the sensitivity analysis of Phase I of the Near Term Hybrid Vehicle (NTHV) Program are presented. The effects of variations in the design of the vehicle body, propulsion systems, and other components on vehicle power, weight, cost, and fuel economy and an optimized hybrid vehicle design are discussed. (LCL)
Heuristic Approach for Balancing Shift Schedules
International Nuclear Information System (INIS)
Kim, Dae Ho; Yun, Young Su; Lee, Yong Hee
2005-01-01
In this paper, a heuristic approach for balancing shift schedules is proposed. For the shift schedules, various constraints which have usually been considered in realworld industry are used, and the objective is to minimize the differences of the workloads in each workgroup. The constraints and objective function are implemented in the proposed heuristic approach. Using a simple instance, the efficiency of the proposed heuristic approach is proved
Heuristics and stock buying decision: Evidence from Malaysian and Pakistani stock markets
Directory of Open Access Journals (Sweden)
Habib Hussain Khan
2017-06-01
Full Text Available Applying both qualitative and quantitative approaches, we examine whether or not investors fall prey to three heuristics; namely, anchoring and adjustment, representativeness, and availability, while investing in stocks. We also compare investors' vulnerability to these heuristics based on their economic association, their type and demographic factors such as income, education and experience. For the data collection, a self-constructed questionnaire was administered to investors in the Malaysian and Pakistani stock exchanges. Data has been analyzed through description, correlation and regression analysis. The results indicate that all three heuristics are likely to affect the investors' stock buying decisions. The effect of heuristics is similar across the sample countries, the type of investors, and the income groups. However, the investors with a higher level of education and more experience are less likely to be affected by the heuristics.
Sensitivity analysis and power for instrumental variable studies.
Wang, Xuran; Jiang, Yang; Zhang, Nancy R; Small, Dylan S
2018-03-31
In observational studies to estimate treatment effects, unmeasured confounding is often a concern. The instrumental variable (IV) method can control for unmeasured confounding when there is a valid IV. To be a valid IV, a variable needs to be independent of unmeasured confounders and only affect the outcome through affecting the treatment. When applying the IV method, there is often concern that a putative IV is invalid to some degree. We present an approach to sensitivity analysis for the IV method which examines the sensitivity of inferences to violations of IV validity. Specifically, we consider sensitivity when the magnitude of association between the putative IV and the unmeasured confounders and the direct effect of the IV on the outcome are limited in magnitude by a sensitivity parameter. Our approach is based on extending the Anderson-Rubin test and is valid regardless of the strength of the instrument. A power formula for this sensitivity analysis is presented. We illustrate its usage via examples about Mendelian randomization studies and its implications via a comparison of using rare versus common genetic variants as instruments. © 2018, The International Biometric Society.
A single cognitive heuristic process meets the complexity of domain-specific moral heuristics.
Dubljević, Veljko; Racine, Eric
2014-10-01
The inherence heuristic (a) offers modest insights into the complex nature of both the is-ought tension in moral reasoning and moral reasoning per se, and (b) does not reflect the complexity of domain-specific moral heuristics. Formal and general in nature, we contextualize the process described as "inherence heuristic" in a web of domain-specific heuristics (e.g., agent specific; action specific; consequences specific).
Sensitivity analysis of LOFT L2-5 test calculations
International Nuclear Information System (INIS)
Prosek, Andrej
2014-01-01
The uncertainty quantification of best-estimate code predictions is typically accompanied by a sensitivity analysis, in which the influence of the individual contributors to uncertainty is determined. The objective of this study is to demonstrate the improved fast Fourier transform based method by signal mirroring (FFTBM-SM) for the sensitivity analysis. The sensitivity study was performed for the LOFT L2-5 test, which simulates the large break loss of coolant accident. There were 14 participants in the BEMUSE (Best Estimate Methods-Uncertainty and Sensitivity Evaluation) programme, each performing a reference calculation and 15 sensitivity runs of the LOFT L2-5 test. The important input parameters varied were break area, gap conductivity, fuel conductivity, decay power etc. For the influence of input parameters on the calculated results the FFTBM-SM was used. The only difference between FFTBM-SM and original FFTBM is that in the FFTBM-SM the signals are symmetrized to eliminate the edge effect (the so called edge is the difference between the first and last data point of one period of the signal) in calculating average amplitude. It is very important to eliminate unphysical contribution to the average amplitude, which is used as a figure of merit for input parameter influence on output parameters. The idea is to use reference calculation as 'experimental signal', 'sensitivity run' as 'calculated signal', and average amplitude as figure of merit for sensitivity instead for code accuracy. The larger is the average amplitude the larger is the influence of varied input parameter. The results show that with FFTBM-SM the analyst can get good picture of the contribution of the parameter variation to the results. They show when the input parameters are influential and how big is this influence. FFTBM-SM could be also used to quantify the influence of several parameter variations on the results. However, the influential parameters could not be
International Nuclear Information System (INIS)
Harper, W.V.; Gupta, S.K.
1983-10-01
A computer code was used to study steady-state flow for a hypothetical borehole scenario. The model consists of three coupled equations with only eight parameters and three dependent variables. This study focused on steady-state flow as the performance measure of interest. Two different approaches to sensitivity/uncertainty analysis were used on this code. One approach, based on Latin Hypercube Sampling (LHS), is a statistical sampling method, whereas, the second approach is based on the deterministic evaluation of sensitivities. The LHS technique is easy to apply and should work well for codes with a moderate number of parameters. Of deterministic techniques, the direct method is preferred when there are many performance measures of interest and a moderate number of parameters. The adjoint method is recommended when there are a limited number of performance measures and an unlimited number of parameters. This unlimited number of parameters capability can be extremely useful for finite element or finite difference codes with a large number of grid blocks. The Office of Nuclear Waste Isolation will use the technique most appropriate for an individual situation. For example, the adjoint method may be used to reduce the scope to a size that can be readily handled by a technique such as LHS. Other techniques for sensitivity/uncertainty analysis, e.g., kriging followed by conditional simulation, will be used also. 15 references, 4 figures, 9 tables
Sensitivity and uncertainty analysis of NET/ITER shielding blankets
International Nuclear Information System (INIS)
Hogenbirk, A.; Gruppelaar, H.; Verschuur, K.A.
1990-09-01
Results are presented of sensitivity and uncertainty calculations based upon the European fusion file (EFF-1). The effect of uncertainties in Fe, Cr and Ni cross sections on the nuclear heating in the coils of a NET/ITER shielding blanket has been studied. The analysis has been performed for the total cross section as well as partial cross sections. The correct expression for the sensitivity profile was used, including the gain term. The resulting uncertainty in the nuclear heating lies between 10 and 20 per cent. (author). 18 refs.; 2 figs.; 2 tabs
Sensitivity analysis of critical experiments with evaluated nuclear data libraries
International Nuclear Information System (INIS)
Fujiwara, D.; Kosaka, S.
2008-01-01
Criticality benchmark testing was performed with evaluated nuclear data libraries for thermal, low-enriched uranium fuel rod applications. C/E values for k eff were calculated with the continuous-energy Monte Carlo code MVP2 and its libraries generated from Endf/B-VI.8, Endf/B-VII.0, JENDL-3.3 and JEFF-3.1. Subsequently, the observed k eff discrepancies between libraries were decomposed to specify the source of difference in the nuclear data libraries using sensitivity analysis technique. The obtained sensitivity profiles are also utilized to estimate the adequacy of cold critical experiments to the boiling water reactor under hot operating condition. (authors)
Importance measures in global sensitivity analysis of nonlinear models
International Nuclear Information System (INIS)
Homma, Toshimitsu; Saltelli, Andrea
1996-01-01
The present paper deals with a new method of global sensitivity analysis of nonlinear models. This is based on a measure of importance to calculate the fractional contribution of the input parameters to the variance of the model prediction. Measures of importance in sensitivity analysis have been suggested by several authors, whose work is reviewed in this article. More emphasis is given to the developments of sensitivity indices by the Russian mathematician I.M. Sobol'. Given that Sobol' treatment of the measure of importance is the most general, his formalism is employed throughout this paper where conceptual and computational improvements of the method are presented. The computational novelty of this study is the introduction of the 'total effect' parameter index. This index provides a measure of the total effect of a given parameter, including all the possible synergetic terms between that parameter and all the others. Rank transformation of the data is also introduced in order to increase the reproducibility of the method. These methods are tested on a few analytical and computer models. The main conclusion of this work is the identification of a sensitivity analysis methodology which is both flexible, accurate and informative, and which can be achieved at reasonable computational cost
Rethinking Sensitivity Analysis of Nuclear Simulations with Topology
Energy Technology Data Exchange (ETDEWEB)
Dan Maljovec; Bei Wang; Paul Rosen; Andrea Alfonsi; Giovanni Pastore; Cristian Rabiti; Valerio Pascucci
2016-01-01
In nuclear engineering, understanding the safety margins of the nuclear reactor via simulations is arguably of paramount importance in predicting and preventing nuclear accidents. It is therefore crucial to perform sensitivity analysis to understand how changes in the model inputs affect the outputs. Modern nuclear simulation tools rely on numerical representations of the sensitivity information -- inherently lacking in visual encodings -- offering limited effectiveness in communicating and exploring the generated data. In this paper, we design a framework for sensitivity analysis and visualization of multidimensional nuclear simulation data using partition-based, topology-inspired regression models and report on its efficacy. We rely on the established Morse-Smale regression technique, which allows us to partition the domain into monotonic regions where easily interpretable linear models can be used to assess the influence of inputs on the output variability. The underlying computation is augmented with an intuitive and interactive visual design to effectively communicate sensitivity information to the nuclear scientists. Our framework is being deployed into the multi-purpose probabilistic risk assessment and uncertainty quantification framework RAVEN (Reactor Analysis and Virtual Control Environment). We evaluate our framework using an simulation dataset studying nuclear fuel performance.
Gigerenzer, Gerd
2009-01-01
In their comment on Marewski et al. (good judgments do not require complex cognition, 2009) Evans and Over (heuristic thinking and human intelligence: a commentary on Marewski, Gaissmaier and Gigerenzer, 2009) conjectured that heuristics can often lead to biases and are not error free. This is a most surprising critique. The computational models of heuristics we have tested allow for quantitative predictions of how many errors a given heuristic will make, and we and others have measured the amount of error by analysis, computer simulation, and experiment. This is clear progress over simply giving heuristics labels, such as availability, that do not allow for quantitative comparisons of errors. Evans and Over argue that the reason people rely on heuristics is the accuracy-effort trade-off. However, the comparison between heuristics and more effortful strategies, such as multiple regression, has shown that there are many situations in which a heuristic is more accurate with less effort. Finally, we do not see how the fast and frugal heuristics program could benefit from a dual-process framework unless the dual-process framework is made more precise. Instead, the dual-process framework could benefit if its two “black boxes” (Type 1 and Type 2 processes) were substituted by computational models of both heuristics and other processes. PMID:19784854
Prior Sensitivity Analysis in Default Bayesian Structural Equation Modeling.
van Erp, Sara; Mulder, Joris; Oberski, Daniel L
2017-11-27
Bayesian structural equation modeling (BSEM) has recently gained popularity because it enables researchers to fit complex models and solve some of the issues often encountered in classical maximum likelihood estimation, such as nonconvergence and inadmissible solutions. An important component of any Bayesian analysis is the prior distribution of the unknown model parameters. Often, researchers rely on default priors, which are constructed in an automatic fashion without requiring substantive prior information. However, the prior can have a serious influence on the estimation of the model parameters, which affects the mean squared error, bias, coverage rates, and quantiles of the estimates. In this article, we investigate the performance of three different default priors: noninformative improper priors, vague proper priors, and empirical Bayes priors-with the latter being novel in the BSEM literature. Based on a simulation study, we find that these three default BSEM methods may perform very differently, especially with small samples. A careful prior sensitivity analysis is therefore needed when performing a default BSEM analysis. For this purpose, we provide a practical step-by-step guide for practitioners to conducting a prior sensitivity analysis in default BSEM. Our recommendations are illustrated using a well-known case study from the structural equation modeling literature, and all code for conducting the prior sensitivity analysis is available in the online supplemental materials. (PsycINFO Database Record (c) 2017 APA, all rights reserved).
A global sensitivity analysis approach for morphogenesis models
Boas, Sonja E. M.
2015-11-21
Background Morphogenesis is a developmental process in which cells organize into shapes and patterns. Complex, non-linear and multi-factorial models with images as output are commonly used to study morphogenesis. It is difficult to understand the relation between the uncertainty in the input and the output of such ‘black-box’ models, giving rise to the need for sensitivity analysis tools. In this paper, we introduce a workflow for a global sensitivity analysis approach to study the impact of single parameters and the interactions between them on the output of morphogenesis models. Results To demonstrate the workflow, we used a published, well-studied model of vascular morphogenesis. The parameters of this cellular Potts model (CPM) represent cell properties and behaviors that drive the mechanisms of angiogenic sprouting. The global sensitivity analysis correctly identified the dominant parameters in the model, consistent with previous studies. Additionally, the analysis provided information on the relative impact of single parameters and of interactions between them. This is very relevant because interactions of parameters impede the experimental verification of the predicted effect of single parameters. The parameter interactions, although of low impact, provided also new insights in the mechanisms of in silico sprouting. Finally, the analysis indicated that the model could be reduced by one parameter. Conclusions We propose global sensitivity analysis as an alternative approach to study the mechanisms of morphogenesis. Comparison of the ranking of the impact of the model parameters to knowledge derived from experimental data and from manipulation experiments can help to falsify models and to find the operand mechanisms in morphogenesis. The workflow is applicable to all ‘black-box’ models, including high-throughput in vitro models in which output measures are affected by a set of experimental perturbations.
A global sensitivity analysis approach for morphogenesis models.
Boas, Sonja E M; Navarro Jimenez, Maria I; Merks, Roeland M H; Blom, Joke G
2015-11-21
Morphogenesis is a developmental process in which cells organize into shapes and patterns. Complex, non-linear and multi-factorial models with images as output are commonly used to study morphogenesis. It is difficult to understand the relation between the uncertainty in the input and the output of such 'black-box' models, giving rise to the need for sensitivity analysis tools. In this paper, we introduce a workflow for a global sensitivity analysis approach to study the impact of single parameters and the interactions between them on the output of morphogenesis models. To demonstrate the workflow, we used a published, well-studied model of vascular morphogenesis. The parameters of this cellular Potts model (CPM) represent cell properties and behaviors that drive the mechanisms of angiogenic sprouting. The global sensitivity analysis correctly identified the dominant parameters in the model, consistent with previous studies. Additionally, the analysis provided information on the relative impact of single parameters and of interactions between them. This is very relevant because interactions of parameters impede the experimental verification of the predicted effect of single parameters. The parameter interactions, although of low impact, provided also new insights in the mechanisms of in silico sprouting. Finally, the analysis indicated that the model could be reduced by one parameter. We propose global sensitivity analysis as an alternative approach to study the mechanisms of morphogenesis. Comparison of the ranking of the impact of the model parameters to knowledge derived from experimental data and from manipulation experiments can help to falsify models and to find the operand mechanisms in morphogenesis. The workflow is applicable to all 'black-box' models, including high-throughput in vitro models in which output measures are affected by a set of experimental perturbations.
Energy Technology Data Exchange (ETDEWEB)
Ortiz, J. J.; Castillo, J. A.; Montes, J. L.; Hernandez, J. L., E-mail: juanjose.ortiz@inin.gob.m [ININ, Carretera Mexico-Toluca s/n, 52750 Ocoyoacac, Estado de Mexico (Mexico)
2009-10-15
This work approaches the study of one of the heuristic rules of fuel cells design for boiling water nuclear reactors. This rule requires that the minor uranium enrichment is placed in the corners of the fuel cell. Also the search greedy is applied for the fuel cells design where explicitly does not take in count this rule, allowing the possibility to place any uranium enrichment with the condition that it does not contain gadolinium. Results are shown in the quality of the obtained cell by search greedy when it considers the rule and when not. The cell quality is measured with the value of the power pick factor obtained, as well as of the neutrons multiplication factor in an infinite medium. Cells were analyzed with 1 and 2 gadolinium concentrations low operation conditions at 120% of the nominal power of the reactors of the nuclear power plant of Laguna Verde. The results show that not to consider the rule in cells with a single gadolinium concentration, it has as repercussion that the greedy search has a minor performance. On the other hand with cells of two gadolinium concentrations, the performance of the greedy search was better. (Author)
Anisotropic analysis for seismic sensitivity of groundwater monitoring wells
Pan, Y.; Hsu, K.
2011-12-01
Taiwan is located at the boundaries of Eurasian Plate and the Philippine Sea Plate. The movement of plate causes crustal uplift and lateral deformation to lead frequent earthquakes in the vicinity of Taiwan. The change of groundwater level trigged by earthquake has been observed and studied in Taiwan for many years. The change of groundwater may appear in oscillation and step changes. The former is caused by seismic waves. The latter is caused by the volumetric strain and reflects the strain status. Since the setting of groundwater monitoring well is easier and cheaper than the setting of strain gauge, the groundwater measurement may be used as a indication of stress. This research proposes the concept of seismic sensitivity of groundwater monitoring well and apply to DonHer station in Taiwan. Geostatistical method is used to analysis the anisotropy of seismic sensitivity. GIS is used to map the sensitive area of the existing groundwater monitoring well.
Sensitivity analysis of predictive models with an automated adjoint generator
International Nuclear Information System (INIS)
Pin, F.G.; Oblow, E.M.
1987-01-01
The adjoint method is a well established sensitivity analysis methodology that is particularly efficient in large-scale modeling problems. The coefficients of sensitivity of a given response with respect to every parameter involved in the modeling code can be calculated from the solution of a single adjoint run of the code. Sensitivity coefficients provide a quantitative measure of the importance of the model data in calculating the final results. The major drawback of the adjoint method is the requirement for calculations of very large numbers of partial derivatives to set up the adjoint equations of the model. ADGEN is a software system that has been designed to eliminate this drawback and automatically implement the adjoint formulation in computer codes. The ADGEN system will be described and its use for improving performance assessments and predictive simulations will be discussed. 8 refs., 1 fig
Sensitivity analysis of time-dependent laminar flows
International Nuclear Information System (INIS)
Hristova, H.; Etienne, S.; Pelletier, D.; Borggaard, J.
2004-01-01
This paper presents a general sensitivity equation method (SEM) for time dependent incompressible laminar flows. The SEM accounts for complex parameter dependence and is suitable for a wide range of problems. The formulation is verified on a problem with a closed form solution obtained by the method of manufactured solution. Systematic grid convergence studies confirm the theoretical rates of convergence in both space and time. The methodology is then applied to pulsatile flow around a square cylinder. Computations show that the flow starts with symmetrical vortex shedding followed by a transition to the traditional Von Karman street (alternate vortex shedding). Simulations show that the transition phase manifests itself earlier in the sensitivity fields than in the flow field itself. Sensitivities are then demonstrated for fast evaluation of nearby flows and uncertainty analysis. (author)
Computational Methods for Sensitivity and Uncertainty Analysis in Criticality Safety
International Nuclear Information System (INIS)
Broadhead, B.L.; Childs, R.L.; Rearden, B.T.
1999-01-01
Interest in the sensitivity methods that were developed and widely used in the 1970s (the FORSS methodology at ORNL among others) has increased recently as a result of potential use in the area of criticality safety data validation procedures to define computational bias, uncertainties and area(s) of applicability. Functional forms of the resulting sensitivity coefficients can be used as formal parameters in the determination of applicability of benchmark experiments to their corresponding industrial application areas. In order for these techniques to be generally useful to the criticality safety practitioner, the procedures governing their use had to be updated and simplified. This paper will describe the resulting sensitivity analysis tools that have been generated for potential use by the criticality safety community
Parameter uncertainty effects on variance-based sensitivity analysis
International Nuclear Information System (INIS)
Yu, W.; Harris, T.J.
2009-01-01
In the past several years there has been considerable commercial and academic interest in methods for variance-based sensitivity analysis. The industrial focus is motivated by the importance of attributing variance contributions to input factors. A more complete understanding of these relationships enables companies to achieve goals related to quality, safety and asset utilization. In a number of applications, it is possible to distinguish between two types of input variables-regressive variables and model parameters. Regressive variables are those that can be influenced by process design or by a control strategy. With model parameters, there are typically no opportunities to directly influence their variability. In this paper, we propose a new method to perform sensitivity analysis through a partitioning of the input variables into these two groupings: regressive variables and model parameters. A sequential analysis is proposed, where first an sensitivity analysis is performed with respect to the regressive variables. In the second step, the uncertainty effects arising from the model parameters are included. This strategy can be quite useful in understanding process variability and in developing strategies to reduce overall variability. When this method is used for nonlinear models which are linear in the parameters, analytical solutions can be utilized. In the more general case of models that are nonlinear in both the regressive variables and the parameters, either first order approximations can be used, or numerically intensive methods must be used
Understanding dynamics using sensitivity analysis: caveat and solution
2011-01-01
Background Parametric sensitivity analysis (PSA) has become one of the most commonly used tools in computational systems biology, in which the sensitivity coefficients are used to study the parametric dependence of biological models. As many of these models describe dynamical behaviour of biological systems, the PSA has subsequently been used to elucidate important cellular processes that regulate this dynamics. However, in this paper, we show that the PSA coefficients are not suitable in inferring the mechanisms by which dynamical behaviour arises and in fact it can even lead to incorrect conclusions. Results A careful interpretation of parametric perturbations used in the PSA is presented here to explain the issue of using this analysis in inferring dynamics. In short, the PSA coefficients quantify the integrated change in the system behaviour due to persistent parametric perturbations, and thus the dynamical information of when a parameter perturbation matters is lost. To get around this issue, we present a new sensitivity analysis based on impulse perturbations on system parameters, which is named impulse parametric sensitivity analysis (iPSA). The inability of PSA and the efficacy of iPSA in revealing mechanistic information of a dynamical system are illustrated using two examples involving switch activation. Conclusions The interpretation of the PSA coefficients of dynamical systems should take into account the persistent nature of parametric perturbations involved in the derivation of this analysis. The application of PSA to identify the controlling mechanism of dynamical behaviour can be misleading. By using impulse perturbations, introduced at different times, the iPSA provides the necessary information to understand how dynamics is achieved, i.e. which parameters are essential and when they become important. PMID:21406095
Sensitivity Analysis of Deviation Source for Fast Assembly Precision Optimization
Directory of Open Access Journals (Sweden)
Jianjun Tang
2014-01-01
Full Text Available Assembly precision optimization of complex product has a huge benefit in improving the quality of our products. Due to the impact of a variety of deviation source coupling phenomena, the goal of assembly precision optimization is difficult to be confirmed accurately. In order to achieve optimization of assembly precision accurately and rapidly, sensitivity analysis of deviation source is proposed. First, deviation source sensitivity is defined as the ratio of assembly dimension variation and deviation source dimension variation. Second, according to assembly constraint relations, assembly sequences and locating, deviation transmission paths are established by locating the joints between the adjacent parts, and establishing each part’s datum reference frame. Third, assembly multidimensional vector loops are created using deviation transmission paths, and the corresponding scalar equations of each dimension are established. Then, assembly deviation source sensitivity is calculated by using a first-order Taylor expansion and matrix transformation method. Finally, taking assembly precision optimization of wing flap rocker as an example, the effectiveness and efficiency of the deviation source sensitivity analysis method are verified.
Sensitivity analysis for improving nanomechanical photonic transducers biosensors
International Nuclear Information System (INIS)
Fariña, D; Álvarez, M; Márquez, S; Lechuga, L M; Dominguez, C
2015-01-01
The achievement of high sensitivity and highly integrated transducers is one of the main challenges in the development of high-throughput biosensors. The aim of this study is to improve the final sensitivity of an opto-mechanical device to be used as a reliable biosensor. We report the analysis of the mechanical and optical properties of optical waveguide microcantilever transducers, and their dependency on device design and dimensions. The selected layout (geometry) based on two butt-coupled misaligned waveguides displays better sensitivities than an aligned one. With this configuration, we find that an optimal microcantilever thickness range between 150 nm and 400 nm would increase both microcantilever bending during the biorecognition process and increase optical sensitivity to 4.8 × 10 −2 nm −1 , an order of magnitude higher than other similar opto-mechanical devices. Moreover, the analysis shows that a single mode behaviour of the propagating radiation is required to avoid modal interference that could misinterpret the readout signal. (paper)
Energy Technology Data Exchange (ETDEWEB)
Gerstl, S.A.W.
1980-01-01
SENSIT computes the sensitivity and uncertainty of a calculated integral response (such as a dose rate) due to input cross sections and their uncertainties. Sensitivity profiles are computed for neutron and gamma-ray reaction cross sections of standard multigroup cross section sets and for secondary energy distributions (SEDs) of multigroup scattering matrices. In the design sensitivity mode, SENSIT computes changes in an integral response due to design changes and gives the appropriate sensitivity coefficients. Cross section uncertainty analyses are performed for three types of input data uncertainties: cross-section covariance matrices for pairs of multigroup reaction cross sections, spectral shape uncertainty parameters for secondary energy distributions (integral SED uncertainties), and covariance matrices for energy-dependent response functions. For all three types of data uncertainties SENSIT computes the resulting variance and estimated standard deviation in an integral response of interest, on the basis of generalized perturbation theory. SENSIT attempts to be more comprehensive than earlier sensitivity analysis codes, such as SWANLAKE.
How the twain can meet: Prospect theory and models of heuristics in risky choice.
Pachur, Thorsten; Suter, Renata S; Hertwig, Ralph
2017-03-01
Two influential approaches to modeling choice between risky options are algebraic models (which focus on predicting the overt decisions) and models of heuristics (which are also concerned with capturing the underlying cognitive process). Because they rest on fundamentally different assumptions and algorithms, the two approaches are usually treated as antithetical, or even incommensurable. Drawing on cumulative prospect theory (CPT; Tversky & Kahneman, 1992) as the currently most influential instance of a descriptive algebraic model, we demonstrate how the two modeling traditions can be linked. CPT's algebraic functions characterize choices in terms of psychophysical (diminishing sensitivity to probabilities and outcomes) as well as psychological (risk aversion and loss aversion) constructs. Models of heuristics characterize choices as rooted in simple information-processing principles such as lexicographic and limited search. In computer simulations, we estimated CPT's parameters for choices produced by various heuristics. The resulting CPT parameter profiles portray each of the choice-generating heuristics in psychologically meaningful ways-capturing, for instance, differences in how the heuristics process probability information. Furthermore, CPT parameters can reflect a key property of many heuristics, lexicographic search, and track the environment-dependent behavior of heuristics. Finally, we show, both in an empirical and a model recovery study, how CPT parameter profiles can be used to detect the operation of heuristics. We also address the limits of CPT's ability to capture choices produced by heuristics. Our results highlight an untapped potential of CPT as a measurement tool to characterize the information processing underlying risky choice. Copyright © 2017 Elsevier Inc. All rights reserved.
Modeling reproductive decisions with simple heuristics
Directory of Open Access Journals (Sweden)
Peter Todd
2013-10-01
Full Text Available BACKGROUND Many of the reproductive decisions that humans make happen without much planning or forethought, arising instead through the use of simple choice rules or heuristics that involve relatively little information and processing. Nonetheless, these heuristic-guided decisions are typically beneficial, owing to humans' ecological rationality - the evolved fit between our constrained decision mechanisms and the adaptive problems we face. OBJECTIVE This paper reviews research on the ecological rationality of human decision making in the domain of reproduction, showing how fertility-related decisions are commonly made using various simple heuristics matched to the structure of the environment in which they are applied, rather than being made with information-hungry mechanisms based on optimization or rational economic choice. METHODS First, heuristics for sequential mate search are covered; these heuristics determine when to stop the process of mate search by deciding that a good-enough mate who is also mutually interested has been found, using a process of aspiration-level setting and assessing. These models are tested via computer simulation and comparison to demographic age-at-first-marriage data. Next, a heuristic process of feature-based mate comparison and choice is discussed, in which mate choices are determined by a simple process of feature-matching with relaxing standards over time. Parental investment heuristics used to divide resources among offspring are summarized. Finally, methods for testing the use of such mate choice heuristics in a specific population over time are then described.
Cooperative heuristic multi-agent planning
De Weerdt, M.M.; Tonino, J.F.M.; Witteveen, C.
2001-01-01
In this paper we will use the framework to study cooperative heuristic multi-agent planning. During the construction of their plans, the agents use a heuristic function inspired by the FF planner (l3l). At any time in the process of planning the agents may exchange available resources, or they may
"A Heuristic for Visual Thinking in History"
Staley, David J.
2007-01-01
This article details a heuristic history teachers can use in assigning and evaluating multimedia projects in history. To use this heuristic successfully, requires more than simply following the steps in the list or stages in a recipe: in many ways, it requires a reorientation in what it means to think like an historian. This article, as much as…
Effective Heuristics for New Venture Formation
Kraaijenbrink, Jeroen
2010-01-01
Entrepreneurs are often under time pressure and may only have a short window of opportunity to launch their new venture. This means they often have no time for rational analytical decisions and rather rely on heuristics. Past research on entrepreneurial heuristics has primarily focused on predictive
Religion, Heuristics, and Intergenerational Risk Management
Rupert Read; Nassim Nicholas Taleb
2014-01-01
Religions come with risk-managing interdicts and heuristics, and they carry such interdicts and heuristics across generations. We remark on such facets of religion in relation to a propensity among some decision scientists and others to regard practices that they cannot understand as being irrational, biased, and so on.
Least Squares Shadowing sensitivity analysis of chaotic limit cycle oscillations
Energy Technology Data Exchange (ETDEWEB)
Wang, Qiqi, E-mail: qiqi@mit.edu; Hu, Rui, E-mail: hurui@mit.edu; Blonigan, Patrick, E-mail: blonigan@mit.edu
2014-06-15
The adjoint method, among other sensitivity analysis methods, can fail in chaotic dynamical systems. The result from these methods can be too large, often by orders of magnitude, when the result is the derivative of a long time averaged quantity. This failure is known to be caused by ill-conditioned initial value problems. This paper overcomes this failure by replacing the initial value problem with the well-conditioned “least squares shadowing (LSS) problem”. The LSS problem is then linearized in our sensitivity analysis algorithm, which computes a derivative that converges to the derivative of the infinitely long time average. We demonstrate our algorithm in several dynamical systems exhibiting both periodic and chaotic oscillations.
Therapeutic Implications from Sensitivity Analysis of Tumor Angiogenesis Models
Poleszczuk, Jan; Hahnfeldt, Philip; Enderling, Heiko
2015-01-01
Anti-angiogenic cancer treatments induce tumor starvation and regression by targeting the tumor vasculature that delivers oxygen and nutrients. Mathematical models prove valuable tools to study the proof-of-concept, efficacy and underlying mechanisms of such treatment approaches. The effects of parameter value uncertainties for two models of tumor development under angiogenic signaling and anti-angiogenic treatment are studied. Data fitting is performed to compare predictions of both models and to obtain nominal parameter values for sensitivity analysis. Sensitivity analysis reveals that the success of different cancer treatments depends on tumor size and tumor intrinsic parameters. In particular, we show that tumors with ample vascular support can be successfully targeted with conventional cytotoxic treatments. On the other hand, tumors with curtailed vascular support are not limited by their growth rate and therefore interruption of neovascularization emerges as the most promising treatment target. PMID:25785600
Global sensitivity analysis of multiscale properties of porous materials
Um, Kimoon; Zhang, Xuan; Katsoulakis, Markos; Plechac, Petr; Tartakovsky, Daniel M.
2018-02-01
Ubiquitous uncertainty about pore geometry inevitably undermines the veracity of pore- and multi-scale simulations of transport phenomena in porous media. It raises two fundamental issues: sensitivity of effective material properties to pore-scale parameters and statistical parameterization of Darcy-scale models that accounts for pore-scale uncertainty. Homogenization-based maps of pore-scale parameters onto their Darcy-scale counterparts facilitate both sensitivity analysis (SA) and uncertainty quantification. We treat uncertain geometric characteristics of a hierarchical porous medium as random variables to conduct global SA and to derive probabilistic descriptors of effective diffusion coefficients and effective sorption rate. Our analysis is formulated in terms of solute transport diffusing through a fluid-filled pore space, while sorbing to the solid matrix. Yet it is sufficiently general to be applied to other multiscale porous media phenomena that are amenable to homogenization.
Sensitivity analysis overlaps of friction elements in cartridge seals
Directory of Open Access Journals (Sweden)
Žmindák Milan
2018-01-01
Full Text Available Cartridge seals are self-contained units consisting of a shaft sleeve, seals, and gland plate. The applications of mechanical seals are numerous. The most common example of application is in bearing production for automobile industry. This paper deals with the sensitivity analysis of overlaps friction elements in cartridge seal and their influence on the friction torque sealing and compressive force. Furthermore, it describes materials for the manufacture of sealings, approaches usually used to solution of hyperelastic materials by FEM and short introduction into the topic wheel bearings. The practical part contains one of the approach for measurement friction torque, which results were used to specifying the methodology and precision of FEM calculation realized by software ANSYS WORKBENCH. This part also contains the sensitivity analysis of overlaps friction elements.
An overview of the design and analysis of simulation experiments for sensitivity analysis
Kleijnen, J.P.C.
2005-01-01
Sensitivity analysis may serve validation, optimization, and risk analysis of simulation models. This review surveys 'classic' and 'modern' designs for experiments with simulation models. Classic designs were developed for real, non-simulated systems in agriculture, engineering, etc. These designs
Evaluating Heuristics for Planning Effective and Efficient Inspections
Shull, Forrest J.; Seaman, Carolyn B.; Diep, Madeline M.; Feldmann, Raimund L.; Godfrey, Sara H.; Regardie, Myrna
2010-01-01
A significant body of knowledge concerning software inspection practice indicates that the value of inspections varies widely both within and across organizations. Inspection effectiveness and efficiency can be measured in numerous ways, and may be affected by a variety of factors such as Inspection planning, the type of software, the developing organization, and many others. In the early 1990's, NASA formulated heuristics for inspection planning based on best practices and early NASA inspection data. Over the intervening years, the body of data from NASA inspections has grown. This paper describes a multi-faceted exploratory analysis performed on this · data to elicit lessons learned in general about conducting inspections and to recommend improvements to the existing heuristics. The contributions of our results include support for modifying some of the original inspection heuristics (e.g. Increasing the recommended page rate), evidence that Inspection planners must choose between efficiency and effectiveness, as a good tradeoff between them may not exist, and Identification of small subsets of inspections for which new inspection heuristics are needed. Most Importantly, this work illustrates the value of collecting rich data on software Inspections, and using it to gain insight into, and Improve, inspection practice.
Heuristic procedures for transmission planning in competitive electricity markets
International Nuclear Information System (INIS)
Lu, Wene; Bompard, Ettore; Napoli, Roberto; Jiang, Xiuchen
2007-01-01
The network structure of the power system, in an electricity market under the pool model, may have severe impacts on market performance, reducing market efficiency considerably, especially when producers bid strategically. In this context network re-enforcement plays a major role and proper strategies of transmission planning need to be devised. This paper presents, for pool-model electricity markets, two heuristic procedures to select the most effective subset of lines that would reduce the impacts on the market, from a set of predefined candidate lines and within the allowed budget for network expansion. A set of indices that account for the economic impacts of the re-enforcing of the candidate lines, both in terms of construction cost and market efficiency, are proposed and used as sensitivity indices in the heuristic procedure. The proposed methods are applied and compared with reference to an 18-bus test system. (author)
Probabilistic Sensitivities for Fatigue Analysis of Turbine Engine Disks
Harry R. Millwater; R. Wesley Osborn
2006-01-01
A methodology is developed and applied that determines the sensitivities of the probability-of-fracture of a gas turbine disk fatigue analysis with respect to the parameters of the probability distributions describing the random variables. The disk material is subject to initial anomalies, in either low- or high-frequency quantities, such that commonly used materials (titanium, nickel, powder nickel) and common damage mechanisms (inherent defects or su...
Influence analysis to assess sensitivity of the dropout process
Molenberghs, Geert; Verbeke, Geert; Thijs, Herbert; Lesaffre, Emmanuel; Kenward, Michael
2001-01-01
Diggle and Kenward (Appl. Statist. 43 (1994) 49) proposed a selection model for continuous longitudinal data subject to possible non-random dropout. It has provoked a large debate about the role for such models. The original enthusiasm was followed by skepticism about the strong but untestable assumption upon which this type of models invariably rests. Since then, the view has emerged that these models should ideally be made part of a sensitivity analysis. One of their examples is a set of da...
Synthesis, Characterization, and Sensitivity Analysis of Urea Nitrate (UN)
2015-04-01
determined. From the results of the study, UN is safe to store under normal operating conditions. 15. SUBJECT TERMS urea, nitrate , sensitivity, thermal ...HNO3). Due to its simple composition, ease of manufacture, and higher detonation parameters than ammonium nitrate , it has become one of the...an H50 value of 10.054 ± 0.620 inches. 5. Conclusions From the results of the thermal analysis study, it can be concluded that urea nitrate is
Applications of the TSUNAMI sensitivity and uncertainty analysis methodology
International Nuclear Information System (INIS)
Rearden, Bradley T.; Hopper, Calvin M.; Elam, Karla R.; Goluoglu, Sedat; Parks, Cecil V.
2003-01-01
The TSUNAMI sensitivity and uncertainty analysis tools under development for the SCALE code system have recently been applied in four criticality safety studies. TSUNAMI is used to identify applicable benchmark experiments for criticality code validation, assist in the design of new critical experiments for a particular need, reevaluate previously computed computational biases, and assess the validation coverage and propose a penalty for noncoverage for a specific application. (author)
Comparison of Heuristics for Inhibitory Rule Optimization
Alsolami, Fawaz; Chikalov, Igor; Moshkov, Mikhail
2014-01-01
Friedman test with Nemenyi post-hoc are used to compare the greedy algorithms statistically against each other for length and coverage. The experiments are carried out on real datasets from UCI Machine Learning Repository. For leading heuristics, the constructed rules are compared with optimal ones obtained based on dynamic programming approach. The results seem to be promising for the best heuristics: the average relative difference between length (coverage) of constructed and optimal rules is at most 2.27% (7%, respectively). Furthermore, the quality of classifiers based on sets of inhibitory rules constructed by the considered heuristics are compared against each other, and the results show that the three best heuristics from the point of view classification accuracy coincides with the three well-performed heuristics from the point of view of rule length minimization.
Interface Heuristics and Style Guide Design: An Air Battle Management Case Study
National Research Council Canada - National Science Library
Nelson, W. T; Bolia, Robert S
2005-01-01
.... An analysis of the content of extensive operator interviews from all relevant platforms preceded the production of a compact style guide based on a few simple heuristics and populated with wire frame...
Sensitivity Analysis of Launch Vehicle Debris Risk Model
Gee, Ken; Lawrence, Scott L.
2010-01-01
As part of an analysis of the loss of crew risk associated with an ascent abort system for a manned launch vehicle, a model was developed to predict the impact risk of the debris resulting from an explosion of the launch vehicle on the crew module. The model consisted of a debris catalog describing the number, size and imparted velocity of each piece of debris, a method to compute the trajectories of the debris and a method to calculate the impact risk given the abort trajectory of the crew module. The model provided a point estimate of the strike probability as a function of the debris catalog, the time of abort and the delay time between the abort and destruction of the launch vehicle. A study was conducted to determine the sensitivity of the strike probability to the various model input parameters and to develop a response surface model for use in the sensitivity analysis of the overall ascent abort risk model. The results of the sensitivity analysis and the response surface model are presented in this paper.
Global sensitivity analysis using a Gaussian Radial Basis Function metamodel
International Nuclear Information System (INIS)
Wu, Zeping; Wang, Donghui; Okolo N, Patrick; Hu, Fan; Zhang, Weihua
2016-01-01
Sensitivity analysis plays an important role in exploring the actual impact of adjustable parameters on response variables. Amongst the wide range of documented studies on sensitivity measures and analysis, Sobol' indices have received greater portion of attention due to the fact that they can provide accurate information for most models. In this paper, a novel analytical expression to compute the Sobol' indices is derived by introducing a method which uses the Gaussian Radial Basis Function to build metamodels of computationally expensive computer codes. Performance of the proposed method is validated against various analytical functions and also a structural simulation scenario. Results demonstrate that the proposed method is an efficient approach, requiring a computational cost of one to two orders of magnitude less when compared to the traditional Quasi Monte Carlo-based evaluation of Sobol' indices. - Highlights: • RBF based sensitivity analysis method is proposed. • Sobol' decomposition of Gaussian RBF metamodel is obtained. • Sobol' indices of Gaussian RBF metamodel are derived based on the decomposition. • The efficiency of proposed method is validated by some numerical examples.
Systemization of burnup sensitivity analysis code (2) (Contract research)
International Nuclear Information System (INIS)
Tatsumi, Masahiro; Hyoudou, Hideaki
2008-08-01
Towards the practical use of fast reactors, it is a very important subject to improve prediction accuracy for neutronic properties in LMFBR cores from the viewpoint of improvements on plant economic efficiency with rationally high performance cores and that on reliability and safety margins. A distinct improvement on accuracy in nuclear core design has been accomplished by the development of adjusted nuclear library using the cross-section adjustment method, in which the results of critical experiments of JUPITER and so on are reflected. In the design of large LMFBR cores, however, it is important to accurately estimate not only neutronic characteristics, for example, reaction rate distribution and control rod worth but also burnup characteristics, for example, burnup reactivity loss, breeding ratio and so on. For this purpose, it is desired to improve prediction accuracy of burnup characteristics using the data widely obtained in actual core such as the experimental fast reactor 'JOYO'. The analysis of burnup characteristic is needed to effectively use burnup characteristics data in the actual cores based on the cross-section adjustment method. So far, a burnup sensitivity analysis code, SAGEP-BURN, has been developed and confirmed its effectiveness. However, there is a problem that analysis sequence become inefficient because of a big burden to users due to complexity of the theory of burnup sensitivity and limitation of the system. It is also desired to rearrange the system for future revision since it is becoming difficult to implement new functions in the existing large system. It is not sufficient to unify each computational component for the following reasons: the computational sequence may be changed for each item being analyzed or for purpose such as interpretation of physical meaning. Therefore, it is needed to systemize the current code for burnup sensitivity analysis with component blocks of functionality that can be divided or constructed on occasion
Directory of Open Access Journals (Sweden)
Fanrong Kong
2017-09-01
Full Text Available To alleviate the emission of greenhouse gas and the dependence on fossil fuel, Plug-in Hybrid Electrical Vehicles (PHEVs have gained an increasing popularity in current decades. Due to the fluctuating electricity prices in the power market, a charging schedule is very influential to driving cost. Although the next-day electricity prices can be obtained in a day-ahead power market, a driving plan is not easily made in advance. Although PHEV owners can input a next-day plan into a charging system, e.g., aggregators, day-ahead, it is a very trivial task to do everyday. Moreover, the driving plan may not be very accurate. To address this problem, in this paper, we analyze energy demands according to a PHEV owner’s historical driving records and build a personalized statistic driving model. Based on the model and the electricity spot prices, a rolling optimization strategy is proposed to help make a charging decision in the current time slot. On one hand, by employing a heuristic algorithm, the schedule is made according to the situations in the following time slots. On the other hand, however, after the current time slot, the schedule will be remade according to the next tens of time slots. Hence, the schedule is made by a dynamic rolling optimization, but it only decides the charging decision in the current time slot. In this way, the fluctuation of electricity prices and driving routine are both involved in the scheduling. Moreover, it is not necessary for PHEV owners to input a day-ahead driving plan. By the optimization simulation, the results demonstrate that the proposed method is feasible to help owners save charging costs and also meet requirements for driving.
Sensitivity analysis in multiple imputation in effectiveness studies of psychotherapy.
Crameri, Aureliano; von Wyl, Agnes; Koemeda, Margit; Schulthess, Peter; Tschuschke, Volker
2015-01-01
The importance of preventing and treating incomplete data in effectiveness studies is nowadays emphasized. However, most of the publications focus on randomized clinical trials (RCT). One flexible technique for statistical inference with missing data is multiple imputation (MI). Since methods such as MI rely on the assumption of missing data being at random (MAR), a sensitivity analysis for testing the robustness against departures from this assumption is required. In this paper we present a sensitivity analysis technique based on posterior predictive checking, which takes into consideration the concept of clinical significance used in the evaluation of intra-individual changes. We demonstrate the possibilities this technique can offer with the example of irregular longitudinal data collected with the Outcome Questionnaire-45 (OQ-45) and the Helping Alliance Questionnaire (HAQ) in a sample of 260 outpatients. The sensitivity analysis can be used to (1) quantify the degree of bias introduced by missing not at random data (MNAR) in a worst reasonable case scenario, (2) compare the performance of different analysis methods for dealing with missing data, or (3) detect the influence of possible violations to the model assumptions (e.g., lack of normality). Moreover, our analysis showed that ratings from the patient's and therapist's version of the HAQ could significantly improve the predictive value of the routine outcome monitoring based on the OQ-45. Since analysis dropouts always occur, repeated measurements with the OQ-45 and the HAQ analyzed with MI are useful to improve the accuracy of outcome estimates in quality assurance assessments and non-randomized effectiveness studies in the field of outpatient psychotherapy.
B1 -sensitivity analysis of quantitative magnetization transfer imaging.
Boudreau, Mathieu; Stikov, Nikola; Pike, G Bruce
2018-01-01
To evaluate the sensitivity of quantitative magnetization transfer (qMT) fitted parameters to B 1 inaccuracies, focusing on the difference between two categories of T 1 mapping techniques: B 1 -independent and B 1 -dependent. The B 1 -sensitivity of qMT was investigated and compared using two T 1 measurement methods: inversion recovery (IR) (B 1 -independent) and variable flip angle (VFA), B 1 -dependent). The study was separated into four stages: 1) numerical simulations, 2) sensitivity analysis of the Z-spectra, 3) healthy subjects at 3T, and 4) comparison using three different B 1 imaging techniques. For typical B 1 variations in the brain at 3T (±30%), the simulations resulted in errors of the pool-size ratio (F) ranging from -3% to 7% for VFA, and -40% to > 100% for IR, agreeing with the Z-spectra sensitivity analysis. In healthy subjects, pooled whole-brain Pearson correlation coefficients for F (comparing measured double angle and nominal flip angle B 1 maps) were ρ = 0.97/0.81 for VFA/IR. This work describes the B 1 -sensitivity characteristics of qMT, demonstrating that it varies substantially on the B 1 -dependency of the T 1 mapping method. Particularly, the pool-size ratio is more robust against B 1 inaccuracies if VFA T 1 mapping is used, so much so that B 1 mapping could be omitted without substantially biasing F. Magn Reson Med 79:276-285, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.
Probability and sensitivity analysis of machine foundation and soil interaction
Directory of Open Access Journals (Sweden)
Králik J., jr.
2009-06-01
Full Text Available This paper deals with the possibility of the sensitivity and probabilistic analysis of the reliability of the machine foundation depending on variability of the soil stiffness, structure geometry and compressor operation. The requirements to design of the foundation under rotating machines increased due to development of calculation method and computer tools. During the structural design process, an engineer has to consider problems of the soil-foundation and foundation-machine interaction from the safety, reliability and durability of structure point of view. The advantages and disadvantages of the deterministic and probabilistic analysis of the machine foundation resistance are discussed. The sensitivity of the machine foundation to the uncertainties of the soil properties due to longtime rotating movement of machine is not negligible for design engineers. On the example of compressor foundation and turbine fy. SIEMENS AG the affectivity of the probabilistic design methodology was presented. The Latin Hypercube Sampling (LHS simulation method for the analysis of the compressor foundation reliability was used on program ANSYS. The 200 simulations for five load cases were calculated in the real time on PC. The probabilistic analysis gives us more complex information about the soil-foundation-machine interaction as the deterministic analysis.
Global Sensitivity Analysis for multivariate output using Polynomial Chaos Expansion
International Nuclear Information System (INIS)
Garcia-Cabrejo, Oscar; Valocchi, Albert
2014-01-01
Many mathematical and computational models used in engineering produce multivariate output that shows some degree of correlation. However, conventional approaches to Global Sensitivity Analysis (GSA) assume that the output variable is scalar. These approaches are applied on each output variable leading to a large number of sensitivity indices that shows a high degree of redundancy making the interpretation of the results difficult. Two approaches have been proposed for GSA in the case of multivariate output: output decomposition approach [9] and covariance decomposition approach [14] but they are computationally intensive for most practical problems. In this paper, Polynomial Chaos Expansion (PCE) is used for an efficient GSA with multivariate output. The results indicate that PCE allows efficient estimation of the covariance matrix and GSA on the coefficients in the approach defined by Campbell et al. [9], and the development of analytical expressions for the multivariate sensitivity indices defined by Gamboa et al. [14]. - Highlights: • PCE increases computational efficiency in 2 approaches of GSA of multivariate output. • Efficient estimation of covariance matrix of output from coefficients of PCE. • Efficient GSA on coefficients of orthogonal decomposition of the output using PCE. • Analytical expressions of multivariate sensitivity indices from coefficients of PCE
Parametric Sensitivity Analysis of the WAVEWATCH III Model
Directory of Open Access Journals (Sweden)
Beng-Chun Lee
2009-01-01
Full Text Available The parameters in numerical wave models need to be calibrated be fore a model can be applied to a specific region. In this study, we selected the 8 most important parameters from the source term of the WAVEWATCH III model and subjected them to sensitivity analysis to evaluate the sensitivity of the WAVEWATCH III model to the selected parameters to determine how many of these parameters should be considered for further discussion, and to justify the significance priority of each parameter. After ranking each parameter by sensitivity and assessing their cumulative impact, we adopted the ARS method to search for the optimal values of those parameters to which the WAVEWATCH III model is most sensitive by comparing modeling results with ob served data at two data buoys off the coast of north eastern Taiwan; the goal being to find optimal parameter values for improved modeling of wave development. The procedure adopting optimal parameters in wave simulations did improve the accuracy of the WAVEWATCH III model in comparison to default runs based on field observations at two buoys.
ADGEN: a system for automated sensitivity analysis of predictive models
International Nuclear Information System (INIS)
Pin, F.G.; Horwedel, J.E.; Oblow, E.M.; Lucius, J.L.
1987-01-01
A system that can automatically enhance computer codes with a sensitivity calculation capability is presented. With this new system, named ADGEN, rapid and cost-effective calculation of sensitivities can be performed in any FORTRAN code for all input data or parameters. The resulting sensitivities can be used in performance assessment studies related to licensing or interactions with the public to systematically and quantitatively prove the relative importance of each of the system parameters in calculating the final performance results. A general procedure calling for the systematic use of sensitivities in assessment studies is presented. The procedure can be used in modeling and model validation studies to avoid over modeling, in site characterization planning to avoid over collection of data, and in performance assessments to determine the uncertainties on the final calculated results. The added capability to formally perform the inverse problem, i.e., to determine the input data or parameters on which to focus to determine the input data or parameters on which to focus additional research or analysis effort in order to improve the uncertainty of the final results, is also discussed. 7 references, 2 figures
ADGEN: a system for automated sensitivity analysis of predictive models
International Nuclear Information System (INIS)
Pin, F.G.; Horwedel, J.E.; Oblow, E.M.; Lucius, J.L.
1986-09-01
A system that can automatically enhance computer codes with a sensitivity calculation capability is presented. With this new system, named ADGEN, rapid and cost-effective calculation of sensitivities can be performed in any FORTRAN code for all input data or parameters. The resulting sensitivities can be used in performance assessment studies related to licensing or interactions with the public to systematically and quantitatively prove the relative importance of each of the system parameters in calculating the final performance results. A general procedure calling for the systematic use of sensitivities in assessment studies is presented. The procedure can be used in modelling and model validation studies to avoid ''over modelling,'' in site characterization planning to avoid ''over collection of data,'' and in performance assessment to determine the uncertainties on the final calculated results. The added capability to formally perform the inverse problem, i.e., to determine the input data or parameters on which to focus additional research or analysis effort in order to improve the uncertainty of the final results, is also discussed
Sensitivity analysis: Interaction of DOE SNF and packaging materials
International Nuclear Information System (INIS)
Anderson, P.A.; Kirkham, R.J.; Shaber, E.L.
1999-01-01
A sensitivity analysis was conducted to evaluate the technical issues pertaining to possible destructive interactions between spent nuclear fuels (SNFs) and the stainless steel canisters. When issues are identified through such an analysis, they provide the technical basis for answering what if questions and, if needed, for conducting additional analyses, testing, or other efforts to resolve them in order to base the licensing on solid technical grounds. The analysis reported herein systematically assessed the chemical and physical properties and the potential interactions of the materials that comprise typical US Department of Energy (DOE) SNFs and the stainless steel canisters in which they will be stored, transported, and placed in a geologic repository for final disposition. The primary focus in each step of the analysis was to identify any possible phenomena that could potentially compromise the structural integrity of the canisters and to assess their thermodynamic feasibility
Heuristic Strategies in Systems Biology
Directory of Open Access Journals (Sweden)
Fridolin Gross
2016-06-01
Full Text Available Systems biology is sometimes presented as providing a superior approach to the problem of biological complexity. Its use of ‘unbiased’ methods and formal quantitative tools might lead to the impression that the human factor is effectively eliminated. However, a closer look reveals that this impression is misguided. Systems biologists cannot simply assemble molecular information and compute biological behavior. Instead, systems biology’s main contribution is to accelerate the discovery of mechanisms by applying models as heuristic tools. These models rely on a variety of idealizing and simplifying assumptions in order to be efficient for this purpose. The strategies of systems biologists are similar to those of experimentalists in that they attempt to reduce the complexity of the discovery process. Analyzing and comparing these strategies, or ‘heuristics’, reveals the importance of the human factor in computational approaches and helps to situate systems biology within the epistemic landscape of the life sciences.
Heuristic approach to train rescheduling
Directory of Open Access Journals (Sweden)
Mladenović Snežana
2007-01-01
Full Text Available Starting from the defined network topology and the timetable assigned beforehand, the paper considers a train rescheduling in respond to disturbances that have occurred. Assuming that the train trips are jobs, which require the elements of infrastructure - resources, it was done by the mapping of the initial problem into a special case of job shop scheduling problem. In order to solve the given problem, a constraint programming approach has been used. A support to fast finding "enough good" schedules is offered by original separation, bound and search heuristic algorithms. In addition, to improve the time performance, instead of the actual objective function with a large domain, a surrogate objective function is used with a smaller domain, if there is such. .
Linear regression and sensitivity analysis in nuclear reactor design
International Nuclear Information System (INIS)
Kumar, Akansha; Tsvetkov, Pavel V.; McClarren, Ryan G.
2015-01-01
Highlights: • Presented a benchmark for the applicability of linear regression to complex systems. • Applied linear regression to a nuclear reactor power system. • Performed neutronics, thermal–hydraulics, and energy conversion using Brayton’s cycle for the design of a GCFBR. • Performed detailed sensitivity analysis to a set of parameters in a nuclear reactor power system. • Modeled and developed reactor design using MCNP, regression using R, and thermal–hydraulics in Java. - Abstract: The paper presents a general strategy applicable for sensitivity analysis (SA), and uncertainity quantification analysis (UA) of parameters related to a nuclear reactor design. This work also validates the use of linear regression (LR) for predictive analysis in a nuclear reactor design. The analysis helps to determine the parameters on which a LR model can be fit for predictive analysis. For those parameters, a regression surface is created based on trial data and predictions are made using this surface. A general strategy of SA to determine and identify the influential parameters those affect the operation of the reactor is mentioned. Identification of design parameters and validation of linearity assumption for the application of LR of reactor design based on a set of tests is performed. The testing methods used to determine the behavior of the parameters can be used as a general strategy for UA, and SA of nuclear reactor models, and thermal hydraulics calculations. A design of a gas cooled fast breeder reactor (GCFBR), with thermal–hydraulics, and energy transfer has been used for the demonstration of this method. MCNP6 is used to simulate the GCFBR design, and perform the necessary criticality calculations. Java is used to build and run input samples, and to extract data from the output files of MCNP6, and R is used to perform regression analysis and other multivariate variance, and analysis of the collinearity of data
Mixed kernel function support vector regression for global sensitivity analysis
Cheng, Kai; Lu, Zhenzhou; Wei, Yuhao; Shi, Yan; Zhou, Yicheng
2017-11-01
Global sensitivity analysis (GSA) plays an important role in exploring the respective effects of input variables on an assigned output response. Amongst the wide sensitivity analyses in literature, the Sobol indices have attracted much attention since they can provide accurate information for most models. In this paper, a mixed kernel function (MKF) based support vector regression (SVR) model is employed to evaluate the Sobol indices at low computational cost. By the proposed derivation, the estimation of the Sobol indices can be obtained by post-processing the coefficients of the SVR meta-model. The MKF is constituted by the orthogonal polynomials kernel function and Gaussian radial basis kernel function, thus the MKF possesses both the global characteristic advantage of the polynomials kernel function and the local characteristic advantage of the Gaussian radial basis kernel function. The proposed approach is suitable for high-dimensional and non-linear problems. Performance of the proposed approach is validated by various analytical functions and compared with the popular polynomial chaos expansion (PCE). Results demonstrate that the proposed approach is an efficient method for global sensitivity analysis.
Optimizing human activity patterns using global sensitivity analysis.
Fairchild, Geoffrey; Hickmann, Kyle S; Mniszewski, Susan M; Del Valle, Sara Y; Hyman, James M
2014-12-01
Implementing realistic activity patterns for a population is crucial for modeling, for example, disease spread, supply and demand, and disaster response. Using the dynamic activity simulation engine, DASim, we generate schedules for a population that capture regular (e.g., working, eating, and sleeping) and irregular activities (e.g., shopping or going to the doctor). We use the sample entropy (SampEn) statistic to quantify a schedule's regularity for a population. We show how to tune an activity's regularity by adjusting SampEn, thereby making it possible to realistically design activities when creating a schedule. The tuning process sets up a computationally intractable high-dimensional optimization problem. To reduce the computational demand, we use Bayesian Gaussian process regression to compute global sensitivity indices and identify the parameters that have the greatest effect on the variance of SampEn. We use the harmony search (HS) global optimization algorithm to locate global optima. Our results show that HS combined with global sensitivity analysis can efficiently tune the SampEn statistic with few search iterations. We demonstrate how global sensitivity analysis can guide statistical emulation and global optimization algorithms to efficiently tune activities and generate realistic activity patterns. Though our tuning methods are applied to dynamic activity schedule generation, they are general and represent a significant step in the direction of automated tuning and optimization of high-dimensional computer simulations.
Social biases determine spatiotemporal sparseness of ciliate mating heuristics.
Clark, Kevin B
2012-01-01
Ciliates become highly social, even displaying animal-like qualities, in the joint presence of aroused conspecifics and nonself mating pheromones. Pheromone detection putatively helps trigger instinctual and learned courtship and dominance displays from which social judgments are made about the availability, compatibility, and fitness representativeness or likelihood of prospective mates and rivals. In earlier studies, I demonstrated the heterotrich Spirostomum ambiguum improves mating competence by effecting preconjugal strategies and inferences in mock social trials via behavioral heuristics built from Hebbian-like associative learning. Heuristics embody serial patterns of socially relevant action that evolve into ordered, topologically invariant computational networks supporting intra- and intermate selection. S. ambiguum employs heuristics to acquire, store, plan, compare, modify, select, and execute sets of mating propaganda. One major adaptive constraint over formation and use of heuristics involves a ciliate's initial subjective bias, responsiveness, or preparedness, as defined by Stevens' Law of subjective stimulus intensity, for perceiving the meaningfulness of mechanical pressures accompanying cell-cell contacts and additional perimating events. This bias controls durations and valences of nonassociative learning, search rates for appropriate mating strategies, potential net reproductive payoffs, levels of social honesty and deception, successful error diagnosis and correction of mating signals, use of insight or analysis to solve mating dilemmas, bioenergetics expenditures, and governance of mating decisions by classical or quantum statistical mechanics. I now report this same social bias also differentially affects the spatiotemporal sparseness, as measured with metric entropy, of ciliate heuristics. Sparseness plays an important role in neural systems through optimizing the specificity, efficiency, and capacity of memory representations. The present
Social biases determine spatiotemporal sparseness of ciliate mating heuristics
2012-01-01
Ciliates become highly social, even displaying animal-like qualities, in the joint presence of aroused conspecifics and nonself mating pheromones. Pheromone detection putatively helps trigger instinctual and learned courtship and dominance displays from which social judgments are made about the availability, compatibility, and fitness representativeness or likelihood of prospective mates and rivals. In earlier studies, I demonstrated the heterotrich Spirostomum ambiguum improves mating competence by effecting preconjugal strategies and inferences in mock social trials via behavioral heuristics built from Hebbian-like associative learning. Heuristics embody serial patterns of socially relevant action that evolve into ordered, topologically invariant computational networks supporting intra- and intermate selection. S. ambiguum employs heuristics to acquire, store, plan, compare, modify, select, and execute sets of mating propaganda. One major adaptive constraint over formation and use of heuristics involves a ciliate’s initial subjective bias, responsiveness, or preparedness, as defined by Stevens’ Law of subjective stimulus intensity, for perceiving the meaningfulness of mechanical pressures accompanying cell-cell contacts and additional perimating events. This bias controls durations and valences of nonassociative learning, search rates for appropriate mating strategies, potential net reproductive payoffs, levels of social honesty and deception, successful error diagnosis and correction of mating signals, use of insight or analysis to solve mating dilemmas, bioenergetics expenditures, and governance of mating decisions by classical or quantum statistical mechanics. I now report this same social bias also differentially affects the spatiotemporal sparseness, as measured with metric entropy, of ciliate heuristics. Sparseness plays an important role in neural systems through optimizing the specificity, efficiency, and capacity of memory representations. The
Sensitivity analysis practices: Strategies for model-based inference
International Nuclear Information System (INIS)
Saltelli, Andrea; Ratto, Marco; Tarantola, Stefano; Campolongo, Francesca
2006-01-01
Fourteen years after Science's review of sensitivity analysis (SA) methods in 1989 (System analysis at molecular scale, by H. Rabitz) we search Science Online to identify and then review all recent articles having 'sensitivity analysis' as a keyword. In spite of the considerable developments which have taken place in this discipline, of the good practices which have emerged, and of existing guidelines for SA issued on both sides of the Atlantic, we could not find in our review other than very primitive SA tools, based on 'one-factor-at-a-time' (OAT) approaches. In the context of model corroboration or falsification, we demonstrate that this use of OAT methods is illicit and unjustified, unless the model under analysis is proved to be linear. We show that available good practices, such as variance based measures and others, are able to overcome OAT shortcomings and easy to implement. These methods also allow the concept of factors importance to be defined rigorously, thus making the factors importance ranking univocal. We analyse the requirements of SA in the context of modelling, and present best available practices on the basis of an elementary model. We also point the reader to available recipes for a rigorous SA
Sensitivity analysis practices: Strategies for model-based inference
Energy Technology Data Exchange (ETDEWEB)
Saltelli, Andrea [Institute for the Protection and Security of the Citizen (IPSC), European Commission, Joint Research Centre, TP 361, 21020 Ispra (Vatican City State, Holy See,) (Italy)]. E-mail: andrea.saltelli@jrc.it; Ratto, Marco [Institute for the Protection and Security of the Citizen (IPSC), European Commission, Joint Research Centre, TP 361, 21020 Ispra (VA) (Italy); Tarantola, Stefano [Institute for the Protection and Security of the Citizen (IPSC), European Commission, Joint Research Centre, TP 361, 21020 Ispra (VA) (Italy); Campolongo, Francesca [Institute for the Protection and Security of the Citizen (IPSC), European Commission, Joint Research Centre, TP 361, 21020 Ispra (VA) (Italy)
2006-10-15
Fourteen years after Science's review of sensitivity analysis (SA) methods in 1989 (System analysis at molecular scale, by H. Rabitz) we search Science Online to identify and then review all recent articles having 'sensitivity analysis' as a keyword. In spite of the considerable developments which have taken place in this discipline, of the good practices which have emerged, and of existing guidelines for SA issued on both sides of the Atlantic, we could not find in our review other than very primitive SA tools, based on 'one-factor-at-a-time' (OAT) approaches. In the context of model corroboration or falsification, we demonstrate that this use of OAT methods is illicit and unjustified, unless the model under analysis is proved to be linear. We show that available good practices, such as variance based measures and others, are able to overcome OAT shortcomings and easy to implement. These methods also allow the concept of factors importance to be defined rigorously, thus making the factors importance ranking univocal. We analyse the requirements of SA in the context of modelling, and present best available practices on the basis of an elementary model. We also point the reader to available recipes for a rigorous SA.
Regional and parametric sensitivity analysis of Sobol' indices
International Nuclear Information System (INIS)
Wei, Pengfei; Lu, Zhenzhou; Song, Jingwen
2015-01-01
Nowadays, utilizing the Monte Carlo estimators for variance-based sensitivity analysis has gained sufficient popularity in many research fields. These estimators are usually based on n+2 sample matrices well designed for computing both the main and total effect indices, where n is the input dimension. The aim of this paper is to use such n+2 sample matrices to investigate how the main and total effect indices change when the uncertainty of the model inputs are reduced. For this purpose, the regional main and total effect functions are defined for measuring the changes on the main and total effect indices when the distribution range of one input is reduced, and the parametric main and total effect functions are introduced to quantify the residual main and total effect indices due to the reduced variance of one input. Monte Carlo estimators are derived for all the developed sensitivity concepts based on the n+2 samples matrices originally used for computing the main and total effect indices, thus no extra computational cost is introduced. The Ishigami function, a nonlinear model and a planar ten-bar structure are utilized for illustrating the developed sensitivity concepts, and for demonstrating the efficiency and accuracy of the derived Monte Carlo estimators. - Highlights: • The regional main and total effect functions are developed. • The parametric main and total effect functions are introduced. • The proposed sensitivity functions are all generalizations of Sobol' indices. • The Monte Carlo estimators are derived for the four sensitivity functions. • The computational cost of the estimators is the same as that of Sobol' indices
A sensitivity analysis of regional and small watershed hydrologic models
Ambaruch, R.; Salomonson, V. V.; Simmons, J. W.
1975-01-01
Continuous simulation models of the hydrologic behavior of watersheds are important tools in several practical applications such as hydroelectric power planning, navigation, and flood control. Several recent studies have addressed the feasibility of using remote earth observations as sources of input data for hydrologic models. The objective of the study reported here was to determine how accurately remotely sensed measurements must be to provide inputs to hydrologic models of watersheds, within the tolerances needed for acceptably accurate synthesis of streamflow by the models. The study objective was achieved by performing a series of sensitivity analyses using continuous simulation models of three watersheds. The sensitivity analysis showed quantitatively how variations in each of 46 model inputs and parameters affect simulation accuracy with respect to five different performance indices.
Stochastic sensitivity analysis and Langevin simulation for neural network learning
International Nuclear Information System (INIS)
Koda, Masato
1997-01-01
A comprehensive theoretical framework is proposed for the learning of a class of gradient-type neural networks with an additive Gaussian white noise process. The study is based on stochastic sensitivity analysis techniques, and formal expressions are obtained for stochastic learning laws in terms of functional derivative sensitivity coefficients. The present method, based on Langevin simulation techniques, uses only the internal states of the network and ubiquitous noise to compute the learning information inherent in the stochastic correlation between noise signals and the performance functional. In particular, the method does not require the solution of adjoint equations of the back-propagation type. Thus, the present algorithm has the potential for efficiently learning network weights with significantly fewer computations. Application to an unfolded multi-layered network is described, and the results are compared with those obtained by using a back-propagation method
An easily implemented static condensation method for structural sensitivity analysis
Gangadharan, S. N.; Haftka, R. T.; Nikolaidis, E.
1990-01-01
A black-box approach to static condensation for sensitivity analysis is presented with illustrative examples of a cube and a car structure. The sensitivity of the structural response with respect to joint stiffness parameter is calculated using the direct method, forward-difference, and central-difference schemes. The efficiency of the various methods for identifying joint stiffness parameters from measured static deflections of these structures is compared. The results indicate that the use of static condensation can reduce computation times significantly and the black-box approach is only slightly less efficient than the standard implementation of static condensation. The ease of implementation of the black-box approach recommends it for use with general-purpose finite element codes that do not have a built-in facility for static condensation.
Nuclear data sensitivity/uncertainty analysis for XT-ADS
International Nuclear Information System (INIS)
Sugawara, Takanori; Sarotto, Massimo; Stankovskiy, Alexey; Van den Eynde, Gert
2011-01-01
Highlights: → The sensitivity and uncertainty analyses were performed to comprehend the reliability of the XT-ADS neutronic design. → The uncertainties deduced from the covariance data for the XT-ADS criticality were 0.94%, 1.9% and 1.1% by the SCALE 44-group, TENDL-2009 and JENDL-3.3 data, respectively. → When the target accuracy of 0.3%Δk for the criticality was considered, the uncertainties did not satisfy it. → To achieve this accuracy, the uncertainties should be improved by experiments under an adequate condition. - Abstract: The XT-ADS, an accelerator-driven system for an experimental demonstration, has been investigated in the framework of IP EUROTRANS FP6 project. In this study, the sensitivity and uncertainty analyses were performed to comprehend the reliability of the XT-ADS neutronic design. For the sensitivity analysis, it was found that the sensitivity coefficients were significantly different by changing the geometry models and calculation codes. For the uncertainty analysis, it was confirmed that the uncertainties deduced from the covariance data varied significantly by changing them. The uncertainties deduced from the covariance data for the XT-ADS criticality were 0.94%, 1.9% and 1.1% by the SCALE 44-group, TENDL-2009 and JENDL-3.3 data, respectively. When the target accuracy of 0.3%Δk for the criticality was considered, the uncertainties did not satisfy it. To achieve this accuracy, the uncertainties should be improved by experiments under an adequate condition.
Uncertainty and sensitivity analysis of the nuclear fuel thermal behavior
Energy Technology Data Exchange (ETDEWEB)
Boulore, A., E-mail: antoine.boulore@cea.fr [Commissariat a l' Energie Atomique (CEA), DEN, Fuel Research Department, 13108 Saint-Paul-lez-Durance (France); Struzik, C. [Commissariat a l' Energie Atomique (CEA), DEN, Fuel Research Department, 13108 Saint-Paul-lez-Durance (France); Gaudier, F. [Commissariat a l' Energie Atomique (CEA), DEN, Systems and Structure Modeling Department, 91191 Gif-sur-Yvette (France)
2012-12-15
Highlights: Black-Right-Pointing-Pointer A complete quantitative method for uncertainty propagation and sensitivity analysis is applied. Black-Right-Pointing-Pointer The thermal conductivity of UO{sub 2} is modeled as a random variable. Black-Right-Pointing-Pointer The first source of uncertainty is the linear heat rate. Black-Right-Pointing-Pointer The second source of uncertainty is the thermal conductivity of the fuel. - Abstract: In the global framework of nuclear fuel behavior simulation, the response of the models describing the physical phenomena occurring during the irradiation in reactor is mainly conditioned by the confidence in the calculated temperature of the fuel. Amongst all parameters influencing the temperature calculation in our fuel rod simulation code (METEOR V2), several sources of uncertainty have been identified as being the most sensitive: thermal conductivity of UO{sub 2}, radial distribution of power in the fuel pellet, local linear heat rate in the fuel rod, geometry of the pellet and thermal transfer in the gap. Expert judgment and inverse methods have been used to model the uncertainty of these parameters using theoretical distributions and correlation matrices. Propagation of these uncertainties in the METEOR V2 code using the URANIE framework and a Monte-Carlo technique has been performed in different experimental irradiations of UO{sub 2} fuel. At every time step of the simulated experiments, we get a temperature statistical distribution which results from the initial distributions of the uncertain parameters. We then can estimate confidence intervals of the calculated temperature. In order to quantify the sensitivity of the calculated temperature to each of the uncertain input parameters and data, we have also performed a sensitivity analysis using the Sobol' indices at first order.
Automatic Generation of Heuristics for Scheduling
Morris, Robert A.; Bresina, John L.; Rodgers, Stuart M.
1997-01-01
This paper presents a technique, called GenH, that automatically generates search heuristics for scheduling problems. The impetus for developing this technique is the growing consensus that heuristics encode advice that is, at best, useful in solving most, or typical, problem instances, and, at worst, useful in solving only a narrowly defined set of instances. In either case, heuristic problem solvers, to be broadly applicable, should have a means of automatically adjusting to the idiosyncrasies of each problem instance. GenH generates a search heuristic for a given problem instance by hill-climbing in the space of possible multi-attribute heuristics, where the evaluation of a candidate heuristic is based on the quality of the solution found under its guidance. We present empirical results obtained by applying GenH to the real world problem of telescope observation scheduling. These results demonstrate that GenH is a simple and effective way of improving the performance of an heuristic scheduler.
Comparison of Heuristics for Inhibitory Rule Optimization
Alsolami, Fawaz
2014-09-13
Knowledge representation and extraction are very important tasks in data mining. In this work, we proposed a variety of rule-based greedy algorithms that able to obtain knowledge contained in a given dataset as a series of inhibitory rules containing an expression “attribute ≠ value” on the right-hand side. The main goal of this paper is to determine based on rule characteristics, rule length and coverage, whether the proposed rule heuristics are statistically significantly different or not; if so, we aim to identify the best performing rule heuristics for minimization of rule length and maximization of rule coverage. Friedman test with Nemenyi post-hoc are used to compare the greedy algorithms statistically against each other for length and coverage. The experiments are carried out on real datasets from UCI Machine Learning Repository. For leading heuristics, the constructed rules are compared with optimal ones obtained based on dynamic programming approach. The results seem to be promising for the best heuristics: the average relative difference between length (coverage) of constructed and optimal rules is at most 2.27% (7%, respectively). Furthermore, the quality of classifiers based on sets of inhibitory rules constructed by the considered heuristics are compared against each other, and the results show that the three best heuristics from the point of view classification accuracy coincides with the three well-performed heuristics from the point of view of rule length minimization.
A comparative study of the A* heuristic search algorithm used to solve efficiently a puzzle game
Iordan, A. E.
2018-01-01
The puzzle game presented in this paper consists in polyhedra (prisms, pyramids or pyramidal frustums) which can be moved using the free available spaces. The problem requires to be found the minimum number of movements in order the game reaches to a goal configuration starting from an initial configuration. Because the problem is enough complex, the principal difficulty in solving it is given by dimension of search space, that leads to necessity of a heuristic search. The improving of the search method consists into determination of a strong estimation by the heuristic function which will guide the search process to the most promising side of the search tree. The comparative study is realized among Manhattan heuristic and the Hamming heuristic using A* search algorithm implemented in Java. This paper also presents the necessary stages in object oriented development of a software used to solve efficiently this puzzle game. The modelling of the software is achieved through specific UML diagrams representing the phases of analysis, design and implementation, the system thus being described in a clear and practical manner. With the purpose to confirm the theoretical results which demonstrates that Manhattan heuristic is more efficient was used space complexity criterion. The space complexity was measured by the number of generated nodes from the search tree, by the number of the expanded nodes and by the effective branching factor. From the experimental results obtained by using the Manhattan heuristic, improvements were observed regarding space complexity of A* algorithm versus Hamming heuristic.
Perceived breast cancer risk: heuristic reasoning and search for a dominance structure.
Katapodi, Maria C; Facione, Noreen C; Humphreys, Janice C; Dodd, Marylin J
2005-01-01
Studies suggest that people construct their risk perceptions by using inferential rules called heuristics. The purpose of this study was to identify heuristics that influence perceived breast cancer risk. We examined 11 interviews from women of diverse ethnic/cultural backgrounds who were recruited from community settings. Narratives in which women elaborated about their own breast cancer risk were analyzed with Argument and Heuristic Reasoning Analysis methodology, which is based on applied logic. The availability, simulation, representativeness, affect, and perceived control heuristics, and search for a dominance structure were commonly used for making risk assessments. Risk assessments were based on experiences with an abnormal breast symptom, experiences with affected family members and friends, beliefs about living a healthy lifestyle, and trust in health providers. Assessment of the potential threat of a breast symptom was facilitated by the search for a dominance structure. Experiences with family members and friends were incorporated into risk assessments through the availability, simulation, representativeness, and affect heuristics. Mistrust in health providers led to an inappropriate dependence on the perceived control heuristic. Identified heuristics appear to create predictable biases and suggest that perceived breast cancer risk is based on common cognitive patterns.
A Hyper-Heuristic Ensemble Method for Static Job-Shop Scheduling.
Hart, Emma; Sim, Kevin
2016-01-01
We describe a new hyper-heuristic method NELLI-GP for solving job-shop scheduling problems (JSSP) that evolves an ensemble of heuristics. The ensemble adopts a divide-and-conquer approach in which each heuristic solves a unique subset of the instance set considered. NELLI-GP extends an existing ensemble method called NELLI by introducing a novel heuristic generator that evolves heuristics composed of linear sequences of dispatching rules: each rule is represented using a tree structure and is itself evolved. Following a training period, the ensemble is shown to outperform both existing dispatching rules and a standard genetic programming algorithm on a large set of new test instances. In addition, it obtains superior results on a set of 210 benchmark problems from the literature when compared to two state-of-the-art hyper-heuristic approaches. Further analysis of the relationship between heuristics in the evolved ensemble and the instances each solves provides new insights into features that might describe similar instances.
Biosphere dose conversion Factor Importance and Sensitivity Analysis
International Nuclear Information System (INIS)
M. Wasiolek
2004-01-01
This report presents importance and sensitivity analysis for the environmental radiation model for Yucca Mountain, Nevada (ERMYN). ERMYN is a biosphere model supporting the total system performance assessment (TSPA) for the license application (LA) for the Yucca Mountain repository. This analysis concerns the output of the model, biosphere dose conversion factors (BDCFs) for the groundwater, and the volcanic ash exposure scenarios. It identifies important processes and parameters that influence the BDCF values and distributions, enhances understanding of the relative importance of the physical and environmental processes on the outcome of the biosphere model, includes a detailed pathway analysis for key radionuclides, and evaluates the appropriateness of selected parameter values that are not site-specific or have large uncertainty
A framework for sensitivity analysis of decision trees.
Kamiński, Bogumił; Jakubczyk, Michał; Szufel, Przemysław
2018-01-01
In the paper, we consider sequential decision problems with uncertainty, represented as decision trees. Sensitivity analysis is always a crucial element of decision making and in decision trees it often focuses on probabilities. In the stochastic model considered, the user often has only limited information about the true values of probabilities. We develop a framework for performing sensitivity analysis of optimal strategies accounting for this distributional uncertainty. We design this robust optimization approach in an intuitive and not overly technical way, to make it simple to apply in daily managerial practice. The proposed framework allows for (1) analysis of the stability of the expected-value-maximizing strategy and (2) identification of strategies which are robust with respect to pessimistic/optimistic/mode-favoring perturbations of probabilities. We verify the properties of our approach in two cases: (a) probabilities in a tree are the primitives of the model and can be modified independently; (b) probabilities in a tree reflect some underlying, structural probabilities, and are interrelated. We provide a free software tool implementing the methods described.
Sensitivity Analysis of OECD Benchmark Tests in BISON
Energy Technology Data Exchange (ETDEWEB)
Swiler, Laura Painton [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Gamble, Kyle [Idaho National Lab. (INL), Idaho Falls, ID (United States); Schmidt, Rodney C. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Williamson, Richard [Idaho National Lab. (INL), Idaho Falls, ID (United States)
2015-09-01
This report summarizes a NEAMS (Nuclear Energy Advanced Modeling and Simulation) project focused on sensitivity analysis of a fuels performance benchmark problem. The benchmark problem was defined by the Uncertainty Analysis in Modeling working group of the Nuclear Science Committee, part of the Nuclear Energy Agency of the Organization for Economic Cooperation and Development (OECD ). The benchmark problem involv ed steady - state behavior of a fuel pin in a Pressurized Water Reactor (PWR). The problem was created in the BISON Fuels Performance code. Dakota was used to generate and analyze 300 samples of 17 input parameters defining core boundary conditions, manuf acturing tolerances , and fuel properties. There were 24 responses of interest, including fuel centerline temperatures at a variety of locations and burnup levels, fission gas released, axial elongation of the fuel pin, etc. Pearson and Spearman correlatio n coefficients and Sobol' variance - based indices were used to perform the sensitivity analysis. This report summarizes the process and presents results from this study.
SENSITIVITY ANALYSIS FOR SALTSTONE DISPOSAL UNIT COLUMN DEGRADATION ANALYSES
Energy Technology Data Exchange (ETDEWEB)
Flach, G.
2014-10-28
PORFLOW related analyses supporting a Sensitivity Analysis for Saltstone Disposal Unit (SDU) column degradation were performed. Previous analyses, Flach and Taylor 2014, used a model in which the SDU columns degraded in a piecewise manner from the top and bottom simultaneously. The current analyses employs a model in which all pieces of the column degrade at the same time. Information was extracted from the analyses which may be useful in determining the distribution of Tc-99 in the various SDUs throughout time and in determining flow balances for the SDUs.
Sensitivity analysis and design optimization through automatic differentiation
International Nuclear Information System (INIS)
Hovland, Paul D; Norris, Boyana; Strout, Michelle Mills; Bhowmick, Sanjukta; Utke, Jean
2005-01-01
Automatic differentiation is a technique for transforming a program or subprogram that computes a function, including arbitrarily complex simulation codes, into one that computes the derivatives of that function. We describe the implementation and application of automatic differentiation tools. We highlight recent advances in the combinatorial algorithms and compiler technology that underlie successful implementation of automatic differentiation tools. We discuss applications of automatic differentiation in design optimization and sensitivity analysis. We also describe ongoing research in the design of language-independent source transformation infrastructures for automatic differentiation algorithms
Expected Fitness Gains of Randomized Search Heuristics for the Traveling Salesperson Problem.
Nallaperuma, Samadhi; Neumann, Frank; Sudholt, Dirk
2017-01-01
Randomized search heuristics are frequently applied to NP-hard combinatorial optimization problems. The runtime analysis of randomized search heuristics has contributed tremendously to our theoretical understanding. Recently, randomized search heuristics have been examined regarding their achievable progress within a fixed-time budget. We follow this approach and present a fixed-budget analysis for an NP-hard combinatorial optimization problem. We consider the well-known Traveling Salesperson Problem (TSP) and analyze the fitness increase that randomized search heuristics are able to achieve within a given fixed-time budget. In particular, we analyze Manhattan and Euclidean TSP instances and Randomized Local Search (RLS), (1+1) EA and (1+[Formula: see text]) EA algorithms for the TSP in a smoothed complexity setting, and derive the lower bounds of the expected fitness gain for a specified number of generations.
Analysis of Hydrological Sensitivity for Flood Risk Assessment
Directory of Open Access Journals (Sweden)
Sanjay Kumar Sharma
2018-02-01
Full Text Available In order for the Indian government to maximize Integrated Water Resource Management (IWRM, the Brahmaputra River has played an important role in the undertaking of the Pilot Basin Study (PBS due to the Brahmaputra River’s annual regional flooding. The selected Kulsi River—a part of Brahmaputra sub-basin—experienced severe floods in 2007 and 2008. In this study, the Rainfall-Runoff-Inundation (RRI hydrological model was used to simulate the recent historical flood in order to understand and improve the integrated flood risk management plan. The ultimate objective was to evaluate the sensitivity of hydrologic simulation using different Digital Elevation Model (DEM resources, coupled with DEM smoothing techniques, with a particular focus on the comparison of river discharge and flood inundation extent. As a result, the sensitivity analysis showed that, among the input parameters, the RRI model is highly sensitive to Manning’s roughness coefficient values for flood plains, followed by the source of the DEM, and then soil depth. After optimizing its parameters, the simulated inundation extent showed that the smoothing filter was more influential than its simulated discharge at the outlet. Finally, the calibrated and validated RRI model simulations agreed well with the observed discharge and the Moderate Imaging Spectroradiometer (MODIS-detected flood extents.
Sensitivity analysis for the effects of multiple unmeasured confounders.
Groenwold, Rolf H H; Sterne, Jonathan A C; Lawlor, Debbie A; Moons, Karel G M; Hoes, Arno W; Tilling, Kate
2016-09-01
Observational studies are prone to (unmeasured) confounding. Sensitivity analysis of unmeasured confounding typically focuses on a single unmeasured confounder. The purpose of this study was to assess the impact of multiple (possibly weak) unmeasured confounders. Simulation studies were performed based on parameters estimated from the British Women's Heart and Health Study, including 28 measured confounders and assuming no effect of ascorbic acid intake on mortality. In addition, 25, 50, or 100 unmeasured confounders were simulated, with various mutual correlations and correlations with measured confounders. The correlated unmeasured confounders did not need to be strongly associated with exposure and outcome to substantially bias the exposure-outcome association at interest, provided that there are sufficiently many unmeasured confounders. Correlations between unmeasured confounders, in addition to the strength of their relationship with exposure and outcome, are key drivers of the magnitude of unmeasured confounding and should be considered in sensitivity analyses. However, if the unmeasured confounders are correlated with measured confounders, the bias yielded by unmeasured confounders is partly removed through adjustment for the measured confounders. Discussions of the potential impact of unmeasured confounding in observational studies, and sensitivity analyses to examine this, should focus on the potential for the joint effect of multiple unmeasured confounders to bias results. Copyright © 2016 Elsevier Inc. All rights reserved.
High order effects in cross section sensitivity analysis
International Nuclear Information System (INIS)
Greenspan, E.; Karni, Y.; Gilai, D.
1978-01-01
Two types of high order effects associated with perturbations in the flux shape are considered: Spectral Fine Structure Effects (SFSE) and non-linearity between changes in performance parameters and data uncertainties. SFSE are investigated in Part I using a simple single resonance model. Results obtained for each of the resolved and for representative unresolved resonances of 238 U in a ZPR-6/7 like environment indicate that SFSE can have a significant contribution to the sensitivity of group constants to resonance parameters. Methods to account for SFSE both for the propagation of uncertainties and for the adjustment of nuclear data are discussed. A Second Order Sensitivity Theory (SOST) is presented, and its accuracy relative to that of the first order sensitivity theory and of the direct substitution method is investigated in Part II. The investigation is done for the non-linear problem of the effect of changes in the 297 keV sodium minimum cross section on the transport of neutrons in a deep-penetration problem. It is found that the SOST provides a satisfactory accuracy for cross section uncertainty analysis. For the same degree of accuracy, the SOST can be significantly more efficient than the direct substitution method
Accuracy and sensitivity analysis on seismic anisotropy parameter estimation
Yan, Fuyong; Han, De-Hua
2018-04-01
There is significant uncertainty in measuring the Thomsen’s parameter δ in laboratory even though the dimensions and orientations of the rock samples are known. It is expected that more challenges will be encountered in the estimating of the seismic anisotropy parameters from field seismic data. Based on Monte Carlo simulation of vertical transversely isotropic layer cake model using the database of laboratory anisotropy measurement from the literature, we apply the commonly used quartic non-hyperbolic reflection moveout equation to estimate the seismic anisotropy parameters and test its accuracy and sensitivities to the source-receive offset, vertical interval velocity error and time picking error. The testing results show that the methodology works perfectly for noise-free synthetic data with short spread length. However, this method is extremely sensitive to the time picking error caused by mild random noises, and it requires the spread length to be greater than the depth of the reflection event. The uncertainties increase rapidly for the deeper layers and the estimated anisotropy parameters can be very unreliable for a layer with more than five overlain layers. It is possible that an isotropic formation can be misinterpreted as a strong anisotropic formation. The sensitivity analysis should provide useful guidance on how to group the reflection events and build a suitable geological model for anisotropy parameter inversion.
A global sensitivity analysis of crop virtual water content
Tamea, S.; Tuninetti, M.; D'Odorico, P.; Laio, F.; Ridolfi, L.
2015-12-01
The concepts of virtual water and water footprint are becoming widely used in the scientific literature and they are proving their usefulness in a number of multidisciplinary contexts. With such growing interest a measure of data reliability (and uncertainty) is becoming pressing but, as of today, assessments of data sensitivity to model parameters, performed at the global scale, are not known. This contribution aims at filling this gap. Starting point of this study is the evaluation of the green and blue virtual water content (VWC) of four staple crops (i.e. wheat, rice, maize, and soybean) at a global high resolution scale. In each grid cell, the crop VWC is given by the ratio between the total crop evapotranspiration over the growing season and the crop actual yield, where evapotranspiration is determined with a detailed daily soil water balance and actual yield is estimated using country-based data, adjusted to account for spatial variability. The model provides estimates of the VWC at a 5x5 arc minutes and it improves on previous works by using the newest available data and including multi-cropping practices in the evaluation. The model is then used as the basis for a sensitivity analysis, in order to evaluate the role of model parameters in affecting the VWC and to understand how uncertainties in input data propagate and impact the VWC accounting. In each cell, small changes are exerted to one parameter at a time, and a sensitivity index is determined as the ratio between the relative change of VWC and the relative change of the input parameter with respect to its reference value. At the global scale, VWC is found to be most sensitive to the planting date, with a positive (direct) or negative (inverse) sensitivity index depending on the typical season of crop planting date. VWC is also markedly dependent on the length of the growing period, with an increase in length always producing an increase of VWC, but with higher spatial variability for rice than for
Usage of Modified Heuristic Model for Determination of Software Stability
Directory of Open Access Journals (Sweden)
Sergey Konstantinovich Marfenko
2013-02-01
Full Text Available The subject of this paper is analysis method for determining the stability of software against the attacks on its integrity. It is suggested to use the modified heuristic model of software reliability as mathematic basis of this method. This model is based on classic approach, but it takes into account impact levels of different software errors on system integrity. It allows to define critical characteristics of software: percentage of time in stable working, the possibility of failure.
The Effect of Incentive Structure on Heuristic Decision Making: The Proportion Heuristic
Robert Oxoby
2007-01-01
When making judgments, individuals often utilize heuristics to interpret information. We report on a series of experiments designed to test the ways in which incentive mechanisms influence the use of a particular heuristic in decision-making. Specifically, we demonstrate how information regarding the number of available practice problems influences the behaviors of individuals preparing for an exam (the proportion heuristic). More importantly the extent to which this information influences be...
examining the predictive power of the VRIO-Framework and the Recognition Heuristic
Powalla, Christian
2010-01-01
Boundedly rational managers regularly have to make complex strategic decisions under uncertainty. In this context heuristics can play an important supporting role. They are used to reasonably structure the decision making process, to reduce the information search, and to achieve a good solution with an acceptable problem-solving effort. This empirical research project analyzes the practical usefulness of several selected heuristic techniques, which can be used within strategic analysis, by...
Variance-based sensitivity analysis for wastewater treatment plant modelling.
Cosenza, Alida; Mannina, Giorgio; Vanrolleghem, Peter A; Neumann, Marc B
2014-02-01
Global sensitivity analysis (GSA) is a valuable tool to support the use of mathematical models that characterise technical or natural systems. In the field of wastewater modelling, most of the recent applications of GSA use either regression-based methods, which require close to linear relationships between the model outputs and model factors, or screening methods, which only yield qualitative results. However, due to the characteristics of membrane bioreactors (MBR) (non-linear kinetics, complexity, etc.) there is an interest to adequately quantify the effects of non-linearity and interactions. This can be achieved with variance-based sensitivity analysis methods. In this paper, the Extended Fourier Amplitude Sensitivity Testing (Extended-FAST) method is applied to an integrated activated sludge model (ASM2d) for an MBR system including microbial product formation and physical separation processes. Twenty-one model outputs located throughout the different sections of the bioreactor and 79 model factors are considered. Significant interactions among the model factors are found. Contrary to previous GSA studies for ASM models, we find the relationship between variables and factors to be non-linear and non-additive. By analysing the pattern of the variance decomposition along the plant, the model factors having the highest variance contributions were identified. This study demonstrates the usefulness of variance-based methods in membrane bioreactor modelling where, due to the presence of membranes and different operating conditions than those typically found in conventional activated sludge systems, several highly non-linear effects are present. Further, the obtained results highlight the relevant role played by the modelling approach for MBR taking into account simultaneously biological and physical processes. © 2013.
DDASAC, Double-Precision Differential or Algebraic Sensitivity Analysis
International Nuclear Information System (INIS)
Caracotsios, M.; Stewart, W.E.; Petzold, L.
1997-01-01
1 - Description of program or function: DDASAC solves nonlinear initial-value problems involving stiff implicit systems of ordinary differential and algebraic equations. Purely algebraic nonlinear systems can also be solved, given an initial guess within the region of attraction of a solution. Options include automatic reconciliation of inconsistent initial states and derivatives, automatic initial step selection, direct concurrent parametric sensitivity analysis, and stopping at a prescribed value of any user-defined functional of the current solution vector. Local error control (in the max-norm or the 2-norm) is provided for the state vector and can include the sensitivities on request. 2 - Method of solution: Reconciliation of initial conditions is done with a damped Newton algorithm adapted from Bain and Stewart (1991). Initial step selection is done by the first-order algorithm of Shampine (1987), extended here to differential-algebraic equation systems. The solution is continued with the DASSL predictor- corrector algorithm (Petzold 1983, Brenan et al. 1989) with the initial acceleration phase detected and with row scaling of the Jacobian added. The backward-difference formulas for the predictor and corrector are expressed in divide-difference form, and the fixed-leading-coefficient form of the corrector (Jackson and Sacks-Davis 1980, Brenan et al. 1989) is used. Weights for error tests are updated in each step with the user's tolerances at the predicted state. Sensitivity analysis is performed directly on the corrector equations as given by Catacotsios and Stewart (1985) and is extended here to the initialization when needed. 3 - Restrictions on the complexity of the problem: This algorithm, like DASSL, performs well on differential-algebraic systems of index 0 and 1 but not on higher-index systems; see Brenan et al. (1989). The user assigns the work array lengths and the output unit. The machine number range and precision are determined at run time by a
Uncertainty and sensitivity analysis of environmental transport models
International Nuclear Information System (INIS)
Margulies, T.S.; Lancaster, L.E.
1985-01-01
An uncertainty and sensitivity analysis has been made of the CRAC-2 (Calculations of Reactor Accident Consequences) atmospheric transport and deposition models. Robustness and uncertainty aspects of air and ground deposited material and the relative contribution of input and model parameters were systematically studied. The underlying data structures were investigated using a multiway layout of factors over specified ranges generated via a Latin hypercube sampling scheme. The variables selected in our analysis include: weather bin, dry deposition velocity, rain washout coefficient/rain intensity, duration of release, heat content, sigma-z (vertical) plume dispersion parameter, sigma-y (crosswind) plume dispersion parameter, and mixing height. To determine the contributors to the output variability (versus distance from the site) step-wise regression analyses were performed on transformations of the spatial concentration patterns simulated. 27 references, 2 figures, 3 tables
Cross-covariance based global dynamic sensitivity analysis
Shi, Yan; Lu, Zhenzhou; Li, Zhao; Wu, Mengmeng
2018-02-01
For identifying the cross-covariance source of dynamic output at each time instant for structural system involving both input random variables and stochastic processes, a global dynamic sensitivity (GDS) technique is proposed. The GDS considers the effect of time history inputs on the dynamic output. In the GDS, the cross-covariance decomposition is firstly developed to measure the contribution of the inputs to the output at different time instant, and an integration of the cross-covariance change over the specific time interval is employed to measure the whole contribution of the input to the cross-covariance of output. Then, the GDS main effect indices and the GDS total effect indices can be easily defined after the integration, and they are effective in identifying the important inputs and the non-influential inputs on the cross-covariance of output at each time instant, respectively. The established GDS analysis model has the same form with the classical ANOVA when it degenerates to the static case. After degeneration, the first order partial effect can reflect the individual effects of inputs to the output variance, and the second order partial effect can reflect the interaction effects to the output variance, which illustrates the consistency of the proposed GDS indices and the classical variance-based sensitivity indices. The MCS procedure and the Kriging surrogate method are developed to solve the proposed GDS indices. Several examples are introduced to illustrate the significance of the proposed GDS analysis technique and the effectiveness of the proposed solution.
Complex finite element sensitivity method for creep analysis
International Nuclear Information System (INIS)
Gomez-Farias, Armando; Montoya, Arturo; Millwater, Harry
2015-01-01
The complex finite element method (ZFEM) has been extended to perform sensitivity analysis for mechanical and structural systems undergoing creep deformation. ZFEM uses a complex finite element formulation to provide shape, material, and loading derivatives of the system response, providing an insight into the essential factors which control the behavior of the system as a function of time. A complex variable-based quadrilateral user element (UEL) subroutine implementing the power law creep constitutive formulation was incorporated within the Abaqus commercial finite element software. The results of the complex finite element computations were verified by comparing them to the reference solution for the steady-state creep problem of a thick-walled cylinder in the power law creep range. A practical application of the ZFEM implementation to creep deformation analysis is the calculation of the skeletal point of a notched bar test from a single ZFEM run. In contrast, the standard finite element procedure requires multiple runs. The value of the skeletal point is that it identifies the location where the stress state is accurate, regardless of the certainty of the creep material properties. - Highlights: • A novel finite element sensitivity method (ZFEM) for creep was introduced. • ZFEM has the capability to calculate accurate partial derivatives. • ZFEM can be used for identification of the skeletal point of creep structures. • ZFEM can be easily implemented in a commercial software, e.g. Abaqus. • ZFEM results were shown to be in excellent agreement with analytical solutions
Overview of hybrid subspace methods for uncertainty quantification, sensitivity analysis
International Nuclear Information System (INIS)
Abdel-Khalik, Hany S.; Bang, Youngsuk; Wang, Congjian
2013-01-01
Highlights: ► We overview the state-of-the-art in uncertainty quantification and sensitivity analysis. ► We overview new developments in above areas using hybrid methods. ► We give a tutorial introduction to above areas and the new developments. ► Hybrid methods address the explosion in dimensionality in nonlinear models. ► Representative numerical experiments are given. -- Abstract: The role of modeling and simulation has been heavily promoted in recent years to improve understanding of complex engineering systems. To realize the benefits of modeling and simulation, concerted efforts in the areas of uncertainty quantification and sensitivity analysis are required. The manuscript intends to serve as a pedagogical presentation of the material to young researchers and practitioners with little background on the subjects. We believe this is important as the role of these subjects is expected to be integral to the design, safety, and operation of existing as well as next generation reactors. In addition to covering the basics, an overview of the current state-of-the-art will be given with particular emphasis on the challenges pertaining to nuclear reactor modeling. The second objective will focus on presenting our own development of hybrid subspace methods intended to address the explosion in the computational overhead required when handling real-world complex engineering systems.
Control strategies and sensitivity analysis of anthroponotic visceral leishmaniasis model.
Zamir, Muhammad; Zaman, Gul; Alshomrani, Ali Saleh
2017-12-01
This study proposes a mathematical model of Anthroponotic visceral leishmaniasis epidemic with saturated infection rate and recommends different control strategies to manage the spread of this disease in the community. To do this, first, a model formulation is presented to support these strategies, with quantifications of transmission and intervention parameters. To understand the nature of the initial transmission of the disease, the reproduction number [Formula: see text] is obtained by using the next-generation method. On the basis of sensitivity analysis of the reproduction number [Formula: see text], four different control strategies are proposed for managing disease transmission. For quantification of the prevalence period of the disease, a numerical simulation for each strategy is performed and a detailed summary is presented. Disease-free state is obtained with the help of control strategies. The threshold condition for globally asymptotic stability of the disease-free state is found, and it is ascertained that the state is globally stable. On the basis of sensitivity analysis of the reproduction number, it is shown that the disease can be eradicated by using the proposed strategies.
Sensitivity Analysis in Observational Research: Introducing the E-Value.
VanderWeele, Tyler J; Ding, Peng
2017-08-15
Sensitivity analysis is useful in assessing how robust an association is to potential unmeasured or uncontrolled confounding. This article introduces a new measure called the "E-value," which is related to the evidence for causality in observational studies that are potentially subject to confounding. The E-value is defined as the minimum strength of association, on the risk ratio scale, that an unmeasured confounder would need to have with both the treatment and the outcome to fully explain away a specific treatment-outcome association, conditional on the measured covariates. A large E-value implies that considerable unmeasured confounding would be needed to explain away an effect estimate. A small E-value implies little unmeasured confounding would be needed to explain away an effect estimate. The authors propose that in all observational studies intended to produce evidence for causality, the E-value be reported or some other sensitivity analysis be used. They suggest calculating the E-value for both the observed association estimate (after adjustments for measured confounders) and the limit of the confidence interval closest to the null. If this were to become standard practice, the ability of the scientific community to assess evidence from observational studies would improve considerably, and ultimately, science would be strengthened.
Nordic reference study on uncertainty and sensitivity analysis
International Nuclear Information System (INIS)
Hirschberg, S.; Jacobsson, P.; Pulkkinen, U.; Porn, K.
1989-01-01
This paper provides a review of the first phase of Nordic reference study on uncertainty and sensitivity analysis. The main objective of this study is to use experiences form previous Nordic Benchmark Exercises and reference studies concerning critical modeling issues such as common cause failures and human interactions, and to demonstrate the impact of associated uncertainties on the uncertainty of the investigated accident sequence. This has been done independently by three working groups which used different approaches to modeling and to uncertainty analysis. The estimated uncertainty interval for the analyzed accident sequence is large. Also the discrepancies between the groups are substantial but can be explained. Sensitivity analyses which have been carried out concern e.g. use of different CCF-quantification models, alternative handling of CCF-data, time windows for operator actions and time dependences in phase mission operation, impact of state-of-knowledge dependences and ranking of dominating uncertainty contributors. Specific findings with respect to these issues are summarized in the paper
Simple Sensitivity Analysis for Orion Guidance Navigation and Control
Pressburger, Tom; Hoelscher, Brian; Martin, Rodney; Sricharan, Kumar
2013-01-01
The performance of Orion flight software, especially its GNC software, is being analyzed by running Monte Carlo simulations of Orion spacecraft flights. The simulated performance is analyzed for conformance with flight requirements, expressed as performance constraints. Flight requirements include guidance (e.g. touchdown distance from target) and control (e.g., control saturation) as well as performance (e.g., heat load constraints). The Monte Carlo simulations disperse hundreds of simulation input variables, for everything from mass properties to date of launch. We describe in this paper a sensitivity analysis tool ("Critical Factors Tool" or CFT) developed to find the input variables or pairs of variables which by themselves significantly influence satisfaction of requirements or significantly affect key performance metrics (e.g., touchdown distance from target). Knowing these factors can inform robustness analysis, can inform where engineering resources are most needed, and could even affect operations. The contributions of this paper include the introduction of novel sensitivity measures, such as estimating success probability, and a technique for determining whether pairs of factors are interacting dependently or independently. The tool found that input variables such as moments, mass, thrust dispersions, and date of launch were found to be significant factors for success of various requirements. Examples are shown in this paper as well as a summary and physics discussion of EFT-1 driving factors that the tool found.
Deterministic sensitivity analysis for the numerical simulation of contaminants transport
International Nuclear Information System (INIS)
Marchand, E.
2007-12-01
The questions of safety and uncertainty are central to feasibility studies for an underground nuclear waste storage site, in particular the evaluation of uncertainties about safety indicators which are due to uncertainties concerning properties of the subsoil or of the contaminants. The global approach through probabilistic Monte Carlo methods gives good results, but it requires a large number of simulations. The deterministic method investigated here is complementary. Based on the Singular Value Decomposition of the derivative of the model, it gives only local information, but it is much less demanding in computing time. The flow model follows Darcy's law and the transport of radionuclides around the storage site follows a linear convection-diffusion equation. Manual and automatic differentiation are compared for these models using direct and adjoint modes. A comparative study of both probabilistic and deterministic approaches for the sensitivity analysis of fluxes of contaminants through outlet channels with respect to variations of input parameters is carried out with realistic data provided by ANDRA. Generic tools for sensitivity analysis and code coupling are developed in the Caml language. The user of these generic platforms has only to provide the specific part of the application in any language of his choice. We also present a study about two-phase air/water partially saturated flows in hydrogeology concerning the limitations of the Richards approximation and of the global pressure formulation used in petroleum engineering. (author)
Sensitivity Analysis of a Riparian Vegetation Growth Model
Directory of Open Access Journals (Sweden)
Michael Nones
2016-11-01
Full Text Available The paper presents a sensitivity analysis of two main parameters used in a mathematic model able to evaluate the effects of changing hydrology on the growth of riparian vegetation along rivers and its effects on the cross-section width. Due to a lack of data in existing literature, in a past study the schematization proposed here was applied only to two large rivers, assuming steady conditions for the vegetational carrying capacity and coupling the vegetal model with a 1D description of the river morphology. In this paper, the limitation set by steady conditions is overcome, imposing the vegetational evolution dependent upon the initial plant population and the growth rate, which represents the potential growth of the overall vegetation along the watercourse. The sensitivity analysis shows that, regardless of the initial population density, the growth rate can be considered the main parameter defining the development of riparian vegetation, but it results site-specific effects, with significant differences for large and small rivers. Despite the numerous simplifications adopted and the small database analyzed, the comparison between measured and computed river widths shows a quite good capability of the model in representing the typical interactions between riparian vegetation and water flow occurring along watercourses. After a thorough calibration, the relatively simple structure of the code permits further developments and applications to a wide range of alluvial rivers.
Sensitivity analysis of numerical model of prestressed concrete containment
Energy Technology Data Exchange (ETDEWEB)
Bílý, Petr, E-mail: petr.bily@fsv.cvut.cz; Kohoutková, Alena, E-mail: akohout@fsv.cvut.cz
2015-12-15
Graphical abstract: - Highlights: • FEM model of prestressed concrete containment with steel liner was created. • Sensitivity analysis of changes in geometry and loads was conducted. • Steel liner and temperature effects are the most important factors. • Creep and shrinkage parameters are essential for the long time analysis. • Prestressing schedule is a key factor in the early stages. - Abstract: Safety is always the main consideration in the design of containment of nuclear power plant. However, efficiency of the design process should be also taken into consideration. Despite the advances in computational abilities in recent years, simplified analyses may be found useful for preliminary scoping or trade studies. In the paper, a study on sensitivity of finite element model of prestressed concrete containment to changes in geometry, loads and other factors is presented. Importance of steel liner, reinforcement, prestressing process, temperature changes, nonlinearity of materials as well as density of finite elements mesh is assessed in the main stages of life cycle of the containment. Although the modeling adjustments have not produced any significant changes in computation time, it was found that in some cases simplified modeling process can lead to significant reduction of work time without degradation of the results.
Procedures for uncertainty and sensitivity analysis in repository performance assessment
International Nuclear Information System (INIS)
Poern, K.; Aakerlund, O.
1985-10-01
The objective of the project was mainly a literature study of available methods for the treatment of parameter uncertainty propagation and sensitivity aspects in complete models such as those concerning geologic disposal of radioactive waste. The study, which has run parallel with the development of a code package (PROPER) for computer assisted analysis of function, also aims at the choice of accurate, cost-affective methods for uncertainty and sensitivity analysis. Such a choice depends on several factors like the number of input parameters, the capacity of the model and the computer reresources required to use the model. Two basic approaches are addressed in the report. In one of these the model of interest is directly simulated by an efficient sampling technique to generate an output distribution. Applying the other basic method the model is replaced by an approximating analytical response surface, which is then used in the sampling phase or in moment matching to generate the output distribution. Both approaches are illustrated by simple examples in the report. (author)
Global sensitivity analysis for models with spatially dependent outputs
International Nuclear Information System (INIS)
Iooss, B.; Marrel, A.; Jullien, M.; Laurent, B.
2011-01-01
The global sensitivity analysis of a complex numerical model often calls for the estimation of variance-based importance measures, named Sobol' indices. Meta-model-based techniques have been developed in order to replace the CPU time-expensive computer code with an inexpensive mathematical function, which predicts the computer code output. The common meta-model-based sensitivity analysis methods are well suited for computer codes with scalar outputs. However, in the environmental domain, as in many areas of application, the numerical model outputs are often spatial maps, which may also vary with time. In this paper, we introduce an innovative method to obtain a spatial map of Sobol' indices with a minimal number of numerical model computations. It is based upon the functional decomposition of the spatial output onto a wavelet basis and the meta-modeling of the wavelet coefficients by the Gaussian process. An analytical example is presented to clarify the various steps of our methodology. This technique is then applied to a real hydrogeological case: for each model input variable, a spatial map of Sobol' indices is thus obtained. (authors)
Multivariate Sensitivity Analysis of Time-of-Flight Sensor Fusion
Schwarz, Sebastian; Sjöström, Mårten; Olsson, Roger
2014-09-01
Obtaining three-dimensional scenery data is an essential task in computer vision, with diverse applications in various areas such as manufacturing and quality control, security and surveillance, or user interaction and entertainment. Dedicated Time-of-Flight sensors can provide detailed scenery depth in real-time and overcome short-comings of traditional stereo analysis. Nonetheless, they do not provide texture information and have limited spatial resolution. Therefore such sensors are typically combined with high resolution video sensors. Time-of-Flight Sensor Fusion is a highly active field of research. Over the recent years, there have been multiple proposals addressing important topics such as texture-guided depth upsampling and depth data denoising. In this article we take a step back and look at the underlying principles of ToF sensor fusion. We derive the ToF sensor fusion error model and evaluate its sensitivity to inaccuracies in camera calibration and depth measurements. In accordance with our findings, we propose certain courses of action to ensure high quality fusion results. With this multivariate sensitivity analysis of the ToF sensor fusion model, we provide an important guideline for designing, calibrating and running a sophisticated Time-of-Flight sensor fusion capture systems.
Hydrocoin level 3 - Testing methods for sensitivity/uncertainty analysis
International Nuclear Information System (INIS)
Grundfelt, B.; Lindbom, B.; Larsson, A.; Andersson, K.
1991-01-01
The HYDROCOIN study is an international cooperative project for testing groundwater hydrology modelling strategies for performance assessment of nuclear waste disposal. The study was initiated in 1984 by the Swedish Nuclear Power Inspectorate and the technical work was finalised in 1987. The participating organisations are regulatory authorities as well as implementing organisations in 10 countries. The study has been performed at three levels aimed at studying computer code verification, model validation and sensitivity/uncertainty analysis respectively. The results from the first two levels, code verification and model validation, have been published in reports in 1988 and 1990 respectively. This paper focuses on some aspects of the results from Level 3, sensitivity/uncertainty analysis, for which a final report is planned to be published during 1990. For Level 3, seven test cases were defined. Some of these aimed at exploring the uncertainty associated with the modelling results by simply varying parameter values and conceptual assumptions. In other test cases statistical sampling methods were applied. One of the test cases dealt with particle tracking and the uncertainty introduced by this type of post processing. The amount of results available is substantial although unevenly spread over the test cases. It has not been possible to cover all aspects of the results in this paper. Instead, the different methods applied will be illustrated by some typical analyses. 4 figs., 9 refs
Thermodynamics-based Metabolite Sensitivity Analysis in metabolic networks.
Kiparissides, A; Hatzimanikatis, V
2017-01-01
The increasing availability of large metabolomics datasets enhances the need for computational methodologies that can organize the data in a way that can lead to the inference of meaningful relationships. Knowledge of the metabolic state of a cell and how it responds to various stimuli and extracellular conditions can offer significant insight in the regulatory functions and how to manipulate them. Constraint based methods, such as Flux Balance Analysis (FBA) and Thermodynamics-based flux analysis (TFA), are commonly used to estimate the flow of metabolites through genome-wide metabolic networks, making it possible to identify the ranges of flux values that are consistent with the studied physiological and thermodynamic conditions. However, unless key intracellular fluxes and metabolite concentrations are known, constraint-based models lead to underdetermined problem formulations. This lack of information propagates as uncertainty in the estimation of fluxes and basic reaction properties such as the determination of reaction directionalities. Therefore, knowledge of which metabolites, if measured, would contribute the most to reducing this uncertainty can significantly improve our ability to define the internal state of the cell. In the present work we combine constraint based modeling, Design of Experiments (DoE) and Global Sensitivity Analysis (GSA) into the Thermodynamics-based Metabolite Sensitivity Analysis (TMSA) method. TMSA ranks metabolites comprising a metabolic network based on their ability to constrain the gamut of possible solutions to a limited, thermodynamically consistent set of internal states. TMSA is modular and can be applied to a single reaction, a metabolic pathway or an entire metabolic network. This is, to our knowledge, the first attempt to use metabolic modeling in order to provide a significance ranking of metabolites to guide experimental measurements. Copyright © 2016 International Metabolic Engineering Society. Published by Elsevier
Heuristic attacks against graphical password generators
CSIR Research Space (South Africa)
Peach, S
2010-05-01
Full Text Available In this paper the authors explore heuristic attacks against graphical password generators. A new trend is emerging to use user clickable pictures to generate passwords. This technique of authentication can be successfully used for - for example...
A Direct Heuristic Algorithm for Linear Programming
Indian Academy of Sciences (India)
Abstract. An (3) mathematically non-iterative heuristic procedure that needs no artificial variable is presented for solving linear programming problems. An optimality test is included. Numerical experiments depict the utility/scope of such a procedure.
Hermawati, Setia; Lawson, Glyn
2016-09-01
Heuristics evaluation is frequently employed to evaluate usability. While general heuristics are suitable to evaluate most user interfaces, there is still a need to establish heuristics for specific domains to ensure that their specific usability issues are identified. This paper presents a comprehensive review of 70 studies related to usability heuristics for specific domains. The aim of this paper is to review the processes that were applied to establish heuristics in specific domains and identify gaps in order to provide recommendations for future research and area of improvements. The most urgent issue found is the deficiency of validation effort following heuristics proposition and the lack of robustness and rigour of validation method adopted. Whether domain specific heuristics perform better or worse than general ones is inconclusive due to lack of validation quality and clarity on how to assess the effectiveness of heuristics for specific domains. The lack of validation quality also affects effort in improving existing heuristics for specific domain as their weaknesses are not addressed. Copyright © 2016 Elsevier Ltd. All rights reserved.
RELAXATION HEURISTICS FOR THE SET COVERING PROBLEM
Umetani, Shunji; Yagiura, Mutsunori; 柳浦, 睦憲
2007-01-01
The set covering problem (SCP) is one of representative combinatorial optimization problems, which has many practical applications. The continuous development of mathematical programming has derived a number of impressive heuristic algorithms as well as exact branch-and-bound algorithms, which can solve huge SCP instances of bus, railway and airline crew scheduling problems. We survey heuristic algorithms for SCP focusing mainly on contributions of mathematical programming techniques to heuri...
A heuristic forecasting model for stock decision
Zhang, D.; Jiang, Q.; Li, X.
2005-01-01
This paper describes a heuristic forecasting model based on neural networks for stock decision-making. Some heuristic strategies are presented for enhancing the learning capability of neural networks and obtaining better trading performance. The China Shanghai Composite Index is used as case study. The forecasting model can forecast the buying and selling signs according to the result of neural network prediction. Results are compared with a benchmark buy-and-hold strategy. ...
Psychology into economics: fast and frugal heuristics
Schilirò, Daniele
2015-01-01
The present essay focuses on the fast and frugal heuristics program set forth by Gerd Gigerenzer and his fellows. In particular it examines the contribution of Gigerenzer and Goldstein (1996) ‘Reasoning the Fast and Frugal Way: Models of Bounded Rationality’. This essay, following the theoretical propositions and the empirical evidence of Gigerenzer and Goldstein, points out that simple cognitive mechanisms such as fast and frugal heuristics can be capable of successful performance in real wo...
Arational heuristic model of economic decision making
Grandori, Anna
2010-01-01
The article discuss the limits of both the rational actor and the behavioral paradigms in explaining and guiding innovative decision making and outlines a model of economic decision making that in the course of being 'heuristic' (research and discovery oriented) is also 'rational' (in the broad sense of following correct reasoning and scientific methods, non 'biasing'). The model specifies a set of 'rational heuristics' for innovative decision making, for the various sub-processes of problem ...
Social heuristics shape intuitive cooperation.
Rand, David G; Peysakhovich, Alexander; Kraft-Todd, Gordon T; Newman, George E; Wurzbacher, Owen; Nowak, Martin A; Greene, Joshua D
2014-04-22
Cooperation is central to human societies. Yet relatively little is known about the cognitive underpinnings of cooperative decision making. Does cooperation require deliberate self-restraint? Or is spontaneous prosociality reined in by calculating self-interest? Here we present a theory of why (and for whom) intuition favors cooperation: cooperation is typically advantageous in everyday life, leading to the formation of generalized cooperative intuitions. Deliberation, by contrast, adjusts behaviour towards the optimum for a given situation. Thus, in one-shot anonymous interactions where selfishness is optimal, intuitive responses tend to be more cooperative than deliberative responses. We test this 'social heuristics hypothesis' by aggregating across every cooperation experiment using time pressure that we conducted over a 2-year period (15 studies and 6,910 decisions), as well as performing a novel time pressure experiment. Doing so demonstrates a positive average effect of time pressure on cooperation. We also find substantial variation in this effect, and show that this variation is partly explained by previous experience with one-shot lab experiments.
Sensitivity analysis for modules for various biosphere types
International Nuclear Information System (INIS)
Karlsson, Sara; Bergstroem, U.; Rosen, K.
2000-09-01
This study presents the results of a sensitivity analysis for the modules developed earlier for calculation of ecosystem specific dose conversion factors (EDFs). The report also includes a comparison between the probabilistically calculated mean values of the EDFs and values gained in deterministic calculations. An overview of the distribution of radionuclides between different environmental parts in the models is also presented. The radionuclides included in the study were 36 Cl, 59 Ni, 93 Mo, 129 I, 135 Cs, 237 Np and 239 Pu, sel to represent various behaviour in the biosphere and some are of particular importance from the dose point of view. The deterministic and probabilistic EDFs showed a good agreement, for most nuclides and modules. Exceptions from this occurred if very skew distributions were used for parameters of importance for the results. Only a minor amount of the released radionuclides were present in the model compartments for all modules, except for the agricultural land module. The differences between the radionuclides were not pronounced which indicates that nuclide specific parameters were of minor importance for the retention of radionuclides for the simulated time period of 10 000 years in those modules. The results from the agricultural land module showed a different pattern. Large amounts of the radionuclides were present in the solid fraction of the saturated soil zone. The high retention within this compartment makes the zone a potential source for future exposure. Differences between the nuclides due to element specific Kd-values could be seen. The amount of radionuclides present in the upper soil layer, which is the most critical zone for exposure to humans, was less then 1% for all studied radionuclides. The sensitivity analysis showed that the physical/chemical parameters were the most important in most modules in contrast to the dominance of biological parameters in the uncertainty analysis. The only exception was the well module where
Sensitivity analysis of the terrestrial food chain model FOOD III
International Nuclear Information System (INIS)
Zach, Reto.
1980-10-01
As a first step in constructing a terrestrial food chain model suitable for long-term waste management situations, a numerical sensitivity analysis of FOOD III was carried out to identify important model parameters. The analysis involved 42 radionuclides, four pathways, 14 food types, 93 parameters and three percentages of parameter variation. We also investigated the importance of radionuclides, pathways and food types. The analysis involved a simple contamination model to render results from individual pathways comparable. The analysis showed that radionuclides vary greatly in their dose contribution to each of the four pathways, but relative contributions to each pathway are very similar. Man's and animals' drinking water pathways are much more important than the leaf and root pathways. However, this result depends on the contamination model used. All the pathways contain unimportant food types. Considering the number of parameters involved, FOOD III has too many different food types. Many of the parameters of the leaf and root pathway are important. However, this is true for only a few of the parameters of animals' drinking water pathway, and for neither of the two parameters of mans' drinking water pathway. The radiological decay constant increases the variability of these results. The dose factor is consistently the most important variable, and it explains most of the variability of radionuclide doses within pathways. Consideration of the variability of dose factors is important in contemporary as well as long-term waste management assessment models, if realistic estimates are to be made. (auth)
Uncertainty and sensitivity analysis in nuclear accident consequence assessment
International Nuclear Information System (INIS)
Karlberg, Olof.
1989-01-01
This report contains the results of a four year project in research contracts with the Nordic Cooperation in Nuclear Safety and the National Institute for Radiation Protection. An uncertainty/sensitivity analysis methodology consisting of Latin Hypercube sampling and regression analysis was applied to an accident consequence model. A number of input parameters were selected and the uncertainties related to these parameter were estimated within a Nordic group of experts. Individual doses, collective dose, health effects and their related uncertainties were then calculated for three release scenarios and for a representative sample of meteorological situations. From two of the scenarios the acute phase after an accident were simulated and from one the long time consequences. The most significant parameters were identified. The outer limits of the calculated uncertainty distributions are large and will grow to several order of magnitudes for the low probability consequences. The uncertainty in the expectation values are typical a factor 2-5 (1 Sigma). The variation in the model responses due to the variation of the weather parameters is fairly equal to the parameter uncertainty induced variation. The most important parameters showed out to be different for each pathway of exposure, which could be expected. However, the overall most important parameters are the wet deposition coefficient and the shielding factors. A general discussion of the usefulness of uncertainty analysis in consequence analysis is also given. (au)
Robust and sensitive analysis of mouse knockout phenotypes.
Directory of Open Access Journals (Sweden)
Natasha A Karp
Full Text Available A significant challenge of in-vivo studies is the identification of phenotypes with a method that is robust and reliable. The challenge arises from practical issues that lead to experimental designs which are not ideal. Breeding issues, particularly in the presence of fertility or fecundity problems, frequently lead to data being collected in multiple batches. This problem is acute in high throughput phenotyping programs. In addition, in a high throughput environment operational issues lead to controls not being measured on the same day as knockouts. We highlight how application of traditional methods, such as a Student's t-Test or a 2-way ANOVA, in these situations give flawed results and should not be used. We explore the use of mixed models using worked examples from Sanger Mouse Genome Project focusing on Dual-Energy X-Ray Absorptiometry data for the analysis of mouse knockout data and compare to a reference range approach. We show that mixed model analysis is more sensitive and less prone to artefacts allowing the discovery of subtle quantitative phenotypes essential for correlating a gene's function to human disease. We demonstrate how a mixed model approach has the additional advantage of being able to include covariates, such as body weight, to separate effect of genotype from these covariates. This is a particular issue in knockout studies, where body weight is a common phenotype and will enhance the precision of assigning phenotypes and the subsequent selection of lines for secondary phenotyping. The use of mixed models with in-vivo studies has value not only in improving the quality and sensitivity of the data analysis but also ethically as a method suitable for small batches which reduces the breeding burden of a colony. This will reduce the use of animals, increase throughput, and decrease cost whilst improving the quality and depth of knowledge gained.
Four Data Visualization Heuristics to Facilitate Reflection in Personal Informatics
DEFF Research Database (Denmark)
Cuttone, Andrea; Petersen, Michael Kai; Larsen, Jakob Eg
2014-01-01
In this paper we discuss how to facilitate the process of reflection in Personal Informatics and Quantified Self systems through interactive data visualizations. Four heuristics for the design and evaluation of such systems have been identified through analysis of self-tracking devices and apps....... Dashboard interface paradigms in specific self-tracking devices (Fitbit and Basis) are discussed as representative examples of state of the art in feedback and reflection support. By relating to existing work in other domains, such as event related representation of time series multivariate data...... in financial analytics, it is discussed how the heuristics could guide designs that would further facilitate reflection in self-tracking personal informatics systems....
Adapting Nielsen's Design Heuristics to Dual Processing for Clinical Decision Support.
Taft, Teresa; Staes, Catherine; Slager, Stacey; Weir, Charlene
2016-01-01
The study objective was to improve the applicability of Nielson's standard design heuristics for evaluating electronic health record (EHR) alerts and linked ordering support by integrating them with Dual Process theory. Through initial heuristic evaluation and a user study of 7 physicians, usability problems were identified. Through independent mapping of specific usability criteria to support for each of the Dual Cognitive processes (S1 and S2) and deliberation, agreement was reached on mapping criteria. Finally, usability errors from the heuristic and user study were mapped to S1 and S2. Adding a dual process perspective to specific heuristic analysis increases the applicability and relevance of computerized health information design evaluations. This mapping enables designers to measure that their systems are tailored to support attention allocation. System 1 will be supported by improving pattern recognition and saliency, and system 2 through efficiency and control of information access.
Adapting Nielsen’s Design Heuristics to Dual Processing for Clinical Decision Support
Taft, Teresa; Staes, Catherine; Slager, Stacey; Weir, Charlene
2016-01-01
The study objective was to improve the applicability of Nielson’s standard design heuristics for evaluating electronic health record (EHR) alerts and linked ordering support by integrating them with Dual Process theory. Through initial heuristic evaluation and a user study of 7 physicians, usability problems were identified. Through independent mapping of specific usability criteria to support for each of the Dual Cognitive processes (S1 and S2) and deliberation, agreement was reached on mapping criteria. Finally, usability errors from the heuristic and user study were mapped to S1 and S2. Adding a dual process perspective to specific heuristic analysis increases the applicability and relevance of computerized health information design evaluations. This mapping enables designers to measure that their systems are tailored to support attention allocation. System 1 will be supported by improving pattern recognition and saliency, and system 2 through efficiency and control of information access. PMID:28269915
A health literacy and usability heuristic evaluation of a mobile consumer health application.
Monkman, Helen; Kushniruk, Andre
2013-01-01
Usability and health literacy are two critical factors in the design and evaluation of consumer health information systems. However, methods for evaluating these two factors in conjunction remain limited. This study adapted a set of existing guidelines for the design of consumer health Web sites into evidence-based evaluation heuristics tailored specifically for mobile consumer health applications. In order to test the approach, a mobile consumer health application (app) was then evaluated using these heuristics. In addition to revealing ways to improve the usability of the system, this analysis identified opportunities to augment the content to make it more understandable by users with limited health literacy. This study successfully demonstrated the utility of converting existing design guidelines into heuristics for the evaluation of usability and health literacy. The heuristics generated could be applied for assessing and revising other existing consumer health information systems.
Madni, Syed Hamid Hussain; Abd Latiff, Muhammad Shafie; Abdullahi, Mohammed; Usman, Mohammed Joda
2017-01-01
Cloud computing infrastructure is suitable for meeting computational needs of large task sizes. Optimal scheduling of tasks in cloud computing environment has been proved to be an NP-complete problem, hence the need for the application of heuristic methods. Several heuristic algorithms have been developed and used in addressing this problem, but choosing the appropriate algorithm for solving task assignment problem of a particular nature is difficult since the methods are developed under different assumptions. Therefore, six rule based heuristic algorithms are implemented and used to schedule autonomous tasks in homogeneous and heterogeneous environments with the aim of comparing their performance in terms of cost, degree of imbalance, makespan and throughput. First Come First Serve (FCFS), Minimum Completion Time (MCT), Minimum Execution Time (MET), Max-min, Min-min and Sufferage are the heuristic algorithms considered for the performance comparison and analysis of task scheduling in cloud computing. PMID:28467505
Madni, Syed Hamid Hussain; Abd Latiff, Muhammad Shafie; Abdullahi, Mohammed; Abdulhamid, Shafi'i Muhammad; Usman, Mohammed Joda
2017-01-01
Cloud computing infrastructure is suitable for meeting computational needs of large task sizes. Optimal scheduling of tasks in cloud computing environment has been proved to be an NP-complete problem, hence the need for the application of heuristic methods. Several heuristic algorithms have been developed and used in addressing this problem, but choosing the appropriate algorithm for solving task assignment problem of a particular nature is difficult since the methods are developed under different assumptions. Therefore, six rule based heuristic algorithms are implemented and used to schedule autonomous tasks in homogeneous and heterogeneous environments with the aim of comparing their performance in terms of cost, degree of imbalance, makespan and throughput. First Come First Serve (FCFS), Minimum Completion Time (MCT), Minimum Execution Time (MET), Max-min, Min-min and Sufferage are the heuristic algorithms considered for the performance comparison and analysis of task scheduling in cloud computing.
Heuristic optimization in penumbral image for high resolution reconstructed image
International Nuclear Information System (INIS)
Azuma, R.; Nozaki, S.; Fujioka, S.; Chen, Y. W.; Namihira, Y.
2010-01-01
Penumbral imaging is a technique which uses the fact that spatial information can be recovered from the shadow or penumbra that an unknown source casts through a simple large circular aperture. The size of the penumbral image on the detector can be mathematically determined as its aperture size, object size, and magnification. Conventional reconstruction methods are very sensitive to noise. On the other hand, the heuristic reconstruction method is very tolerant of noise. However, the aperture size influences the accuracy and resolution of the reconstructed image. In this article, we propose the optimization of the aperture size for the neutron penumbral imaging.
International Nuclear Information System (INIS)
Iman, R.L.; Helton, J.C.
1985-01-01
Probabilistic Risk Assessment (PRA) is playing an increasingly important role in the nuclear reactor regulatory process. The assessment of uncertainties associated with PRA results is widely recognized as an important part of the analysis process. One of the major criticisms of the Reactor Safety Study was that its representation of uncertainty was inadequate. The desire for the capability to treat uncertainties with the MELCOR risk code being developed at Sandia National Laboratories is indicative of the current interest in this topic. However, as yet, uncertainty analysis and sensitivity analysis in the context of PRA is a relatively immature field. In this paper, available methods for uncertainty analysis and sensitivity analysis in a PRA are reviewed. This review first treats methods for use with individual components of a PRA and then considers how these methods could be combined in the performance of a complete PRA. In the context of this paper, the goal of uncertainty analysis is to measure the imprecision in PRA outcomes of interest, and the goal of sensitivity analysis is to identify the major contributors to this imprecision. There are a number of areas that must be considered in uncertainty analysis and sensitivity analysis for a PRA: (1) information, (2) systems analysis, (3) thermal-hydraulic phenomena/fission product behavior, (4) health and economic consequences, and (5) display of results. Each of these areas and the synthesis of them into a complete PRA are discussed
Sensitivity Analysis Of Financing Demand In Syariah Banking
Directory of Open Access Journals (Sweden)
DR. HJ. ROSYETTI
2017-11-01
Full Text Available This study aims to analyze the Sensitivity of Demand Financing in syariah banking with a focus on the elasticity of financing demand income elasticity and cross elasticity. The type of data used in this study is secondary data quantitative and time series obtained from the publication of BPS BI and OJK. The data analysis technique begins by estimating multiple linear regression equations using the Eviews Application further measuring the sensitivity using elasticity. The research variables consist of revenue gross domestic product and conventional bank interest rate as independent variables and demand for financing as a dependent variable. The results obtained for the results gross domestic product and interest rate of conventional banks simultaneously affect the demand for financing in Islamic banking with a significant level of 5 obtained probability value F statistic amp945 005. Partially revenue share and gross domestic product have a significant effect on demand for financing. While the variable interest rate of conventional banks partially does not have a significant effect on demand for financing in Islamic banking. The ability of the three independent variables to explain the dependent variable of 99.06 the rest of 0.04 influenced by other factors outside this study. The sensitive value of demand for financing in syariah banking during the observation period was 3.94 amp400P 1 so that it can be said that demand for financing in syariah banking is elastic. The elasticity of income demand for financing in syariah banking during the observation period of 3.08 amp400I 1 is categorized as luxuries goods. The cross elasticity value of financing demand in syariah banking during the observation period is 0.52 or positive amp400C 0 it can be categorized that the interest rate of a conventional bank is a substitute of profit sharing.
Simplified procedures for fast reactor fuel cycle and sensitivity analysis
International Nuclear Information System (INIS)
Badruzzaman, A.
1979-01-01
The Continuous Slowing Down-Integral Transport Theory has been extended to perform criticality calculations in a Fast Reactor Core-blanket system achieving excellent prediction of the spectrum and the eigenvalue. The integral transport parameters did not need recalculation with source iteration and were found to be relatively constant with exposure. Fuel cycle parameters were accurately predicted when these were not varied, thus reducing a principal potential penalty of the Intergal Transport approach where considerable effort may be required to calculate transport parameters in more complicated geometries. The small variation of the spectrum in the central core region, and its weak dependence on exposure for both this region, the core blanket interface and blanket region led to the extension and development of inexpensive simplified procedures to complement exact methods. These procedures gave accurate predictions of the key fuel cycle parameters such as cost and their sensitivity to variation in spectrum-averaged and multigroup cross sections. They also predicted the implications of design variation on these parameters very well. The accuracy of these procedures and their use in analyzing a wide variety of sensitivities demonstrate the potential utility of survey calculations in Fast Reactor analysis and fuel management
Relative sensitivity analysis of the predictive properties of sloppy models.
Myasnikova, Ekaterina; Spirov, Alexander
2018-01-25
Commonly among the model parameters characterizing complex biological systems are those that do not significantly influence the quality of the fit to experimental data, so-called "sloppy" parameters. The sloppiness can be mathematically expressed through saturating response functions (Hill's, sigmoid) thereby embodying biological mechanisms responsible for the system robustness to external perturbations. However, if a sloppy model is used for the prediction of the system behavior at the altered input (e.g. knock out mutations, natural expression variability), it may demonstrate the poor predictive power due to the ambiguity in the parameter estimates. We introduce a method of the predictive power evaluation under the parameter estimation uncertainty, Relative Sensitivity Analysis. The prediction problem is addressed in the context of gene circuit models describing the dynamics of segmentation gene expression in Drosophila embryo. Gene regulation in these models is introduced by a saturating sigmoid function of the concentrations of the regulatory gene products. We show how our approach can be applied to characterize the essential difference between the sensitivity properties of robust and non-robust solutions and select among the existing solutions those providing the correct system behavior at any reasonable input. In general, the method allows to uncover the sources of incorrect predictions and proposes the way to overcome the estimation uncertainties.
Sensitivity analysis of energy demands on performance of CCHP system
International Nuclear Information System (INIS)
Li, C.Z.; Shi, Y.M.; Huang, X.H.
2008-01-01
Sensitivity analysis of energy demands is carried out in this paper to study their influence on performance of CCHP system. Energy demand is a very important and complex factor in the optimization model of CCHP system. Average, uncertainty and historical peaks are adopted to describe energy demands. The mix-integer nonlinear programming model (MINLP) which can reflect the three aspects of energy demands is established. Numerical studies are carried out based on energy demands of a hotel and a hospital. The influence of average, uncertainty and peaks of energy demands on optimal facility scheme and economic advantages of CCHP system are investigated. The optimization results show that the optimal GT's capacity and economy of CCHP system mainly lie on the average energy demands. Sum of capacities of GB and HE is equal to historical heating demand peaks, and sum of capacities of AR and ER are equal to historical cooling demand peaks. Maximum of PG is sensitive with historical peaks of energy demands and not influenced by uncertainty of energy demands, while the corresponding influence on DH is adverse
Ensemble Solar Forecasting Statistical Quantification and Sensitivity Analysis: Preprint
Energy Technology Data Exchange (ETDEWEB)
Cheung, WanYin; Zhang, Jie; Florita, Anthony; Hodge, Bri-Mathias; Lu, Siyuan; Hamann, Hendrik F.; Sun, Qian; Lehman, Brad
2015-12-08
Uncertainties associated with solar forecasts present challenges to maintain grid reliability, especially at high solar penetrations. This study aims to quantify the errors associated with the day-ahead solar forecast parameters and the theoretical solar power output for a 51-kW solar power plant in a utility area in the state of Vermont, U.S. Forecasts were generated by three numerical weather prediction (NWP) models, including the Rapid Refresh, the High Resolution Rapid Refresh, and the North American Model, and a machine-learning ensemble model. A photovoltaic (PV) performance model was adopted to calculate theoretical solar power generation using the forecast parameters (e.g., irradiance, cell temperature, and wind speed). Errors of the power outputs were quantified using statistical moments and a suite of metrics, such as the normalized root mean squared error (NRMSE). In addition, the PV model's sensitivity to different forecast parameters was quantified and analyzed. Results showed that the ensemble model yielded forecasts in all parameters with the smallest NRMSE. The NRMSE of solar irradiance forecasts of the ensemble NWP model was reduced by 28.10% compared to the best of the three NWP models. Further, the sensitivity analysis indicated that the errors of the forecasted cell temperature attributed only approximately 0.12% to the NRMSE of the power output as opposed to 7.44% from the forecasted solar irradiance.
A Sensitivity Analysis Approach to Identify Key Environmental Performance Factors
Directory of Open Access Journals (Sweden)
Xi Yu
2014-01-01
Full Text Available Life cycle assessment (LCA is widely used in design phase to reduce the product’s environmental impacts through the whole product life cycle (PLC during the last two decades. The traditional LCA is restricted to assessing the environmental impacts of a product and the results cannot reflect the effects of changes within the life cycle. In order to improve the quality of ecodesign, it is a growing need to develop an approach which can reflect the changes between the design parameters and product’s environmental impacts. A sensitivity analysis approach based on LCA and ecodesign is proposed in this paper. The key environmental performance factors which have significant influence on the products’ environmental impacts can be identified by analyzing the relationship between environmental impacts and the design parameters. Users without much environmental knowledge can use this approach to determine which design parameter should be first considered when (redesigning a product. A printed circuit board (PCB case study is conducted; eight design parameters are chosen to be analyzed by our approach. The result shows that the carbon dioxide emission during the PCB manufacture is highly sensitive to the area of PCB panel.
Sensitivity Study on Analysis of Reactor Containment Response to LOCA
International Nuclear Information System (INIS)
Chung, Ku Young; Sung, Key Yong
2010-01-01
As a reactor containment vessel is the final barrier to the release of radioactive material during design basis accidents (DBAs), its structural integrity must be maintained by withstanding the high pressure conditions resulting from DBAs. To verify the structural integrity of the containment, response analyses are performed to get the pressure transient inside the containment after DBAs, including loss of coolant accidents (LOCAs). The purpose of this study is to give regulative insights into the importance of input variables in the analysis of containment responses to a large break LOCA (LBLOCA). For the sensitivity study, a LBLOCA in Kori 3 and 4 nuclear power plant (NPP) is analyzed by CONTEMPT-LT computer code
Sensitivity Study on Analysis of Reactor Containment Response to LOCA
Energy Technology Data Exchange (ETDEWEB)
Chung, Ku Young; Sung, Key Yong [Korea Institute of Nuclear Safety, Daejeon (Korea, Republic of)
2010-10-15
As a reactor containment vessel is the final barrier to the release of radioactive material during design basis accidents (DBAs), its structural integrity must be maintained by withstanding the high pressure conditions resulting from DBAs. To verify the structural integrity of the containment, response analyses are performed to get the pressure transient inside the containment after DBAs, including loss of coolant accidents (LOCAs). The purpose of this study is to give regulative insights into the importance of input variables in the analysis of containment responses to a large break LOCA (LBLOCA). For the sensitivity study, a LBLOCA in Kori 3 and 4 nuclear power plant (NPP) is analyzed by CONTEMPT-LT computer code
Emissivity compensated spectral pyrometry—algorithm and sensitivity analysis
International Nuclear Information System (INIS)
Hagqvist, Petter; Sikström, Fredrik; Christiansson, Anna-Karin; Lennartson, Bengt
2014-01-01
In order to solve the problem of non-contact temperature measurements on an object with varying emissivity, a new method is herein described and evaluated. The method uses spectral radiance measurements and converts them to temperature readings. It proves to be resilient towards changes in spectral emissivity and tolerates noisy spectral measurements. It is based on an assumption of smooth changes in emissivity and uses historical values of spectral emissivity and temperature for estimating current spectral emissivity. The algorithm, its constituent steps and accompanying parameters are described and discussed. A thorough sensitivity analysis of the method is carried out through simulations. No rigorous instrument calibration is needed for the presented method and it is therefore industrially tractable. (paper)
Sensitive Spectroscopic Analysis of Biomarkers in Exhaled Breath
Bicer, A.; Bounds, J.; Zhu, F.; Kolomenskii, A. A.; Kaya, N.; Aluauee, E.; Amani, M.; Schuessler, H. A.
2018-06-01
We have developed a novel optical setup which is based on a high finesse cavity and absorption laser spectroscopy in the near-IR spectral region. In pilot experiments, spectrally resolved absorption measurements of biomarkers in exhaled breath, such as methane and acetone, were carried out using cavity ring-down spectroscopy (CRDS). With a 172-cm-long cavity, an efficient optical path of 132 km was achieved. The CRDS technique is well suited for such measurements due to its high sensitivity and good spectral resolution. The detection limits for methane of 8 ppbv and acetone of 2.1 ppbv with spectral sampling of 0.005 cm-1 were achieved, which allowed to analyze multicomponent gas mixtures and to observe absorption peaks of 12CH4 and 13CH4. Further improvements of the technique have the potential to realize diagnostics of health conditions based on a multicomponent analysis of breath samples.
Sequence length variation, indel costs, and congruence in sensitivity analysis
DEFF Research Database (Denmark)
Aagesen, Lone; Petersen, Gitte; Seberg, Ole
2005-01-01
The behavior of two topological and four character-based congruence measures was explored using different indel treatments in three empirical data sets, each with different alignment difficulties. The analyses were done using direct optimization within a sensitivity analysis framework in which...... the cost of indels was varied. Indels were treated either as a fifth character state, or strings of contiguous gaps were considered single events by using linear affine gap cost. Congruence consistently improved when indels were treated as single events, but no congruence measure appeared as the obviously...... preferable one. However, when combining enough data, all congruence measures clearly tended to select the same alignment cost set as the optimal one. Disagreement among congruence measures was mostly caused by a dominant fragment or a data partition that included all or most of the length variation...
Global sensitivity analysis using low-rank tensor approximations
International Nuclear Information System (INIS)
Konakli, Katerina; Sudret, Bruno
2016-01-01
In the context of global sensitivity analysis, the Sobol' indices constitute a powerful tool for assessing the relative significance of the uncertain input parameters of a model. We herein introduce a novel approach for evaluating these indices at low computational cost, by post-processing the coefficients of polynomial meta-models belonging to the class of low-rank tensor approximations. Meta-models of this class can be particularly efficient in representing responses of high-dimensional models, because the number of unknowns in their general functional form grows only linearly with the input dimension. The proposed approach is validated in example applications, where the Sobol' indices derived from the meta-model coefficients are compared to reference indices, the latter obtained by exact analytical solutions or Monte-Carlo simulation with extremely large samples. Moreover, low-rank tensor approximations are confronted to the popular polynomial chaos expansion meta-models in case studies that involve analytical rank-one functions and finite-element models pertinent to structural mechanics and heat conduction. In the examined applications, indices based on the novel approach tend to converge faster to the reference solution with increasing size of the experimental design used to build the meta-model. - Highlights: • A new method is proposed for global sensitivity analysis of high-dimensional models. • Low-rank tensor approximations (LRA) are used as a meta-modeling technique. • Analytical formulas for the Sobol' indices in terms of LRA coefficients are derived. • The accuracy and efficiency of the approach is illustrated in application examples. • LRA-based indices are compared to indices based on polynomial chaos expansions.
Sensitivity analysis on various parameters for lattice analysis of DUPIC fuel with WIMS-AECL code
Energy Technology Data Exchange (ETDEWEB)
Roh, Gyu Hong; Choi, Hang Bok; Park, Jee Won [Korea Atomic Energy Research Institute, Taejon (Korea, Republic of)
1997-12-31
The code WIMS-AECL has been used for the lattice analysis of DUPIC fuel. The lattice parameters calculated by the code is sensitive to the choice of number of parameters, such as the number of tracking lines, number of condensed groups, mesh spacing in the moderator region, other parameters vital to the calculation of probabilities and burnup analysis. We have studied this sensitivity with respect to these parameters and recommend their proper values which are necessary for carrying out the lattice analysis of DUPIC fuel.
Sensitivity analysis on various parameters for lattice analysis of DUPIC fuel with WIMS-AECL code
Energy Technology Data Exchange (ETDEWEB)
Roh, Gyu Hong; Choi, Hang Bok; Park, Jee Won [Korea Atomic Energy Research Institute, Taejon (Korea, Republic of)
1998-12-31
The code WIMS-AECL has been used for the lattice analysis of DUPIC fuel. The lattice parameters calculated by the code is sensitive to the choice of number of parameters, such as the number of tracking lines, number of condensed groups, mesh spacing in the moderator region, other parameters vital to the calculation of probabilities and burnup analysis. We have studied this sensitivity with respect to these parameters and recommend their proper values which are necessary for carrying out the lattice analysis of DUPIC fuel.
An Overview of the Design and Analysis of Simulation Experiments for Sensitivity Analysis
Kleijnen, J.P.C.
2004-01-01
Sensitivity analysis may serve validation, optimization, and risk analysis of simulation models.This review surveys classic and modern designs for experiments with simulation models.Classic designs were developed for real, non-simulated systems in agriculture, engineering, etc.These designs assume a
Using tree diversity to compare phylogenetic heuristics.
Sul, Seung-Jin; Matthews, Suzanne; Williams, Tiffani L
2009-04-29
Evolutionary trees are family trees that represent the relationships between a group of organisms. Phylogenetic heuristics are used to search stochastically for the best-scoring trees in tree space. Given that better tree scores are believed to be better approximations of the true phylogeny, traditional evaluation techniques have used tree scores to determine the heuristics that find the best scores in the fastest time. We develop new techniques to evaluate phylogenetic heuristics based on both tree scores and topologies to compare Pauprat and Rec-I-DCM3, two popular Maximum Parsimony search algorithms. Our results show that although Pauprat and Rec-I-DCM3 find the trees with the same best scores, topologically these trees are quite different. Furthermore, the Rec-I-DCM3 trees cluster distinctly from the Pauprat trees. In addition to our heatmap visualizations of using parsimony scores and the Robinson-Foulds distance to compare best-scoring trees found by the two heuristics, we also develop entropy-based methods to show the diversity of the trees found. Overall, Pauprat identifies more diverse trees than Rec-I-DCM3. Overall, our work shows that there is value to comparing heuristics beyond the parsimony scores that they find. Pauprat is a slower heuristic than Rec-I-DCM3. However, our work shows that there is tremendous value in using Pauprat to reconstruct trees-especially since it finds identical scoring but topologically distinct trees. Hence, instead of discounting Pauprat, effort should go in improving its implementation. Ultimately, improved performance measures lead to better phylogenetic heuristics and will result in better approximations of the true evolutionary history of the organisms of interest.
Gene selection heuristic algorithm for nutrigenomics studies.
Valour, D; Hue, I; Grimard, B; Valour, B
2013-07-15
Large datasets from -omics studies need to be deeply investigated. The aim of this paper is to provide a new method (LEM method) for the search of transcriptome and metabolome connections. The heuristic algorithm here described extends the classical canonical correlation analysis (CCA) to a high number of variables (without regularization) and combines well-conditioning and fast-computing in "R." Reduced CCA models are summarized in PageRank matrices, the product of which gives a stochastic matrix that resumes the self-avoiding walk covered by the algorithm. Then, a homogeneous Markov process applied to this stochastic matrix converges the probabilities of interconnection between genes, providing a selection of disjointed subsets of genes. This is an alternative to regularized generalized CCA for the determination of blocks within the structure matrix. Each gene subset is thus linked to the whole metabolic or clinical dataset that represents the biological phenotype of interest. Moreover, this selection process reaches the aim of biologists who often need small sets of genes for further validation or extended phenotyping. The algorithm is shown to work efficiently on three published datasets, resulting in meaningfully broadened gene networks.
Tuning Parameters in Heuristics by Using Design of Experiments Methods
Arin, Arif; Rabadi, Ghaith; Unal, Resit
2010-01-01
With the growing complexity of today's large scale problems, it has become more difficult to find optimal solutions by using exact mathematical methods. The need to find near-optimal solutions in an acceptable time frame requires heuristic approaches. In many cases, however, most heuristics have several parameters that need to be "tuned" before they can reach good results. The problem then turns into "finding best parameter setting" for the heuristics to solve the problems efficiently and timely. One-Factor-At-a-Time (OFAT) approach for parameter tuning neglects the interactions between parameters. Design of Experiments (DOE) tools can be instead employed to tune the parameters more effectively. In this paper, we seek the best parameter setting for a Genetic Algorithm (GA) to solve the single machine total weighted tardiness problem in which n jobs must be scheduled on a single machine without preemption, and the objective is to minimize the total weighted tardiness. Benchmark instances for the problem are available in the literature. To fine tune the GA parameters in the most efficient way, we compare multiple DOE models including 2-level (2k ) full factorial design, orthogonal array design, central composite design, D-optimal design and signal-to-noise (SIN) ratios. In each DOE method, a mathematical model is created using regression analysis, and solved to obtain the best parameter setting. After verification runs using the tuned parameter setting, the preliminary results for optimal solutions of multiple instances were found efficiently.
Multiobjective hyper heuristic scheme for system design and optimization
Rafique, Amer Farhan
2012-11-01
As system design is becoming more and more multifaceted, integrated, and complex, the traditional single objective optimization trends of optimal design are becoming less and less efficient and effective. Single objective optimization methods present a unique optimal solution whereas multiobjective methods present pareto front. The foremost intent is to predict a reasonable distributed pareto-optimal solution set independent of the problem instance through multiobjective scheme. Other objective of application of intended approach is to improve the worthiness of outputs of the complex engineering system design process at the conceptual design phase. The process is automated in order to provide the system designer with the leverage of the possibility of studying and analyzing a large multiple of possible solutions in a short time. This article presents Multiobjective Hyper Heuristic Optimization Scheme based on low level meta-heuristics developed for the application in engineering system design. Herein, we present a stochastic function to manage meta-heuristics (low-level) to augment surety of global optimum solution. Generic Algorithm, Simulated Annealing and Swarm Intelligence are used as low-level meta-heuristics in this study. Performance of the proposed scheme is investigated through a comprehensive empirical analysis yielding acceptable results. One of the primary motives for performing multiobjective optimization is that the current engineering systems require simultaneous optimization of conflicting and multiple. Random decision making makes the implementation of this scheme attractive and easy. Injecting feasible solutions significantly alters the search direction and also adds diversity of population resulting in accomplishment of pre-defined goals set in the proposed scheme.
Prediction-based dynamic load-sharing heuristics
Goswami, Kumar K.; Devarakonda, Murthy; Iyer, Ravishankar K.
1993-01-01
The authors present dynamic load-sharing heuristics that use predicted resource requirements of processes to manage workloads in a distributed system. A previously developed statistical pattern-recognition method is employed for resource prediction. While nonprediction-based heuristics depend on a rapidly changing system status, the new heuristics depend on slowly changing program resource usage patterns. Furthermore, prediction-based heuristics can be more effective since they use future requirements rather than just the current system state. Four prediction-based heuristics, two centralized and two distributed, are presented. Using trace driven simulations, they are compared against random scheduling and two effective nonprediction based heuristics. Results show that the prediction-based centralized heuristics achieve up to 30 percent better response times than the nonprediction centralized heuristic, and that the prediction-based distributed heuristics achieve up to 50 percent improvements relative to their nonprediction counterpart.
Relative performance of academic departments using DEA with sensitivity analysis.
Tyagi, Preeti; Yadav, Shiv Prasad; Singh, S P
2009-05-01
The process of liberalization and globalization of Indian economy has brought new opportunities and challenges in all areas of human endeavor including education. Educational institutions have to adopt new strategies to make best use of the opportunities and counter the challenges. One of these challenges is how to assess the performance of academic programs based on multiple criteria. Keeping this in view, this paper attempts to evaluate the performance efficiencies of 19 academic departments of IIT Roorkee (India) through data envelopment analysis (DEA) technique. The technique has been used to assess the performance of academic institutions in a number of countries like USA, UK, Australia, etc. But we are using it first time in Indian context to the best of our knowledge. Applying DEA models, we calculate technical, pure technical and scale efficiencies and identify the reference sets for inefficient departments. Input and output projections are also suggested for inefficient departments to reach the frontier. Overall performance, research performance and teaching performance are assessed separately using sensitivity analysis.
Directory of Open Access Journals (Sweden)
G. Esteve-Asensio
2009-01-01
Full Text Available We propose and compare three novel heuristics for the calculation of the optimal cell radius in mobile networks based on Wideband Code Division Multiple Access (WCDMA technology. The proposed heuristics solve the problem of the load assignment and cellular radius calculation. We have tested our approaches with experiments in multiservices scenarios showing that the proposed heuristics maximize the cell radius, providing the optimum load factor assignment. The main application of these algorithms is strategic planning studies, where an estimation of the number of Nodes B of the mobile operator, at a national level, is required for economic analysis. In this case due to the large number of different scenarios considered (cities, towns, and open areas other methods than simulation need to be considered. As far as we know, there is no other similar method in the literature and therefore these heuristics may represent a novelty in strategic network planning studies. The proposed heuristics are implemented in a strategic planning software tool and an example of their application for a case in Spain is presented. The proposed heuristics are used for telecommunications regulatory studies in several countries.
Quantifying Heuristic Bias: Anchoring, Availability, and Representativeness.
Richie, Megan; Josephson, S Andrew
2018-01-01
Construct: Authors examined whether a new vignette-based instrument could isolate and quantify heuristic bias. Heuristics are cognitive shortcuts that may introduce bias and contribute to error. There is no standardized instrument available to quantify heuristic bias in clinical decision making, limiting future study of educational interventions designed to improve calibration of medical decisions. This study presents validity data to support a vignette-based instrument quantifying bias due to the anchoring, availability, and representativeness heuristics. Participants completed questionnaires requiring assignment of probabilities to potential outcomes of medical and nonmedical scenarios. The instrument randomly presented scenarios in one of two versions: Version A, encouraging heuristic bias, and Version B, worded neutrally. The primary outcome was the difference in probability judgments for Version A versus Version B scenario options. Of 167 participants recruited, 139 enrolled. Participants assigned significantly higher mean probability values to Version A scenario options (M = 9.56, SD = 3.75) than Version B (M = 8.98, SD = 3.76), t(1801) = 3.27, p = .001. This result remained significant analyzing medical scenarios alone (Version A, M = 9.41, SD = 3.92; Version B, M = 8.86, SD = 4.09), t(1204) = 2.36, p = .02. Analyzing medical scenarios by heuristic revealed a significant difference between Version A and B for availability (Version A, M = 6.52, SD = 3.32; Version B, M = 5.52, SD = 3.05), t(404) = 3.04, p = .003, and representativeness (Version A, M = 11.45, SD = 3.12; Version B, M = 10.67, SD = 3.71), t(396) = 2.28, p = .02, but not anchoring. Stratifying by training level, students maintained a significant difference between Version A and B medical scenarios (Version A, M = 9.83, SD = 3.75; Version B, M = 9.00, SD = 3.98), t(465) = 2.29, p = .02, but not residents or attendings. Stratifying by heuristic and training level, availability maintained
PDASAC, Partial Differential Sensitivity Analysis of Stiff System
International Nuclear Information System (INIS)
Caracotsios, M.; Stewart, W.E.
2001-01-01
1 - Description of program or function: PDASAC solves stiff, nonlinear initial-boundary-value problems in a timelike dimension t and a space dimension x. Plane, circular cylindrical or spherical boundaries can be handled. Mixed-order systems of partial differential and algebraic equations can be analyzed with members of order or 0 or 1 in t, 0, 1 or 2 in x. Parametric sensitivities of the calculated states are computed simultaneously on request, via the Jacobian of the state equations. Initial and boundary conditions are efficiently reconciled. Local error control (in the max-norm or the 2-norm) is provided for the state vector and can include the parametric sensitivities if desired. 2 - Method of solution: The method of lines is used, with a user- selected x-grid and a minimum-bandwidth finite-difference approximations of the x-derivatives. Starting conditions are reconciled with a damped Newton algorithm adapted from Bain and Stewart (1991). Initial step selection is done by the first-order algorithms of Shampine (1987), extended here to differential- algebraic equation systems. The solution is continued with the DASSL predictor-corrector algorithm (Petzold 1983, Brenan et al. 1989) with the initial acceleration phase deleted and with row scaling of the Jacobian added. The predictor and corrector are expressed in divided-difference form, with the fixed-leading-coefficient form of corrector (Jackson and Sacks-Davis 1989; Brenan et al. 1989). Weights for the error tests are updated in each step with the user's tolerances at the predicted state. Sensitivity analysis is performed directly on the corrector equations of Caracotsios and Stewart (1985) and is extended here to the initialization when needed. 3 - Restrictions on the complexity of the problem: This algorithm, like DASSL, performs well on differential-algebraic equation systems of index 0 and 1 but not on higher-index systems; see Brenan et al. (1989). The user assigned the work array lengths and the output
Sensitivity Analysis for Steady State Groundwater Flow Using Adjoint Operators
Sykes, J. F.; Wilson, J. L.; Andrews, R. W.
1985-03-01
Adjoint sensitivity theory is currently being considered as a potential method for calculating the sensitivity of nuclear waste repository performance measures to the parameters of the system. For groundwater flow systems, performance measures of interest include piezometric heads in the vicinity of a waste site, velocities or travel time in aquifers, and mass discharge to biosphere points. The parameters include recharge-discharge rates, prescribed boundary heads or fluxes, formation thicknesses, and hydraulic conductivities. The derivative of a performance measure with respect to the system parameters is usually taken as a measure of sensitivity. To calculate sensitivities, adjoint sensitivity equations are formulated from the equations describing the primary problem. The solution of the primary problem and the adjoint sensitivity problem enables the determination of all of the required derivatives and hence related sensitivity coefficients. In this study, adjoint sensitivity theory is developed for equations of two-dimensional steady state flow in a confined aquifer. Both the primary flow equation and the adjoint sensitivity equation are solved using the Galerkin finite element method. The developed computer code is used to investigate the regional flow parameters of the Leadville Formation of the Paradox Basin in Utah. The results illustrate the sensitivity of calculated local heads to the boundary conditions. Alternatively, local velocity related performance measures are more sensitive to hydraulic conductivities.
Energy Technology Data Exchange (ETDEWEB)
Shrivastava, Manish [Pacific Northwest National Laboratory, Richland Washington USA; Zhao, Chun [Pacific Northwest National Laboratory, Richland Washington USA; Easter, Richard C. [Pacific Northwest National Laboratory, Richland Washington USA; Qian, Yun [Pacific Northwest National Laboratory, Richland Washington USA; Zelenyuk, Alla [Pacific Northwest National Laboratory, Richland Washington USA; Fast, Jerome D. [Pacific Northwest National Laboratory, Richland Washington USA; Liu, Ying [Pacific Northwest National Laboratory, Richland Washington USA; Zhang, Qi [Department of Environmental Toxicology, University of California Davis, California USA; Guenther, Alex [Department of Earth System Science, University of California, Irvine California USA
2016-04-08
We investigate the sensitivity of secondary organic aerosol (SOA) loadings simulated by a regional chemical transport model to 7 selected tunable model parameters: 4 involving emissions of anthropogenic and biogenic volatile organic compounds, anthropogenic semi-volatile and intermediate volatility organics (SIVOCs), and NOx, 2 involving dry deposition of SOA precursor gases, and one involving particle-phase transformation of SOA to low volatility. We adopt a quasi-Monte Carlo sampling approach to effectively sample the high-dimensional parameter space, and perform a 250 member ensemble of simulations using a regional model, accounting for some of the latest advances in SOA treatments based on our recent work. We then conduct a variance-based sensitivity analysis using the generalized linear model method to study the responses of simulated SOA loadings to the tunable parameters. Analysis of SOA variance from all 250 simulations shows that the volatility transformation parameter, which controls whether particle-phase transformation of SOA from semi-volatile SOA to non-volatile is on or off, is the dominant contributor to variance of simulated surface-level daytime SOA (65% domain average contribution). We also split the simulations into 2 subsets of 125 each, depending on whether the volatility transformation is turned on/off. For each subset, the SOA variances are dominated by the parameters involving biogenic VOC and anthropogenic SIVOC emissions. Furthermore, biogenic VOC emissions have a larger contribution to SOA variance when the SOA transformation to non-volatile is on, while anthropogenic SIVOC emissions have a larger contribution when the transformation is off. NOx contributes less than 4.3% to SOA variance, and this low contribution is mainly attributed to dominance of intermediate to high NOx conditions throughout the simulated domain. The two parameters related to dry deposition of SOA precursor gases also have very low contributions to SOA variance
An Application of Monte-Carlo-Based Sensitivity Analysis on the Overlap in Discriminant Analysis
Directory of Open Access Journals (Sweden)
S. Razmyan
2012-01-01
Full Text Available Discriminant analysis (DA is used for the measurement of estimates of a discriminant function by minimizing their group misclassifications to predict group membership of newly sampled data. A major source of misclassification in DA is due to the overlapping of groups. The uncertainty in the input variables and model parameters needs to be properly characterized in decision making. This study combines DEA-DA with a sensitivity analysis approach to an assessment of the influence of banks’ variables on the overall variance in overlap in a DA in order to determine which variables are most significant. A Monte-Carlo-based sensitivity analysis is considered for computing the set of first-order sensitivity indices of the variables to estimate the contribution of each uncertain variable. The results show that the uncertainties in the loans granted and different deposit variables are more significant than uncertainties in other banks’ variables in decision making.
Sensitivity analysis of alkaline plume modelling: influence of mineralogy
International Nuclear Information System (INIS)
Gaboreau, S.; Claret, F.; Marty, N.; Burnol, A.; Tournassat, C.; Gaucher, E.C.; Munier, I.; Michau, N.; Cochepin, B.
2010-01-01
Document available in extended abstract form only. In the context of a disposal facility for radioactive waste in clayey geological formation, an important modelling effort has been carried out in order to predict the time evolution of interacting cement based (concrete or cement) and clay (argillites and bentonite) materials. The high number of modelling input parameters associated with non negligible uncertainties makes often difficult the interpretation of modelling results. As a consequence, it is necessary to carry out sensitivity analysis on main modelling parameters. In a recent study, Marty et al. (2009) could demonstrate that numerical mesh refinement and consideration of dissolution/precipitation kinetics have a marked effect on (i) the time necessary to numerically clog the initial porosity and (ii) on the final mineral assemblage at the interface. On the contrary, these input parameters have little effect on the extension of the alkaline pH plume. In the present study, we propose to investigate the effects of the considered initial mineralogy on the principal simulation outputs: (1) the extension of the high pH plume, (2) the time to clog the porosity and (3) the alteration front in the clay barrier (extension and nature of mineralogy changes). This was done through sensitivity analysis on both concrete composition and clay mineralogical assemblies since in most published studies, authors considered either only one composition per materials or simplified mineralogy in order to facilitate or to reduce their calculation times. 1D Cartesian reactive transport models were run in order to point out the importance of (1) the crystallinity of concrete phases, (2) the type of clayey materials and (3) the choice of secondary phases that are allowed to precipitate during calculations. Two concrete materials with either nanocrystalline or crystalline phases were simulated in contact with two clayey materials (smectite MX80 or Callovo- Oxfordian argillites). Both
Can we trust module-respect heuristics?
International Nuclear Information System (INIS)
Mo, Yuchang
2013-01-01
BDD (Binary Decision Diagrams) have proven to be a very efficient tool to assess Fault Trees. However, the size of BDD, and therefore the efficiency of the whole methodology, depends dramatically on the choice of variable ordering. The determination of the best variable ordering is intractable. Therefore, heuristics have been designed to select reasonably good variable orderings. One very important common feature for good static heuristics is to respect modules. In this paper, the notion of module-respect is studied in a systematic way. It is proved that under certain condition there always exists an optimal ordering that respects modules. This condition is that for each module there is always a smallest module BDD and each included module variable appears only once. On the other hand, it is shown that for the trees not satisfying the above sufficient condition the optimal orderings may not be able to be directly generated using module-respect heuristics, even when the shuffling strategy is used.
Judgment under Uncertainty: Heuristics and Biases.
Tversky, A; Kahneman, D
1974-09-27
This article described three heuristics that are employed in making judgements under uncertainty: (i) representativeness, which is usually employed when people are asked to judge the probability that an object or event A belongs to class or process B; (ii) availability of instances or scenarios, which is often employed when people are asked to assess the frequency of a class or the plausibility of a particular development; and (iii) adjustment from an anchor, which is usually employed in numerical prediction when a relevant value is available. These heuristics are highly economical and usually effective, but they lead to systematic and predictable errors. A better understanding of these heuristics and of the biases to which they lead could improve judgements and decisions in situations of uncertainty.
International Nuclear Information System (INIS)
Heo, Jaeseok; Kim, Kyung Doo
2015-01-01
Statistical approaches to uncertainty quantification and sensitivity analysis are very important in estimating the safety margins for an engineering design application. This paper presents a system analysis and optimization toolkit developed by Korea Atomic Energy Research Institute (KAERI), which includes multiple packages of the sensitivity analysis and uncertainty quantification algorithms. In order to reduce the computing demand, multiple compute resources including multiprocessor computers and a network of workstations are simultaneously used. A Graphical User Interface (GUI) was also developed within the parallel computing framework for users to readily employ the toolkit for an engineering design and optimization problem. The goal of this work is to develop a GUI framework for engineering design and scientific analysis problems by implementing multiple packages of system analysis methods in the parallel computing toolkit. This was done by building an interface between an engineering simulation code and the system analysis software packages. The methods and strategies in the framework were designed to exploit parallel computing resources such as those found in a desktop multiprocessor workstation or a network of workstations. Available approaches in the framework include statistical and mathematical algorithms for use in science and engineering design problems. Currently the toolkit has 6 modules of the system analysis methodologies: deterministic and probabilistic approaches of data assimilation, uncertainty propagation, Chi-square linearity test, sensitivity analysis, and FFTBM
Energy Technology Data Exchange (ETDEWEB)
Heo, Jaeseok; Kim, Kyung Doo [KAERI, Daejeon (Korea, Republic of)
2015-05-15
Statistical approaches to uncertainty quantification and sensitivity analysis are very important in estimating the safety margins for an engineering design application. This paper presents a system analysis and optimization toolkit developed by Korea Atomic Energy Research Institute (KAERI), which includes multiple packages of the sensitivity analysis and uncertainty quantification algorithms. In order to reduce the computing demand, multiple compute resources including multiprocessor computers and a network of workstations are simultaneously used. A Graphical User Interface (GUI) was also developed within the parallel computing framework for users to readily employ the toolkit for an engineering design and optimization problem. The goal of this work is to develop a GUI framework for engineering design and scientific analysis problems by implementing multiple packages of system analysis methods in the parallel computing toolkit. This was done by building an interface between an engineering simulation code and the system analysis software packages. The methods and strategies in the framework were designed to exploit parallel computing resources such as those found in a desktop multiprocessor workstation or a network of workstations. Available approaches in the framework include statistical and mathematical algorithms for use in science and engineering design problems. Currently the toolkit has 6 modules of the system analysis methodologies: deterministic and probabilistic approaches of data assimilation, uncertainty propagation, Chi-square linearity test, sensitivity analysis, and FFTBM.
ECOS - analysis of sensitivity to database and input parameters
International Nuclear Information System (INIS)
Sumerling, T.J.; Jones, C.H.
1986-06-01
The sensitivity of doses calculated by the generic biosphere code ECOS to parameter changes has been investigated by the authors for the Department of the Environment as part of its radioactive waste management research programme. The sensitivity of results to radionuclide dependent parameters has been tested by specifying reasonable parameter ranges and performing code runs for best estimate, upper-bound and lower-bound parameter values. The work indicates that doses are most sensitive to scenario parameters: geosphere input fractions, area of contaminated land, land use and diet, flux of contaminated waters and water use. Recommendations are made based on the results of sensitivity. (author)
Intelligent System Design Using Hyper-Heuristics
Directory of Open Access Journals (Sweden)
Nelishia Pillay
2015-07-01
Full Text Available Determining the most appropriate search method or artificial intelligence technique to solve a problem is not always evident and usually requires implementation of the different approaches to ascertain this. In some instances a single approach may not be sufficient and hybridization of methods may be needed to find a solution. This process can be time consuming. The paper proposes the use of hyper-heuristics as a means of identifying which method or combination of approaches is needed to solve a problem. The research presented forms part of a larger initiative aimed at using hyper-heuristics to develop intelligent hybrid systems. As an initial step in this direction, this paper investigates this for classical artificial intelligence uninformed and informed search methods, namely depth first search, breadth first search, best first search, hill-climbing and the A* algorithm. The hyper-heuristic determines the search or combination of searches to use to solve the problem. An evolutionary algorithm hyper-heuristic is implemented for this purpose and its performance is evaluated in solving the 8-Puzzle, Towers of Hanoi and Blocks World problems. The hyper-heuristic employs a generational evolutionary algorithm which iteratively refines an initial population using tournament selection to select parents, which the mutation and crossover operators are applied to for regeneration. The hyper-heuristic was able to identify a search or combination of searches to produce solutions for the twenty 8-Puzzle, five Towers of Hanoi and five Blocks World problems. Furthermore, admissible solutions were produced for all problem instances.
A Sensitivity Analysis of fMRI Balloon Model
Zayane, Chadia
2015-04-22
Functional magnetic resonance imaging (fMRI) allows the mapping of the brain activation through measurements of the Blood Oxygenation Level Dependent (BOLD) contrast. The characterization of the pathway from the input stimulus to the output BOLD signal requires the selection of an adequate hemodynamic model and the satisfaction of some specific conditions while conducting the experiment and calibrating the model. This paper, focuses on the identifiability of the Balloon hemodynamic model. By identifiability, we mean the ability to estimate accurately the model parameters given the input and the output measurement. Previous studies of the Balloon model have somehow added knowledge either by choosing prior distributions for the parameters, freezing some of them, or looking for the solution as a projection on a natural basis of some vector space. In these studies, the identification was generally assessed using event-related paradigms. This paper justifies the reasons behind the need of adding knowledge, choosing certain paradigms, and completing the few existing identifiability studies through a global sensitivity analysis of the Balloon model in the case of blocked design experiment.
Methods and computer codes for probabilistic sensitivity and uncertainty analysis
International Nuclear Information System (INIS)
Vaurio, J.K.
1985-01-01
This paper describes the methods and applications experience with two computer codes that are now available from the National Energy Software Center at Argonne National Laboratory. The purpose of the SCREEN code is to identify a group of most important input variables of a code that has many (tens, hundreds) input variables with uncertainties, and do this without relying on judgment or exhaustive sensitivity studies. Purpose of the PROSA-2 code is to propagate uncertainties and calculate the distributions of interesting output variable(s) of a safety analysis code using response surface techniques, based on the same runs used for screening. Several applications are discussed, but the codes are generic, not tailored to any specific safety application code. They are compatible in terms of input/output requirements but also independent of each other, e.g., PROSA-2 can be used without first using SCREEN if a set of important input variables has first been selected by other methods. Also, although SCREEN can select cases to be run (by random sampling), a user can select cases by other methods if he so prefers, and still use the rest of SCREEN for identifying important input variables
Nonparametric Bounds and Sensitivity Analysis of Treatment Effects
Richardson, Amy; Hudgens, Michael G.; Gilbert, Peter B.; Fine, Jason P.
2015-01-01
This paper considers conducting inference about the effect of a treatment (or exposure) on an outcome of interest. In the ideal setting where treatment is assigned randomly, under certain assumptions the treatment effect is identifiable from the observable data and inference is straightforward. However, in other settings such as observational studies or randomized trials with noncompliance, the treatment effect is no longer identifiable without relying on untestable assumptions. Nonetheless, the observable data often do provide some information about the effect of treatment, that is, the parameter of interest is partially identifiable. Two approaches are often employed in this setting: (i) bounds are derived for the treatment effect under minimal assumptions, or (ii) additional untestable assumptions are invoked that render the treatment effect identifiable and then sensitivity analysis is conducted to assess how inference about the treatment effect changes as the untestable assumptions are varied. Approaches (i) and (ii) are considered in various settings, including assessing principal strata effects, direct and indirect effects and effects of time-varying exposures. Methods for drawing formal inference about partially identified parameters are also discussed. PMID:25663743
Impact Responses and Parameters Sensitivity Analysis of Electric Wheelchairs
Directory of Open Access Journals (Sweden)
Song Wang
2018-06-01
Full Text Available The shock and vibration of electric wheelchairs undergoing road irregularities is inevitable. The road excitation causes the uneven magnetic gap of the motor, and the harmful vibration decreases the recovery rate of rehabilitation patients. To effectively suppress the shock and vibration, this paper introduces the DA (dynamic absorber to the electric wheelchair. Firstly, a vibration model of the human-wheelchair system with the DA was created. The models of the road excitation for wheelchairs going up a step and going down a step were proposed, respectively. To reasonably evaluate the impact level of the human-wheelchair system undergoing the step–road transition, evaluation indexes were given. Moreover, the created vibration model and the road–step model were validated via tests. Then, to reveal the vibration suppression performance of the DA, the impact responses and the amplitude frequency characteristics were numerically simulated and compared. Finally, a sensitivity analysis of the impact responses to the tire static radius r and the characteristic parameters was carried out. The results show that the DA can effectively suppress the shock and vibration of the human-wheelchair system. Moreover, for the electric wheelchair going up a step and going down a step, there are some differences in the vibration behaviors.
A Sensitivity Analysis of fMRI Balloon Model
Zayane, Chadia; Laleg-Kirati, Taous-Meriem
2015-01-01
Functional magnetic resonance imaging (fMRI) allows the mapping of the brain activation through measurements of the Blood Oxygenation Level Dependent (BOLD) contrast. The characterization of the pathway from the input stimulus to the output BOLD signal requires the selection of an adequate hemodynamic model and the satisfaction of some specific conditions while conducting the experiment and calibrating the model. This paper, focuses on the identifiability of the Balloon hemodynamic model. By identifiability, we mean the ability to estimate accurately the model parameters given the input and the output measurement. Previous studies of the Balloon model have somehow added knowledge either by choosing prior distributions for the parameters, freezing some of them, or looking for the solution as a projection on a natural basis of some vector space. In these studies, the identification was generally assessed using event-related paradigms. This paper justifies the reasons behind the need of adding knowledge, choosing certain paradigms, and completing the few existing identifiability studies through a global sensitivity analysis of the Balloon model in the case of blocked design experiment.
Sensitivity analysis on parameters and processes affecting vapor intrusion risk
Picone, Sara
2012-03-30
A one-dimensional numerical model was developed and used to identify the key processes controlling vapor intrusion risks by means of a sensitivity analysis. The model simulates the fate of a dissolved volatile organic compound present below the ventilated crawl space of a house. In contrast to the vast majority of previous studies, this model accounts for vertical variation of soil water saturation and includes aerobic biodegradation. The attenuation factor (ratio between concentration in the crawl space and source concentration) and the characteristic time to approach maximum concentrations were calculated and compared for a variety of scenarios. These concepts allow an understanding of controlling mechanisms and aid in the identification of critical parameters to be collected for field situations. The relative distance of the source to the nearest gas-filled pores of the unsaturated zone is the most critical parameter because diffusive contaminant transport is significantly slower in water-filled pores than in gas-filled pores. Therefore, attenuation factors decrease and characteristic times increase with increasing relative distance of the contaminant dissolved source to the nearest gas diffusion front. Aerobic biodegradation may decrease the attenuation factor by up to three orders of magnitude. Moreover, the occurrence of water table oscillations is of importance. Dynamic processes leading to a retreating water table increase the attenuation factor by two orders of magnitude because of the enhanced gas phase diffusion. © 2012 SETAC.
Sensitivity study of CFD turbulent models for natural convection analysis
International Nuclear Information System (INIS)
Yu sun, Park
2007-01-01
The buoyancy driven convective flow fields are steady circulatory flows which were made between surfaces maintained at two fixed temperatures. They are ubiquitous in nature and play an important role in many engineering applications. Application of a natural convection can reduce the costs and efforts remarkably. This paper focuses on the sensitivity study of turbulence analysis using CFD (Computational Fluid Dynamics) for a natural convection in a closed rectangular cavity. Using commercial CFD code, FLUENT and various turbulent models were applied to the turbulent flow. Results from each CFD model will be compared each other in the viewpoints of grid resolution and flow characteristics. It has been showed that: -) obtaining general flow characteristics is possible with relatively coarse grid; -) there is no significant difference between results from finer grid resolutions than grid with y + + is defined as y + = ρ*u*y/μ, u being the wall friction velocity, y being the normal distance from the center of the cell to the wall, ρ and μ being respectively the fluid density and the fluid viscosity; -) the K-ε models show a different flow characteristic from K-ω models or from the Reynolds Stress Model (RSM); and -) the y + parameter is crucial for the selection of the appropriate turbulence model to apply within the simulation
Multi-scale sensitivity analysis of pile installation using DEM
Esposito, Ricardo Gurevitz; Velloso, Raquel Quadros; , Eurípedes do Amaral Vargas, Jr.; Danziger, Bernadete Ragoni
2017-12-01
The disturbances experienced by the soil due to the pile installation and dynamic soil-structure interaction still present major challenges to foundation engineers. These phenomena exhibit complex behaviors, difficult to measure in physical tests and to reproduce in numerical models. Due to the simplified approach used by the discrete element method (DEM) to simulate large deformations and nonlinear stress-dilatancy behavior of granular soils, the DEM consists of an excellent tool to investigate these processes. This study presents a sensitivity analysis of the effects of introducing a single pile using the PFC2D software developed by Itasca Co. The different scales investigated in these simulations include point and shaft resistance, alterations in porosity and stress fields and particles displacement. Several simulations were conducted in order to investigate the effects of different numerical approaches showing indications that the method of installation and particle rotation could influence greatly in the conditions around the numerical pile. Minor effects were also noted due to change in penetration velocity and pile-soil friction. The difference in behavior of a moving and a stationary pile shows good qualitative agreement with previous experimental results indicating the necessity of realizing a force equilibrium process prior to any load-test to be simulated.
Sensitivity Analysis for the CLIC Damping Ring Inductive Adder
Holma, Janne
2012-01-01
The CLIC study is exploring the scheme for an electron-positron collider with high luminosity and a nominal centre-of-mass energy of 3 TeV. The CLIC pre-damping rings and damping rings will produce, through synchrotron radiation, ultra-low emittance beam with high bunch charge, necessary for the luminosity performance of the collider. To limit the beam emittance blow-up due to oscillations, the pulse generators for the damping ring kickers must provide extremely flat, high-voltage pulses. The specifications for the extraction kickers of the CLIC damping rings are particularly demanding: the flattop of the output pulse must be 160 ns duration, 12.5 kV and 250 A, with a combined ripple and droop of not more than ±0.02 %. An inductive adder allows the use of different modulation techniques and is therefore a very promising approach to meeting the specifications. PSpice has been utilised to carry out a sensitivity analysis of the predicted output pulse to the value of both individual and groups of circuit compon...
Heuristics for container loading of furniture
DEFF Research Database (Denmark)
Egeblad, Jens; Garavelli, Claudio; Lisi, Stefano
2010-01-01
. In the studied company, the problem arises hundreds of times daily during transport planning. Instances may contain more than one hundred different items with irregular shapes. To solve this complex problem we apply a set of heuristics successively that each solve one part of the problem. Large items...... are combined in specific structures to ensure proper protection of the items during transportation and to simplify the problem. The solutions generated by the heuristic has an average loading utilization of 91.3% for the most general instances with average running times around 100 seconds....
Heuristic extension of the Schwarzschild metric
International Nuclear Information System (INIS)
Espinosa, J.M.
1982-01-01
The Schwarzschild solution of Einstein's equations of gravitation has several singularities. It is known that the singularity at r = 2Gm/c 2 is only apparent, a result of the coordinates in which the solution was found. Paradoxical results occuring near the singularity show the system of coordinates is incomplete. We introduce a simple, two-dimensional metric with an apparent singularity that makes it incomplete. By a straightforward, heuristic procedure we extend and complete this simple metric. We then use the same procedure to give a heuristic derivation of the Kruskal system of coordinates, which is known to extend the Schwarzschild manifold past its apparent singularity and produce a complete manifold
Age Effects and Heuristics in Decision Making.
Besedeš, Tibor; Deck, Cary; Sarangi, Sudipta; Shor, Mikhael
2012-05-01
Using controlled experiments, we examine how individuals make choices when faced with multiple options. Choice tasks are designed to mimic the selection of health insurance, prescription drug, or retirement savings plans. In our experiment, available options can be objectively ranked allowing us to examine optimal decision making. First, the probability of a person selecting the optimal option declines as the number of options increases, with the decline being more pronounced for older subjects. Second, heuristics differ by age with older subjects relying more on suboptimal decision rules. In a heuristics validation experiment, older subjects make worse decisions than younger subjects.
From Metaphors to Formalism: A Heuristic Approach to Holistic Assessments of Ecosystem Health.
Fock, Heino O; Kraus, Gerd
2016-01-01
Environmental policies employ metaphoric objectives such as ecosystem health, resilience and sustainable provision of ecosystem services, which influence corresponding sustainability assessments by means of normative settings such as assumptions on system description, indicator selection, aggregation of information and target setting. A heuristic approach is developed for sustainability assessments to avoid ambiguity and applications to the EU Marine Strategy Framework Directive (MSFD) and OSPAR assessments are presented. For MSFD, nineteen different assessment procedures have been proposed, but at present no agreed assessment procedure is available. The heuristic assessment framework is a functional-holistic approach comprising an ex-ante/ex-post assessment framework with specifically defined normative and systemic dimensions (EAEPNS). The outer normative dimension defines the ex-ante/ex-post framework, of which the latter branch delivers one measure of ecosystem health based on indicators and the former allows to account for the multi-dimensional nature of sustainability (social, economic, ecological) in terms of modeling approaches. For MSFD, the ex-ante/ex-post framework replaces the current distinction between assessments based on pressure and state descriptors. The ex-ante and the ex-post branch each comprise an inner normative and a systemic dimension. The inner normative dimension in the ex-post branch considers additive utility models and likelihood functions to standardize variables normalized with Bayesian modeling. Likelihood functions allow precautionary target setting. The ex-post systemic dimension considers a posteriori indicator selection by means of analysis of indicator space to avoid redundant indicator information as opposed to a priori indicator selection in deconstructive-structural approaches. Indicator information is expressed in terms of ecosystem variability by means of multivariate analysis procedures. The application to the OSPAR
From Metaphors to Formalism: A Heuristic Approach to Holistic Assessments of Ecosystem Health
Kraus, Gerd
2016-01-01
Environmental policies employ metaphoric objectives such as ecosystem health, resilience and sustainable provision of ecosystem services, which influence corresponding sustainability assessments by means of normative settings such as assumptions on system description, indicator selection, aggregation of information and target setting. A heuristic approach is developed for sustainability assessments to avoid ambiguity and applications to the EU Marine Strategy Framework Directive (MSFD) and OSPAR assessments are presented. For MSFD, nineteen different assessment procedures have been proposed, but at present no agreed assessment procedure is available. The heuristic assessment framework is a functional-holistic approach comprising an ex-ante/ex-post assessment framework with specifically defined normative and systemic dimensions (EAEPNS). The outer normative dimension defines the ex-ante/ex-post framework, of which the latter branch delivers one measure of ecosystem health based on indicators and the former allows to account for the multi-dimensional nature of sustainability (social, economic, ecological) in terms of modeling approaches. For MSFD, the ex-ante/ex-post framework replaces the current distinction between assessments based on pressure and state descriptors. The ex-ante and the ex-post branch each comprise an inner normative and a systemic dimension. The inner normative dimension in the ex-post branch considers additive utility models and likelihood functions to standardize variables normalized with Bayesian modeling. Likelihood functions allow precautionary target setting. The ex-post systemic dimension considers a posteriori indicator selection by means of analysis of indicator space to avoid redundant indicator information as opposed to a priori indicator selection in deconstructive-structural approaches. Indicator information is expressed in terms of ecosystem variability by means of multivariate analysis procedures. The application to the OSPAR
Considering Respiratory Tract Infections and Antimicrobial Sensitivity: An Exploratory Analysis
Directory of Open Access Journals (Sweden)
Amin, R.
2009-01-01
Full Text Available This study was conducted to observe the sensitivity and resistance of status of antibiotics for respiratory tract infection (RTI. Throat swab culture and sensitivity report of 383 patients revealed sensitivity profiles were observed with amoxycillin (7.9%, penicillin (33.7%, ampicillin (36.6%, co-trimoxazole (46.5%, azithromycin (53.5%, erythromycin (57.4%, cephalexin (69.3%, gentamycin (78.2%, ciprofloxacin (80.2%, cephradine (81.2%, ceftazidime (93.1%, ceftriaxone (93.1%. Sensitivity to cefuroxime was reported 93.1% cases. Resistance was found with amoxycillin (90.1%, ampicillin (64.1%, penicillin (61.4%, co-trimoxazole (43.6%, erythromycin (39.6%, and azithromycin (34.7%. Cefuroxime demonstrates high level of sensitivity than other antibiotics and supports its consideration with patients with upper RTI.
Sensitivity analysis: Theory and practical application in safety cases
International Nuclear Information System (INIS)
Kuhlmann, Sebastian; Plischke, Elmar; Roehlig, Klaus-Juergen; Becker, Dirk-Alexander
2014-01-01
The projects described here aim at deriving an adaptive and stepwise approach to sensitivity analysis (SA). Since the appropriateness of a single SA method strongly depends on the nature of the model under study, a top-down approach (from simple to sophisticated methods) is suggested. If simple methods explain the model behaviour sufficiently well then there is no need for applying more sophisticated ones and the SA procedure can be considered complete. The procedure is developed and tested using a model for a LLW/ILW repository in salt. Additionally, a new model for the disposal of HLW in rock salt will be available soon for SA studies within the MOSEL/NUMSA projects. This model will address special characteristics of waste disposal in undisturbed rock salt, especially the case of total confinement, resulting in a zero release which is indeed the objective of radioactive waste disposal. A high proportion of zero-output realisations causes many SA methods to fail, so special treatment is needed and has to be developed. Furthermore, the HLW disposal model will be used as a first test case for applying the procedure described above, which was and is being derived using the LLW/ILW model. How to treat dependencies in the input, model conservatism and time-dependent outputs will be addressed in the future project programme: - If correlations or, more generally, dependencies between input parameters exist, the question arises about the deeper meaning of sensitivity results in such cases: A strict separation between inputs, internal states and outputs is no longer possible. Such correlations (or dependencies) might have different reasons. In some cases correlated input parameters might have a common physically (well-)known fundamental cause but there are reasons why this fundamental cause cannot or should not be integrated into the model, i.e. the cause might generate a very complex model which cannot be calculated in appropriate time. In other cases the correlation may
Uncertainty and sensitivity analysis in a Probabilistic Safety Analysis level-1
International Nuclear Information System (INIS)
Nunez Mc Leod, Jorge E.; Rivera, Selva S.
1996-01-01
A methodology for sensitivity and uncertainty analysis, applicable to a Probabilistic Safety Assessment Level I has been presented. The work contents are: correct association of distributions to parameters, importance and qualification of expert opinions, generations of samples according to sample sizes, and study of the relationships among system variables and systems response. A series of statistical-mathematical techniques are recommended along the development of the analysis methodology, as well as different graphical visualization for the control of the study. (author)
Economic impact analysis for global warming: Sensitivity analysis for cost and benefit estimates
International Nuclear Information System (INIS)
Ierland, E.C. van; Derksen, L.
1994-01-01
Proper policies for the prevention or mitigation of the effects of global warming require profound analysis of the costs and benefits of alternative policy strategies. Given the uncertainty about the scientific aspects of the process of global warming, in this paper a sensitivity analysis for the impact of various estimates of costs and benefits of greenhouse gas reduction strategies is carried out to analyze the potential social and economic impacts of climate change
Aldeen Yousra, S.; Mazleena, Salleh
2018-05-01
Recent advancement in Information and Communication Technologies (ICT) demanded much of cloud services to sharing users’ private data. Data from various organizations are the vital information source for analysis and research. Generally, this sensitive or private data information involves medical, census, voter registration, social network, and customer services. Primary concern of cloud service providers in data publishing is to hide the sensitive information of individuals. One of the cloud services that fulfill the confidentiality concerns is Privacy Preserving Data Mining (PPDM). The PPDM service in Cloud Computing (CC) enables data publishing with minimized distortion and absolute privacy. In this method, datasets are anonymized via generalization to accomplish the privacy requirements. However, the well-known privacy preserving data mining technique called K-anonymity suffers from several limitations. To surmount those shortcomings, I propose a new heuristic anonymization framework for preserving the privacy of sensitive datasets when publishing on cloud. The advantages of K-anonymity, L-diversity and (α, k)-anonymity methods for efficient information utilization and privacy protection are emphasized. Experimental results revealed the superiority and outperformance of the developed technique than K-anonymity, L-diversity, and (α, k)-anonymity measure.
Pasta, D J; Taylor, J L; Henning, J M
1999-01-01
Decision-analytic models are frequently used to evaluate the relative costs and benefits of alternative therapeutic strategies for health care. Various types of sensitivity analysis are used to evaluate the uncertainty inherent in the models. Although probabilistic sensitivity analysis is more difficult theoretically and computationally, the results can be much more powerful and useful than deterministic sensitivity analysis. The authors show how a Monte Carlo simulation can be implemented using standard software to perform a probabilistic sensitivity analysis incorporating the bootstrap. The method is applied to a decision-analytic model evaluating the cost-effectiveness of Helicobacter pylori eradication. The necessary steps are straightforward and are described in detail. The use of the bootstrap avoids certain difficulties encountered with theoretical distributions. The probabilistic sensitivity analysis provided insights into the decision-analytic model beyond the traditional base-case and deterministic sensitivity analyses and should become the standard method for assessing sensitivity.
Assessing Use of Cognitive Heuristic Representativeness in Clinical Reasoning
Payne, Velma L.; Crowley, Rebecca S.
2008-01-01
We performed a pilot study to investigate use of the cognitive heuristic Representativeness in clinical reasoning. We tested a set of tasks and assessments to determine whether subjects used the heuristics in reasoning, to obtain initial frequencies of heuristic use and related cognitive errors, and to collect cognitive process data using think-aloud techniques. The study investigates two aspects of the Representativeness heuristic - judging by perceived frequency and representativeness as ca...
Automated generation of constructive ordering heuristics for educational timetabling
Pillay, Nelishia; Özcan, Ender
2017-01-01
Construction heuristics play an important role in solving combinatorial optimization problems. These heuristics are usually used to create an initial solution to the problem which is improved using optimization techniques such as metaheuristics. For examination timetabling and university course timetabling problems essentially graph colouring heuristics have been used for this purpose. The process of deriving heuristics manually for educational timetabling is a time consuming task. Furthermor...
Adaptive selection of heuristics for improving exam timetables
Burke, Edmund; Qu, Rong; Soghier, Amr
2014-01-01
This paper presents a hyper-heuristic approach which hybridises low-level heuristic moves to improve timetables. Exams which cause a soft-constraint violation in the timetable are ordered and rescheduled to produce a better timetable. It is observed that both the order in which exams are rescheduled and the heuristic moves used to reschedule the exams and improve the timetable affect the quality of the solution produced. After testing different combinations in a hybrid hyper-heuristic approac...
Sorption of redox-sensitive elements: critical analysis
International Nuclear Information System (INIS)
Strickert, R.G.
1980-12-01
The redox-sensitive elements (Tc, U, Np, Pu) discussed in this report are of interest to nuclear waste management due to their long-lived isotopes which have a potential radiotoxic effect on man. In their lower oxidation states these elements have been shown to be highly adsorbed by geologic materials occurring under reducing conditions. Experimental research conducted in recent years, especially through the Waste Isolation Safety Assessment Program (WISAP) and Waste/Rock Interaction Technology (WRIT) program, has provided extensive information on the mechanisms of retardation. In general, ion-exchange probably plays a minor role in the sorption behavior of cations of the above three actinide elements. Formation of anionic complexes of the oxidized states with common ligands (OH - , CO -- 3 ) is expected to reduce adsorption by ion exchange further. Pertechnetate also exhibits little ion-exchange sorption by geologic media. In the reduced (IV) state, all of the elements are highly charged and it appears that they form a very insoluble compound (oxide, hydroxide, etc.) or undergo coprecipitation or are incorporated into minerals. The exact nature of the insoluble compounds and the effect of temperature, pH, pe, other chemical species, and other parameters are currently being investigated. Oxidation states other than Tc (IV,VII), U(IV,VI), Np(IV,V), and Pu(IV,V) are probably not important for the geologic repository environment expected, but should be considered especially when extreme conditions exist (radiation, temperature, etc.). Various experimental techniques such as oxidation-state analysis of tracer-level isotopes, redox potential measurement and control, pH measurement, and solid phase identification have been used to categorize the behavior of the various valence states
Sorption of redox-sensitive elements: critical analysis
Energy Technology Data Exchange (ETDEWEB)
Strickert, R.G.
1980-12-01
The redox-sensitive elements (Tc, U, Np, Pu) discussed in this report are of interest to nuclear waste management due to their long-lived isotopes which have a potential radiotoxic effect on man. In their lower oxidation states these elements have been shown to be highly adsorbed by geologic materials occurring under reducing conditions. Experimental research conducted in recent years, especially through the Waste Isolation Safety Assessment Program (WISAP) and Waste/Rock Interaction Technology (WRIT) program, has provided extensive information on the mechanisms of retardation. In general, ion-exchange probably plays a minor role in the sorption behavior of cations of the above three actinide elements. Formation of anionic complexes of the oxidized states with common ligands (OH/sup -/, CO/sup - -//sub 3/) is expected to reduce adsorption by ion exchange further. Pertechnetate also exhibits little ion-exchange sorption by geologic media. In the reduced (IV) state, all of the elements are highly charged and it appears that they form a very insoluble compound (oxide, hydroxide, etc.) or undergo coprecipitation or are incorporated into minerals. The exact nature of the insoluble compounds and the effect of temperature, pH, pe, other chemical species, and other parameters are currently being investigated. Oxidation states other than Tc (IV,VII), U(IV,VI), Np(IV,V), and Pu(IV,V) are probably not important for the geologic repository environment expected, but should be considered especially when extreme conditions exist (radiation, temperature, etc.). Various experimental techniques such as oxidation-state analysis of tracer-level isotopes, redox potential measurement and control, pH measurement, and solid phase identification have been used to categorize the behavior of the various valence states.
Analysis of Sea Ice Cover Sensitivity in Global Climate Model
Directory of Open Access Journals (Sweden)
V. P. Parhomenko
2014-01-01
Full Text Available The paper presents joint calculations using a 3D atmospheric general circulation model, an ocean model, and a sea ice evolution model. The purpose of the work is to analyze a seasonal and annual evolution of sea ice, long-term variability of a model ice cover, and its sensitivity to some parameters of model as well to define atmosphere-ice-ocean interaction.Results of 100 years simulations of Arctic basin sea ice evolution are analyzed. There are significant (about 0.5 m inter-annual fluctuations of an ice cover.The ice - atmosphere sensible heat flux reduced by 10% leads to the growth of average sea ice thickness within the limits of 0.05 m – 0.1 m. However in separate spatial points the thickness decreases up to 0.5 m. An analysis of the seasonably changing average ice thickness with decreasing, as compared to the basic variant by 0.05 of clear sea ice albedo and that of snow shows the ice thickness reduction in a range from 0.2 m up to 0.6 m, and the change maximum falls for the summer season of intensive melting. The spatial distribution of ice thickness changes shows, that on the large part of the Arctic Ocean there was a reduction of ice thickness down to 1 m. However, there is also an area of some increase of the ice layer basically in a range up to 0.2 m (Beaufort Sea. The 0.05 decrease of sea ice snow albedo leads to reduction of average ice thickness approximately by 0.2 m, and this value slightly depends on a season. In the following experiment the ocean – ice thermal interaction influence on the ice cover is estimated. It is carried out by increase of a heat flux from ocean to the bottom surface of sea ice by 2 W/sq. m in comparison with base variant. The analysis demonstrates, that the average ice thickness reduces in a range from 0.2 m to 0.35 m. There are small seasonal changes of this value.The numerical experiments results have shown, that an ice cover and its seasonal evolution rather strongly depend on varied parameters
Heuristics for multiobjective multiple sequence alignment.
Abbasi, Maryam; Paquete, Luís; Pereira, Francisco B
2016-07-15
Aligning multiple sequences arises in many tasks in Bioinformatics. However, the alignments produced by the current software packages are highly dependent on the parameters setting, such as the relative importance of opening gaps with respect to the increase of similarity. Choosing only one parameter setting may provide an undesirable bias in further steps of the analysis and give too simplistic interpretations. In this work, we reformulate multiple sequence alignment from a multiobjective point of view. The goal is to generate several sequence alignments that represent a trade-off between maximizing the substitution score and minimizing the number of indels/gaps in the sum-of-pairs score function. This trade-off gives to the practitioner further information about the similarity of the sequences, from which she could analyse and choose the most plausible alignment. We introduce several heuristic approaches, based on local search procedures, that compute a set of sequence alignments, which are representative of the trade-off between the two objectives (substitution score and indels). Several algorithm design options are discussed and analysed, with particular emphasis on the influence of the starting alignment and neighborhood search definitions on the overall performance. A perturbation technique is proposed to improve the local search, which provides a wide range of high-quality alignments. The proposed approach is tested experimentally on a wide range of instances. We performed several experiments with sequences obtained from the benchmark database BAliBASE 3.0. To evaluate the quality of the results, we calculate the hypervolume indicator of the set of score vectors returned by the algorithms. The results obtained allow us to identify reasonably good choices of parameters for our approach. Further, we compared our method in terms of correctly aligned pairs ratio and columns correctly aligned ratio with respect to reference alignments. Experimental results show
Applying usability heuristics to radiotherapy systems
International Nuclear Information System (INIS)
Chan, Alvita J.; Islam, Mohammad K.; Rosewall, Tara; Jaffray, David A.; Easty, Anthony C.; Cafazzo, Joseph A.
2012-01-01
Background and purpose: Heuristic evaluations have been used to evaluate safety of medical devices by identifying and assessing usability issues. Since radiotherapy treatment delivery systems often consist of multiple complex user-interfaces, a heuristic evaluation was conducted to assess the potential safety issues of such a system. Material and methods: A heuristic evaluation was conducted to evaluate the treatment delivery system at Princess Margaret Hospital (Toronto, Canada). Two independent evaluators identified usability issues with the user-interfaces and rated the severity of each issue. Results: The evaluators identified 75 usability issues in total. Eighteen of them were rated as high severity, indicating the potential to have a major impact on patient safety. A majority of issues were found on the record and verify system, and many were associated with the patient setup process. While the hospital has processes in place to ensure patient safety, recommendations were developed to further mitigate the risks of potential consequences. Conclusions: Heuristic evaluation is an efficient and inexpensive method that can be successfully applied to radiotherapy delivery systems to identify usability issues and improve patient safety. Although this study was conducted only at one site, the findings may have broad implications for the design of these systems.
Can the inherence heuristic explain vitalistic reasoning?
Bastian, Brock
2014-10-01
Inherence is an important component of psychological essentialism. By drawing on vitalism as a way in which to explain this link, however, the authors appear to conflate causal explanations based on fixed features with those based on general causal forces. The disjuncture between these two types of explanatory principles highlights potential new avenues for the inherence heuristic.
Fast heuristics for a dynamic paratransit problem
Cremers, M.L.A.G.; Klein Haneveld, W.K.; van der Vlerk, M.H.
2008-01-01
In a previous paper we developed a non-standard two-stage recourse model for the dynamic day-ahead paratransit planning problem. Two heuristics, which are frequently applied in the recourse model, contain many details which leads to large CPU times to solve instances of relatively small size. In
A Heuristic for Improving Transmedia Exhibition Experience
DEFF Research Database (Denmark)
Selvadurai, Vashanth; Rosenstand, Claus Andreas Foss
2017-01-01
in the scientific field of designing transmedia experience in an exhibition context that links the pre- and post-activities to the actual visit (during-activities). The result of this study is a preliminary heuristic for establishing a relation between the platform and content complexity in transmedia exhibitions....
Efficient heuristics for maximum common substructure search.
Englert, Péter; Kovács, Péter
2015-05-26
Maximum common substructure search is a computationally hard optimization problem with diverse applications in the field of cheminformatics, including similarity search, lead optimization, molecule alignment, and clustering. Most of these applications have strict constraints on running time, so heuristic methods are often preferred. However, the development of an algorithm that is both fast enough and accurate enough for most practical purposes is still a challenge. Moreover, in some applications, the quality of a common substructure depends not only on its size but also on various topological features of the one-to-one atom correspondence it defines. Two state-of-the-art heuristic algorithms for finding maximum common substructures have been implemented at ChemAxon Ltd., and effective heuristics have been developed to improve both their efficiency and the relevance of the atom mappings they provide. The implementations have been thoroughly evaluated and compared with existing solutions (KCOMBU and Indigo). The heuristics have been found to greatly improve the performance and applicability of the algorithms. The purpose of this paper is to introduce the applied methods and present the experimental results.
Heuristics for speeding up gaze estimation
DEFF Research Database (Denmark)
Leimberg, Denis; Vester-Christensen, Martin; Ersbøll, Bjarne Kjær
2005-01-01
A deformable template method for eye tracking on full face images is presented. The strengths of the method are that it is fast and retains accuracy independently of the resolution. We compare the method with a state of the art active contour approach, showing that the heuristic method is more...
The Heuristic Interpretation of Box Plots
Lem, Stephanie; Onghena, Patrick; Verschaffel, Lieven; Van Dooren, Wim
2013-01-01
Box plots are frequently used, but are often misinterpreted by students. Especially the area of the box in box plots is often misinterpreted as representing number or proportion of observations, while it actually represents their density. In a first study, reaction time evidence was used to test whether heuristic reasoning underlies this…
Heuristic Classification. Technical Report Number 12.
Clancey, William J.
A broad range of well-structured problems--embracing forms of diagnosis, catalog selection, and skeletal planning--are solved in expert computer systems by the method of heuristic classification. These programs have a characteristic inference structure that systematically relates data to a pre-enumerated set of solutions by abstraction, heuristic…
A Heuristic for the Teaching of Persuasion.
Schell, John F.
Interpreting Aristotle's criteria for persuasive writing--ethos, logos, and pathos--as a concern for writer, language, and audience creates both an effective model for persuasive writing and a structure around which to organize discussions of relevant rhetorical issues. Use of this heuristic to analyze writing style, organization, and content…
Fourth Graders' Heuristic Problem-Solving Behavior.
Lee, Kil S.
1982-01-01
Eight boys and eight girls from a rural elementary school participated in the investigation. Specific heuristics were adopted from Polya; and the students selected represented two substages of Piaget's concrete operational stage. Five hypotheses were generated, based on observed results and the study's theoretical rationale. (MP)
Heuristic Decision Making in Network Linking
M.J.W. Harmsen - Van Hout (Marjolein); B.G.C. Dellaert (Benedict); P.J.J. Herings (Jean-Jacques)
2015-01-01
textabstractNetwork formation among individuals constitutes an important part of many OR processes, but relatively little is known about how individuals make their linking decisions in networks. This article provides an investigation of heuristic effects in individual linking decisions for
Investigating Heuristic Evaluation: A Case Study.
Goldman, Kate Haley; Bendoly, Laura
When museum professionals speak of evaluating a web site, they primarily mean formative evaluation, and by that they primarily mean testing the usability of the site. In the for-profit world, usability testing is a multi-million dollar industry, while non-profits often rely on far too few dollars to do too much. Hence, heuristic evaluation is one…
Sensitivity analysis of hybrid power systems using Power Pinch Analysis considering Feed-in Tariff
International Nuclear Information System (INIS)
Mohammad Rozali, Nor Erniza; Wan Alwi, Sharifah Rafidah; Manan, Zainuddin Abdul; Klemeš, Jiří Jaromír
2016-01-01
Feed-in Tariff (FiT) has been one of the most effective policies in accelerating the development of renewable energy (RE) projects. The amount of RE electricity in the FiT purchase agreement is an important decision that has to be made by the RE project developers. They have to consider various crucial factors associated with RE system operation as well as its stochastic nature. The presented work aims to assess the sensitivity and profitability of a hybrid power system (HPS) in cases of RE system failure or shutdown. The amount of RE electricity for the FiT purchase agreement in various scenarios was determined using a novel tool called On-Grid Problem Table based on the Power Pinch Analysis (PoPA). A sensitivity table has also been introduced to assist planners to evaluate the effects of the RE system's failure on the profitability of the HPS. This table offers insights on the variance of the RE electricity. The sensitivity analysis of various possible scenarios shows that the RE projects can still provide financial benefits via the FiT, despite the losses incurred from the penalty levied. - Highlights: • A Power Pinch Analysis (PoPA) tool to assess the economics of an HPS with FiT. • The new On-Grid Problem Table for targeting the available RE electricity for FiT sale. • A sensitivity table showing the effect of RE electricity changes on the HPS profitability.
Global sensitivity analysis in stochastic simulators of uncertain reaction networks
Navarro, Marí a; Le Maitre, Olivier; Knio, Omar
2016-01-01
sources are independent, and considers the Poisson processes in the random-time-change representation of the state dynamics as the fundamental objects governing the inherent stochasticity. A sampling algorithm is proposed to perform the global sensitivity