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Artykuły w czasopismach na temat "Complex factorial experiments"
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Drinkwater, Laurie E. "Cropping Systems Rsearch: Reconsidering Agricultural Experimental Approaches". HortTechnology 12, nr 3 (styczeń 2002): 355–61. http://dx.doi.org/10.21273/horttech.12.3.355.
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Systems approaches to research can be used to study characteristics of agricultural systems that cannot be addressed using conventional factorial experiments. The goal of a factorial experiment is to break down a complex system in order to isolate and study specific components and identify cause-effect relationships. In contrast, systems experiments aim to understand how a complex system functions as a whole and thus requires that intact systems be studied. Two approaches have been successfully applied to agricultural systems research: 1) field station experiments where simulated cropping systems are established in replicated plots and 2) studies of intact agroecosystems using commercial farms as study sites. These two approaches have complementary strengths and limitations and have made significant contributions to our understanding of ecological processes in agricultural systems. The development of sustainable agroecosystems will be best accomplished using an integrated research approach combining systems experiments with appropriately designed factorial experiments.
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Cervantes, Michel J., i T. Fredrik Engstro¨m. "Factorial Design Applied to CFD". Journal of Fluids Engineering 126, nr 5 (1.09.2004): 791–98. http://dx.doi.org/10.1115/1.1792277.
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Factorial design, a statistical method widely used for experiments, and its application to CFD are discussed. The aim is to propose a systematic, objective, and quantitative method for engineers to design a set of simulations in order to evaluate main and joint effects of input parameters on the numerical solution. The input parameters may be experimental uncertainty on boundary conditions, unknown boundary conditions, grid, differencing schemes, and turbulence models. The complex flow of the Turbine-99 test case, a hydropower draft tube flow, is used to illustrate the method, where four factors are chosen to perform a 24 factorial design. The radial velocity at the inlet (not measured) is shown to have an important influence on the pressure recovery (7%) and the energy loss factor (49%).
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Łacka, Agnieszka. "NRC Designs—New Tools for Successful Agricultural Experiments". Agronomy 11, nr 12 (25.11.2021): 2406. http://dx.doi.org/10.3390/agronomy11122406.
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In a nested row–column design (NRC), the experimental units in each of n blocks are grouped into n1 rows and n2 columns. Due to its structure, this experimental design allows full control of the experimental material and a relatively simple feedback loop within the “statistical triangle”. By applying such designs in agricultural experiments, we provide an insurance policy against future unexpected problems. Until now, the cost of this policy has been a complex statistical analysis of experimental data. This paper proposes a new “direct” approach to ANOVA based on the latest literature on the subject. The paper provides the theoretical foundations of this approach, indicates the possibility of applying it to factorial and near-factorial experiments, and supplements the theory with a familiar letter-based representation of all-pairwise comparisons, which has so far been lacking in the literature. The methodology is illustrated by the analysis of a field experiment carried out to improve the use of fungicides against late blight in tomato processing. The presented analytical tools are supplemented with code in R.
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Düval, Sabine, i Thomas Hinz. "Different Order, Different Results? The Effects of Dimension Order in Factorial Survey Experiments". Field Methods 32, nr 1 (19.11.2019): 23–37. http://dx.doi.org/10.1177/1525822x19886827.
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Factorial surveys are widely used in the social sciences to measure respondents’ attitudes, beliefs, or behavioral intentions. In such surveys, respondents evaluate short descriptions of hypothetical situations, persons, or objects that vary across several dimensions. An important prerequisite of the method’s validity is that respondents are able to deal with the highly complex task created by the need to consider several variable dimensions within one coherent judgment. We analyze the effects of the order in which dimensions are presented in running text vignettes. An experimental setup with four order treatments was randomly allocated to 787 respondents (based on a random sample of register data), yielding 3,119 vignette evaluations. The analyses compare respondent groups across age, education, and response speed. Overall, there is no strong evidence for order effects. However, we find a slight tendency for fast responders to be more prone to recency effects.
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Schaarschmidt, Frank, i Lea Vaas. "Analysis of Trials with Complex Treatment Structure Using Multiple Contrast Tests". HortScience 44, nr 1 (luty 2009): 188–95. http://dx.doi.org/10.21273/hortsci.44.1.188.
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Experiments with complex treatment structures are not uncommon in horticultural research. For example, in augmented factorial designs, one control treatment is added to a full factorial arrangement, or an experiment might be arranged as a two-factorial design with some groups omitted because they are practically not of interest. Several statistical procedures have been proposed to analyze such designs. Suitable linear models followed by F-tests provide only global inference for main effects and their interactions. Orthogonal contrasts are demanding to formulate and cannot always reflect all experimental questions underlying the design. Finally, simple mean comparisons following global F-tests do not control the overall error rate of the experiment in the strong sense. In this article, we show how multiple contrast tests can be used as a tool to address the experimental questions underlying complex designs while preserving the overall error rate of the conclusions. Using simultaneous confidence intervals allows for displaying the direction, magnitude, and relevance of the mean comparisons of interest. Along with application in statistical software, shown by two examples, we discuss the possibilities and limitations of the proposed approach.
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Aramesh, Saeed, i Ali Ghorbanian. "Multi-objective Optimization for a Complex Intersection Using Design of Experiments and Simulation". Journal Européen des Systèmes Automatisés 53, nr 6 (23.12.2020): 791–802. http://dx.doi.org/10.18280/jesa.530605.
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Considering the importance of time in today's world and the rising traffic congestion in urban areas, using methods to reduce wait times and air pollution can have a significant impact on promoting urban management. Given the uncertainty in the number of vehicles and the emission rate of vehicles, a complex T intersection with three traffic lights was simulated in this study. Three objective functions were defined for the mean of wait time, average queue length, and aggregate pollutant emission of the vehicles in queue. First, regression equations for each of the variables were obtained by a full factorial design and analysis of variance, and the optimal period for each traffic light was then computed with a utility function approach. Finally, the results were compared to the results obtained from the optimization of each response variable OptQuest for Arena software.
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Jensen, Signe M., Christian Andreasen, Jens C. Streibig, Eshagh Keshtkar i Christian Ritz. "A note on the analysis of germination data from complex experimental designs". Seed Science Research 27, nr 4 (18.09.2017): 321–27. http://dx.doi.org/10.1017/s0960258517000228.
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AbstractIn recent years germination experiments have become more and more complex. Typically, they are replicated in time as independent runs and at each time point they involve hierarchical, often factorial experimental designs, which are now commonly analysed by means of linear mixed models. However, in order to characterize germination in response to time elapsed, specific event-time models are needed and mixed model extensions of these models are not readily available, neither in theory nor in practice. As a practical workaround we propose a two-step approach that combines and weighs together results from event-time models fitted separately to data from each germination test by means of meta-analytic random effects models. We show that this approach provides a more appropriate appreciation of the sources of variation in hierarchically structured germination experiments as both between- and within-experiment variation may be recovered from the data.
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Stenhouse, Neil, i Richard Heinrich. "Breaking Negative Stereotypes of Climate Activists: A Conjoint Experiment". Science Communication 41, nr 3 (13.05.2019): 339–68. http://dx.doi.org/10.1177/1075547019848766.
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We tested 44 variations in profiles of climate change activists to see what affected willingness to associate with them. The largest effects were from activists’ perspectives on climate change, how often they pressure others, gun control views, and party affiliation. If implemented as a traditional factorial experiment, this experiment would require 648,000 conditions and an infeasibly large sample. We obtained our results much more efficiently via an experimental design rare in communication research. Conjoint experiments will be useful to science communication researchers who wish to simultaneously test many factors of complex stimuli, such as individuals, organizations, technologies, or policies.
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Cangussu, Nara, Ana Mafalda Matos, Paula Milheiro-Oliveira i Lino Maia. "Modelling and Predicting Self-Compacting High Early Age Strength Mortars Properties: Comparison of Response Models from Full, Fractioned and Small Central Composite Designs". Applied Sciences 13, nr 14 (20.07.2023): 8413. http://dx.doi.org/10.3390/app13148413.
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The mixture design of cement-based materials can be complex due to the increasing number of constituent raw materials and multiple requirements in terms of engineering performance and economic and environmental efficiency. Designing experiments based on factorial plans has shown to be a powerful tool for predicting and optimising advanced cement-based materials, such as self-compacting high-early-strength cement-based mortars. Nevertheless, the number of factor interactions required for factor scheduling increases considerably with the number of factors. Consequently, the probability that the interactions do not significantly affect the answer also increases. As such, fractioned factorial plans may be an exciting option. For the first time, the current work compares the regression models and the predicting capacity of full, fractionated (A and B fractions) and small factorial designs to describe self-compacting high-early-strength cement-based mortars’ properties, namely, the funnel time, flexure and compressive strength at 24 h for the function of the mixture parameters Vw/Vc, Sp/p, Vw/Vp, Vs/Vm and Vfs/Vs for the different factorial designs. We combine statistical methods and regression analysis. Response models were obtained from the full, fractionated, and small plans. The full and fractionated models seem appropriate for describing the properties of self-compacting high-early-strength cement-based mortars in the experimental region. Moreover, the predicting ability of the full and fractionated factorial designs is very similar; however, the small design predictions reveal some concerns. Our results confirm the potentiality of fractioned plans to reduce the number of experiments and consequently reduce the cost and time of experimentation when designing self-compacting high-early-strength cement-based mortars.
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Jankovic, Aleksandar, Gaurav Chaudhary i Francesco Goia. "Designing the design of experiments (DOE) – An investigation on the influence of different factorial designs on the characterization of complex systems". Energy and Buildings 250 (listopad 2021): 111298. http://dx.doi.org/10.1016/j.enbuild.2021.111298.
Pełny tekst źródłaRozprawy doktorskie na temat "Complex factorial experiments"
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Medeiros, Patricia Neves de. "S?ntese de pigmento cer?mico ferrita de cobalto utilizando planejamento experimental". Universidade Federal do Rio Grande do Norte, 2013. http://repositorio.ufrn.br:8080/jspui/handle/123456789/12809.
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Synthetic inorganic pigments are the most widely used in ceramic applications because they have excellent chemical and thermal stability and also, in general, a lower toxicity to man and to the environment. In the present work, the ceramic black pigment CoFe2O4 was synthesized by the polymerization Complex method (MPC) in order to form a material with good chemical homogeneity. Aiming to optimize the process of getting the pigment through the MPC was used a fractional factorial design 2(5-2), with resolution III. The factors studied in mathematical models were: citric acid concentration, the pyrolysis time, temperature, time and rate of calcination. The response surfaces using the software statistica 7.0. The powders were characterized by thermal analysis (TG/DSC), x-ray diffraction (XRD), scanning electron microscopy (SEM) and spectroscopy in the UV-visible. Based on the results, there was the formation of phase cobalt ferrite (CoFe2O4) with spinel structure. The color of the pigments obtained showed dark shades, from black to gray. The model chosen was appropriate since proved to be adjusted and predictive. Planning also showed that all factors were significant, with a confidence level of 95%
Os pigmentos inorg?nicos sint?ticos s?o os mais utilizados em aplica??es cer?micas por apresentarem uma excelente estabilidade qu?mica e t?rmica e tamb?m, em geral, uma menor toxicidade para o homem e para o meio ambiente. No presente trabalho, o pigmento cer?mico preto CoFe2O4 foi sintetizado pelo M?todo de Polimeriza??o de Complexos (MPC) visando a forma??o de um material com boa homogeneidade qu?mica. Com o objetivo de otimizar o processo de obten??o do pigmento atrav?s do MPC foi utilizado um planejamento fatorial fracionado 2(5-2), com resolu??o III. Os fatores estudados na modelagem matem?tica foram: concentra??o de ?cido c?trico, tempo de pir?lise, temperatura, tempo e taxa de calcina??o. As superf?cies de resposta utilizando o programa statistica 7.0. Os p?s obtidos foram caracterizados atrav?s de an?lises t?rmicas (TG/DSC), difra??o de raios-x (DRX), microscopia eletr?nica de varredura (MEV) e espectroscopia na regi?o do UV-vis?vel. Com base nos resultados, foi verificada a forma??o da fase ferrita de cobalto (CoFe2O4) com estrutura espin?lio. A cor dos pigmentos obtidos apresentou tonalidades escuras, do preto ao cinza. O modelo escolhido foi adequado, visto que mostrou-se ajustado e preditivo. O planejamento tamb?m mostrou que todos os fatores foram significativos, com n?vel de confian?a em 95%
Książki na temat "Complex factorial experiments"
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Miksza, Peter, i Kenneth Elpus. Design and Analysis of Experimental Research II. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780199391905.003.0009.
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This chapter introduces the reader to more possibilities for thinking about causal questions and for laying the foundational concepts necessary for conducting data analyses that correspond to more complex experimental designs. The discussion of experimental design types presented in chapter 8 is expanded to include within-subjects designs, factorial designs, mixed designs, and designs for multivariate outcomes. Prototypical examples of each design type are presented along with the typical analysis tools used for testing the associated experimental hypotheses. Hypothetical examples of research designs that are suitable for illustrating analyses with repeated-measures ANOVA, factorial or multiway ANOVA, and MANOVA (multivariate analysis of variance).
Części książek na temat "Complex factorial experiments"
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Durner, Edward F. "The randomized complete block design." W Applied plant science experimental design and statistical analysis using the SAS® OnDemand for Academics, 177–91. Wallingford: CABI, 2021. http://dx.doi.org/10.1079/9781789249927.0012.
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Abstract This chapter focuses on randomized complete block design (RCBD). The RCBD can be simple, holding several levels of a single treatment, or complex, holding a complicated factorial. Field experiments may be blocked due to an observed or potential gradient in the field where the experiment will be performed. The yield of four lettuce cultivars was used as an example.
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Taneja, Baldeo K. "Nonparametric Selection Procedures in Complete Factorial Experiments". W Contributions to Stochastics, 214–35. Heidelberg: Physica-Verlag HD, 1987. http://dx.doi.org/10.1007/978-3-642-46893-3_22.
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Mutz, Diana C. "Vignette Treatments". W Population-Based Survey Experiments. Princeton University Press, 2011. http://dx.doi.org/10.23943/princeton/9780691144511.003.0004.
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This chapter focuses on the process of vignette treatments. Vignettes offer the possibility of easily executing complex, multi-dimensional factorial designs. Although the vignette approach can certainly be used for very simple studies as well, the trade-offs that they impose—namely, the introduction of what are essentially hypothetical people and situations—may be most beneficial when studying more complex theories. Vignettes could be considered a subspecies of direct treatment in that the interventions are essentially what they appear to be on the surface. The goal of vignette treatments is to evaluate what difference it makes when the actual object of study or judgment, or the context in which that object appears, is systematically changed in some way.
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Moser, Barry Kurt. "Complete, Balanced Factorial Experiments". W Linear Models, 53–80. Elsevier, 1996. http://dx.doi.org/10.1016/b978-012508465-9/50004-1.
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Anderson, Virgil L., i Robert A. McLean. "2n Factorial Experiments (Complete and Incomplete Blocks)". W Design of Experiments, 225–51. Routledge, 2018. http://dx.doi.org/10.1201/9781315141039-9.
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Pelet, Jean-Éric, i Basma Taieb. "Designing Website Interfaces for M-Commerce With Consideration for Adult Consumers". W Mobile Platforms, Design, and Apps for Social Commerce, 288–308. IGI Global, 2017. http://dx.doi.org/10.4018/978-1-5225-2469-4.ch016.
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This chapter analyzes the interaction effects between the principal design cues of a mobile commerce website, such as background/foreground colors, font text and layout. Three experiments have been conducted based on visits to a fictitious m-commerce website. Experiment 1 manipulates the levels of color contrast: positive contrast (light text on a dark background) versus negative contrast (dark text on a light background). In experiment 2, contrast and font have been manipulated with a complete factorial plan: 2 x 2 (negative vs positive contrast x serif font vs sans serif font). Finally, contrast and layout have been manipulated in a third experimental 2 x 2 plan (negative vs positive contrast x dense vs airy layout). This research involved 219 French participants. Results show significant effects of the positive contrast (light text on a dark background) of the mobile website design on the purchase and revisit intentions of adults. Discussions about the interaction effects of design elements, limitations and directions for future research follow.
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Chen, Huige, Hangyu Chen, Kechi Chen, Xinda Wu, Wanyu Zheng i Linjing Wang. "Research on the Technology of Recovering Low Concentration Ni+ Metal Ion Solution". W Advances in Transdisciplinary Engineering. IOS Press, 2021. http://dx.doi.org/10.3233/atde210329.
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Under environmentally friendly and environmental issues, wastewater treatment in laboratories and factories is an important international issue. Among them, wastewater from the chemical industry accounts for a large part of industrial wastewater discharge. The introduction of new technologies to treat chemical wastewater is of great significance. In particular, the amount of wastewater produced by inorganic chemistry experiments is relatively large, and the pollutants are mostly heavy metal salts. According to the characteristics of inorganic chemistry experimental wastewater, such as special nature, small amount, strong discontinuity, high hazard, complex and changeable composition, etc., design a chemical reaction to provide a practical and feasible method to treat wastewater with high efficiency and low cost. This research initially takes Ni+ metal ion waste liquid as the first stage of recycling and treatment to improve the traditional low-concentration non-economic treatment. The preliminary results of this research are neutralization reaction and optimal pH value control of Ni+ waste liquid to generate Ni+ precursors to increase the economic value of recycling will be the basis for providing in-house recycling systems for electroplating plants, panel plants, and semiconductor plants to achieve emission reduction, green chemical industry and green environmental protection.
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Arredondo-Soto, Karina Cecilia, Arturo Realyvasquez-Vargas i Alejandro Jiménez-Zaragoza. "Optimization of Injection Molding Process Parameters via Design of Experiments". W Design of Experiments for Chemical, Pharmaceutical, Food, and Industrial Applications, 253–69. IGI Global, 2020. http://dx.doi.org/10.4018/978-1-7998-1518-1.ch011.
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The validation of processes is an innovative methodology where a process has been submitted to scrutiny to guarantee the products comply with the specifications of the company and the norms of the country of consumption. In the medical industry, this process is considered as a regulatory requirement, however, this also helps to improve quality, eliminate waste, and reduce costs, among other things. This chapter applied the methodology of process validation in a medical device company; the engineering tests were used in the company's clean room, using an injection molding machine and tests of several parameters were used even without being validated to know which are the best run and the best parameters, for its daily use. This project addresses the validation of the blood filter process by injection molding. The Design of Experiments applied was a 2K factorial design with central points where the replicas consisted of five of 45 in total for the three dimensions. The pieces are shared for those three dimensions that are being evaluated.
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Chaki, Sudipto, i Dipankar Bose. "Application of Artificial Neural Networks to Estimate Tensile Strength of Austenitic Stainless Steel During Metal Inert Gas Welding Process". W Artificial Neural Network Applications in Business and Engineering, 197–221. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-3238-6.ch009.
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In the present work, artificial neural networks (ANN) have been used to model the complex relationship between input-output parameters of metal inert gas (MIG) welding processes. Four ANN training algorithms such as back propagation neural network (BPNN) with gradient descent momentum (GDM), BPNN with Levenberg Marquardt (LM) algorithm, BPNN with Bayesian regularization (BR), and radial basis function networks (RBFN) method have been used for prediction modelling. An experimentation based on full factorial experimental design has been conducted on MIG welding of austenitic stainless steel of grade-304 where welding current, welding speed, and voltage have been considered as input parameters, and tensile strength has been considered as measurable output parameter. The dataset so constituted is used for ANN modelling. Altogether, 40 different ANN architectures have been trained and tested using the above-mentioned algorithms, and 3-11-1 ANN architecture trained using BPNN with BR has been considered to show best prediction capability with mean % absolute error of 0.354%.
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Loskot, Pavel. "Bayesian Methods and Monte Carlo Simulations". W Numerical Simulation [Working Title]. IntechOpen, 2022. http://dx.doi.org/10.5772/intechopen.108699.
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Bayesian methods provide the means for studying probabilistic models of linear as well as non-linear stochastic systems. They allow tracking changes in probability distributions by applying Bayes’s theorem and the chain rule for factoring the probabilities. However, an excessive complexity of resulting distributions often dictates the use of numerical methods when performing statistical and causal inferences over probabilistic models. In this chapter, the Bayesian methods for intractable distributions are first introduced as sampling, filtering, approximation, and likelihood-free methods. Their fundamental principles are explained, and the key challenges are identified. The concise survey of Bayesian methods is followed by outlining their applications. In particular, Bayesian experiment design aims at maximizing information gain or utility, and it is often combined with an optimum model selection. Bayesian hypothesis testing introduces optimality in the data-driven decision making. Bayesian machine learning assumes data labels to be random variables. Bayesian optimization is a powerful strategy for configuring and optimizing large-scale complex systems, for which conventional optimization techniques are usually ineffective. The chapter is concluded by examining Bayesian Monte Carlo simulations. It is proposed that augmented Monte Carlo simulations can achieve explainability and also provide much better information efficiency.
Streszczenia konferencji na temat "Complex factorial experiments"
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Sanikhani, Hamed, Javad Akbari, Ali Reza Shahidi i Ali Akbar Darki. "Modeling and Optimization of an Elliptical Shape Ultrasonic Motor Using Combination of Finite Element Method and Design of Experiments". W ASME 2010 International Mechanical Engineering Congress and Exposition. ASMEDC, 2010. http://dx.doi.org/10.1115/imece2010-40074.
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Standing-wave ultrasonic motors are a modern class of positioning systems, which are used to deliver a high precision linear or rotary motion with an unlimited stroke. The design process should be performed through an effective optimization algorithm in order to guaranty proper and efficient function of these motors. An optimization method of ultrasonic motors is proposed based on the combination of finite element method and factorial design as a design of experiments in this study. The results show the ability of this method in optimal design of ultrasonic motors especially those which have a complex structure and multi modes operation principle.
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Cheng, Bo, i Kevin Chou. "A Design-of-Experiments Approach to Study Thermal Property Effects on Melt Pool Geometry in Powder-Based EBAM". W ASME 2013 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/imece2013-66009.
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Powder-based electron beam additive manufacturing (EBAM) is capable of making full-density metallic parts and has been increasingly utilized to produce complex-shaped, custom-designed Ti-6Al-4V alloy parts. EBAM also has the potential using other various powders materials such as intermetallics. Different materials will have different thermal properties that will result in distinct thermal responses during the EBAM process and thus, selecting adequate process parameters can be challenging. Because virtually all thermal properties would change when a different material was selected, testing individual thermal property is insufficient to understand the anticipated thermal response when a different powder material is to be used. In this study, EBAM process thermal simulations were extended to study the effect of thermal properties in EBAM in a more systematic way using the design of experiments approach. Four factors, two levels, and full factorial experiments were conducted. Three simulation response of melt pool geometry was evaluated using analysis of variance (ANOVA). It is concluded that the thermal conductivity and the melting temperature are the two most significant factors.
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Wu, Dazhong, Changxue Xu i Srikumar Krishnamoorthy. "Predictive Modeling of Droplet Velocity and Size in Inkjet-Based Bioprinting". W ASME 2018 13th International Manufacturing Science and Engineering Conference. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/msec2018-6513.
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Additive manufacturing is driving major innovations in many areas such as biomedical engineering. Recent advances have enabled 3D printing of biocompatible materials and cells into complex 3D functional living tissues and organs using bioink. Inkjet-based bioprinting fabricates the tissue and organ constructs by ejecting droplets onto a substrate. Compared with microextrusion-based and laser-assisted bioprinting, it is very difficult to predict and control the droplet formation process (e.g., droplet velocity and size). To address this issue, this paper presents a new data-driven approach to predict droplet velocity and size in the inkjet-based bioprinting process. An imaging system was used to monitor the droplet formation process. To investigate the effects of excitation voltage, dwell time, and rise time on droplet velocity and droplet size, a full factorial design of experiments was conducted. Two predictive models were developed to predict droplet velocity and droplet size using random forests. The accuracy of the two predictive models was evaluated using the relative error. Experimental results have shown that the predictive models are capable of predicting droplet velocity and size with sufficient accuracy.
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Cebral, Juan R., i Christopher M. Putman. "Relating Wall Shear Stress, Bleb Formation and Rupture of Cerebral Aneurysms: Image-Based Modeling and Clinical Observations". W ASME 2008 Summer Bioengineering Conference. American Society of Mechanical Engineers, 2008. http://dx.doi.org/10.1115/sbc2008-192364.
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Cerebral aneurysms are widely believed to form and grow as a result of the interactions of hemodynamics and wall mechano-biology. Researchers have used a variety of tools to study these complex multi-factorial mechanisms including animal, in vitro, and computational models. The goal of these experiments has been to approximate the in vivo environment so that theories about the natural history of brain aneurysms can be developed and tested in realistic systems. Studying the link between hemodynamics and clinical observations of aneurysm progression is necessary to reach an understanding of the relative importance of the different mechanisms involved in these processes [1]. The objective of our research is to investigate the possible relationship between wall shear stress (WSS) — which is known to regulate mechano-biological processes at the arterial wall — produced by different blood flow patterns and the evolution and rupture of cerebral aneurysms.
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Bhattacharya, A., Samarjit Singh, K. Maneesh, N. Venkata Reddy i Jian Cao. "Formability and Surface Finish Studies in Single Point Incremental Forming". W ASME 2011 International Manufacturing Science and Engineering Conference. ASMEDC, 2011. http://dx.doi.org/10.1115/msec2011-50284.
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Incremental sheet metal forming (ISMF) has demonstrated its great potential to form complex three-dimensional parts without using a component specific tooling. The die-less nature in incremental forming provides a competitive alternative for economically and effectively fabricating low-volume functional sheet parts. However, ISMF has limitations with respect to maximum formable wall angle, geometrical accuracy and surface finish of the component. In the present work, an experimental study is carried out to study the effect of incremental sheet metal forming process variables on maximum formable angle and surface finish. Box-Behnken method is used to design the experiments for formability study and full factorial method is used for surface finish study. Analysis of experimental results indicates that formability in incremental forming decreases with increase in tool diameter. Formable angle first increases and then decreases with incremental depth and it is also observed that the variation in the formable angle is not significant in the range of incremental depths considered to produce good surface finishes during the present study. A simple analysis model is used to estimate the stress values during incremental sheet metal forming assuming that the deformation occurs predominantly under plane strain condition. A stress based criterion is used along with the above mentioned analysis to predict the formability in ISMF and its predictions are in very good agreement with the experimental results. Surface roughness decreases with increase in tool diameter for all incremental depths. Surface roughness increases first with increase in incremental depth up to certain angle and then decreases. Surface roughness value decreases with increase in wall angle.
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Partee, Brock, Scott J. Hollister i Suman Das. "Fabrication of Polycaprolactone Bone Tissue Engineering Scaffolds Using Selective Laser Sintering". W ASME 2004 International Mechanical Engineering Congress and Exposition. ASMEDC, 2004. http://dx.doi.org/10.1115/imece2004-60724.
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Tissue engineering combines principles of the life sciences and engineering to replace and repair damaged human tissue. Present practice generally requires the use of porous, bioresorbable scaffolds to serve as temporary 3D templates to guide cell attachment, differentiation, proliferation, and subsequent regenerate tissue formation. Such scaffolds are anticipated to play an important role in allowing physicians to simultaneously reconstruct and regenerate damaged human tissue such as bone, cartilage, ligament and tendon. Recent research strongly suggests the choice of scaffold material and its internal porous architecture significantly influence regenerate tissue structure and function. However, a lack of versatile biomaterials processing and fabrication methods capable of meeting the complex geometric and compositional requirements of tissue engineering scaffolds has slowed progress towards fully testing these promising findings. It is widely accepted that layered manufacturing methods such as selective laser sintering (SLS) have the potential to fulfill these needs. Our research aims to investigate the viability of using SLS to fabricate tissue engineering scaffolds composed of polycaprolactone (PCL), one of the most widely investigated biocompatible, bioresorbable materials for tissue engineering applications. In this work, we report our recent progress on porous scaffold design and fabrication, optimal SLS processing parameter development using systematic factorial design of experiments, and structural characterization via optical microscopy.
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Yadav, Sunil, Christ P. Paul, Arackal N. Jinoop, Saurav K. Nayak, Arun K. Rai i Kushvinder S. Bindra. "Effect of Process Parameters on Laser Directed Energy Deposition of Copper". W ASME 2019 Gas Turbine India Conference. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/gtindia2019-2453.
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Abstract Laser Additive Manufacturing (LAM) is an advanced manufacturing processes for fabricating engineering components directly from CAD Model by depositing material in a layer by layer fashion using lasers. LAM is being widely deployed in various sectors such as power, aerospace, automotive etc. for fabricating complex shaped and customized components. One of the most commonly used LAM process is Directed Energy Deposition (LAM-DED) which is used for manufacturing near net shaped components with tailored microstructure, multi-materials (direct and graded) and complex geometry. This paper reports experimental investigation of LAM of Copper (Cu) tracks on Stainless Steel 304 L (SS 304L) using an indigenously developed LAM-DED system. Cu-SS304L joints find wider applications in tooling, automotive and aerospace sectors due to its combination of higher strength, thermal conductivity and corrosion resistance. However, laying Cu layers on SS304L is not trivial due to large difference in the thermo-physical properties. Thus, a comprehensive experiments using full factorial design are carried out and a number of Cu tracks were laid on SS304L substrate by varying laser power, scan speed and powder feed rate. The laid tracks are characterized for track geometry and porosity and the quality of the tracks are analyzed. Lower values of laser power and higher powder feed rate results in discontinuous deposition, while higher laser power and lower powder feed rate results in cracked deposits. Porosity is observed to vary from 6–45 % at different process conditions. Analysis of Variance (ANOVA) of deposition rate and track geometry is performed to estimate the major contributing process parameters. This study paves a way to understand effect of process parameters on LAM-DED for fabricating bimetallic joints and graded structures of Copper and SS304L.
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Rauniyar, Santosh, Subin Shrestha i Kevin Chou. "An Investigation Into Multi-Track Deposition in Laser Powder-Bed Fusion: Transient Regions Analysis and Scan Length Effects". W ASME 2022 17th International Manufacturing Science and Engineering Conference. American Society of Mechanical Engineers, 2022. http://dx.doi.org/10.1115/msec2022-85746.
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Abstract Laser powder bed fusion (L-PBF) additive manufacturing has been used to fabricate complex-shaped structures, which often consist of fine features. Due to transient process phenomena, there are differences in terms of the melt pool formation and the surface morphology depending upon the feature area and scan parameters. This study investigates the scan length effect on the surface morphology and the presence of transient length and width that may have a significant effect as the layer addition continues. For this purpose, four scan lengths (0.25 mm, 0.5 mm, 1.0 mm, and 2.0 mm) are used to fabricate six tracks with back-and-forth scanning. A full factorial design of experiments is used to form multi-track depositions with three levels of power (125 W, 160 W, and 195 W), two levels of scan speed (550 mm/s and 1000 mm/s), and four levels of hatch spacing (80 μm, 100 μm, 120 μm, and 140 μm). A white light interferometer is used to acquire the surface data, and MATLAB is used for surface topographical analysis. The results indicated that the scan length has a significant effect on the surface characteristics. The average height of multi-track deposits increases with the decrease of the scan length. Moreover, the transient length and width can be approximated based on the height variation along both the scan and transverse directions, respectively.
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Marbaker, Rachel, Brent Utter, Kevin Eschen i Julianna Abel. "Preliminary Experimental Investigation of Control Parameters for the Electroresistive Heating of SMA Knitted Textiles". W ASME 2019 Conference on Smart Materials, Adaptive Structures and Intelligent Systems. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/smasis2019-5666.
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Abstract Knitted textiles manufactured from shape memory alloy (SMA) monofilaments possess advanced capabilities for distributed and complex actuation and are suited for a range of emerging needs in aerospace, biomedical, and robotics applications. In general, high currents for short periods of time provide sufficient electroresistive (Joule) heat to cause SMA wires to transform to austenite. However, SMA knitted textiles are difficult to electroresistively heat because the interlocking knit structure short-circuits the flow of current, causing localized overheating and isolating the transformation of the material along the current path. One approach for heating SMA knitted textiles is to drive pulses of high current between pairs of electrodes positioned across horizontal courses (rows) of knitted loops. This research presents a preliminary experimental investigation of the effects of factors related to electroresistive heating for SMA knitted textiles. A design of experiments analysis with two levels of four factors was conducted using a 24–1 fractional factorial design. The factors included the voltage of the power supply connected to the current amplifiers; a geometric factor defining the horizontal spacing of the electrodes attached to the knit sample; and two waveform factors: On Cycles and Off/On Cycles, which defined the length of time each current amplifier was enabled and disabled. Actuation performance was quantified by the actuation displacement and actuation force of the knit sample. Preliminary results suggest that voltage is the most influential factor, but also indicate that interactions between the geometric and waveform factors have significant effects on the heating and actuation performance. The characterization of these factor interactions has the potential to inform optimal electroresistive heating approaches for SMA knitted textiles, enabling integration into applications such as wearable technologies where convective heating is not practical.
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Rainsberger, Robert B., Jeffrey T. Fong i Pedro V. Marcal. "A Super-Parametric Approach to Estimating Accuracy and Uncertainty of the Finite Element Method (*)". W ASME 2016 Pressure Vessels and Piping Conference. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/pvp2016-63890.
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A finite element method (FEM)-based solution of an industry-grade problem with complex geometry, partially-validated material property databases, incomplete knowledge of prior loading histories, and an increasingly user-friendly human-computer interface, is extremely difficult to verify because of at least five major sources of errors or solution uncertainty (SU), namely, (SU-1) numerical algorithm of approximation for solving a system of partial differential equations with initial and boundary conditions; (SU-2) the choice of the element type in the design of a finite element mesh; (SU-3) the choice of a mesh density; (SU-4) the quality measures of a finite element mesh such as the mean aspect ratio.; and (SU-5) the uncertainty in the geometric parameters, the physical and material property parameters, the loading parameters, and the boundary constraints. To address this problem, a super-parametric approach to FEM is developed, where the uncertainties in all of the known factors are estimated using three classical tools, namely, (a) a nonlinear least squares logistic fit algorithm, (b) a relative error convergence plot, and (c) a sensitivity analysis based on a fractional factorial orthogonal design of experiments approach. To illustrate our approach, with emphasis on addressing the mesh quality issue, we present a numerical example on the elastic deformation of a cylindrical pipe with a surface crack and subjected to a uniform load along the axis of the pipe.