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Journal articles on the topic 'Selective parameter'

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Author: Grafiati

Published: 11 March 2023

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1

Gill, Wonpyong. "Computer simulation for the growing probability of additional offspring with an advantageous reversal allele in the decoupled continuous-time mutation–selection model." International Journal of Modern Physics C 27, no. 06 (May 13, 2016): 1650070. http://dx.doi.org/10.1142/s0129183116500704.

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This study calculated the growing probability of additional offspring with the advantageous reversal allele in an asymmetric sharply-peaked landscape using the decoupled continuous-time mutation–selection model. The growing probability was calculated for various population sizes, N, sequence lengths, L, selective advantages, s, fitness parameters, k and measuring parameters, C. The saturated growing probability in the stochastic region was approximately the effective selective advantage, [Formula: see text], when [Formula: see text] and [Formula: see text]. The present study suggests that the growing probability in the stochastic region in the decoupled continuous-time mutation–selection model can be described using the theoretical formula for the growing probability in the Moran two-allele model. The selective advantage ratio, which represents the ratio of the effective selective advantage to the selective advantage, does not depend on the population size, selective advantage, measuring parameter and fitness parameter; instead the selective advantage ratio decreases with the increasing sequence length.

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GILL, WONPYONG. "COMPUTER SIMULATION FOR THE CROSSING TIME IN A DIPLOID, ASYMMETRIC, SHARPLY-PEAKED LANDSCAPE IN THE INFINITE POPULATION LIMIT." International Journal of Modern Physics C 24, no. 01 (January 2013): 1250091. http://dx.doi.org/10.1142/s012918311250091x.

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This study calculated the crossing time in the diploid mutation–selection model in an infinite population limit for various dominance parameters, h, and selective advantages, by switching on a diploid, asymmetric, sharply-peaked landscape, from an initial state which is the steady state in a diploid, sharply-peaked landscape. The crossing time for h < 1 was found to diverge at the critical fitness parameter, which increased with increasing selective advantage and decreased with increasing sequence length. When the sequence length was increased with a fixed extension parameter, there was no crossing time for h < 1 when the sequence length was longer than the critical sequence length, which increased with increasing selective advantage. The crossing time for h ≤ 1 was found to be an exponentially increasing function of the sequence length, and the crossing time for h > 1 became saturated at a long sequence length. The crossing time decreased with increasing selective advantage, mainly because the larger selective advantage caused the increase in relative density of the reversal allele to grow exponentially at an earlier time.

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3

Spencer, Jack, Ke Chen, and Jinming Duan. "Parameter-Free Selective Segmentation With Convex Variational Methods." IEEE Transactions on Image Processing 28, no. 5 (May 2019): 2163–72. http://dx.doi.org/10.1109/tip.2018.2883521.

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4

Yang, Xiong, Ying Shu Liu, and Yong Ling Li. "Study of Adsorption Characteristics on Active Carbon for Ventilation Air Methane Separation." Advanced Materials Research 391-392 (December 2011): 1253–58. http://dx.doi.org/10.4028/www.scientific.net/amr.391-392.1253.

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Nine types of active carbon’s adsorption isotherm of nitrogen and methane at 298K, 308K and 318K were measured, and their selectivity factor and PSA sorption selection parameters were calculated. The results show the nine active carbons have desirable selective adsorption characters on methane to nitrogen. AC3 has the highest selectivity factor. It reaches to 5.11 at 298K. And AC3 is the optimal adsorbent in 9 different adsorbents. Its PSA sorption selection parameter is higher than others with the methane concentration of 0.2% at the operating pressure between 50kPa to 150kPa abs. In above conditions the higher the selectivity factor is, the higher the PSA sorption selection parameter will be.

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5

Filipovich, Oleg, and Vadim Kopp. "Simulation model of selective assembly of two parts with sorting by the estimated values." MATEC Web of Conferences 224 (2018): 01114. http://dx.doi.org/10.1051/matecconf/201822401114.

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The process of one-parameter selective assembly of two parts is considered. Methods for reducing the probability of sorting errors are given. It is suggested to perform the sorting process according to the values of the parameter estimates. For this estimate, a recursion algorithm (the Kalman filter) is used in each cycle. In the environment of GPSS World, a simulation model of selective acquisition and assembly of two parts for determining the parameters of the assembly process is constructed. Comparative modeling results are presented that prove the effectiveness of the algorithm for estimating parameters for selective assembly. The variants of using the algorithm and the prospects for further research are suggested.

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6

Cuesta, I. I., A. Díaz, M. A. Rojo, L. B. Peral, J. Martínez, and J. M. Alegre. "Parameter Optimisation in Selective Laser Melting on C300 Steel." Applied Sciences 12, no. 19 (September 28, 2022): 9786. http://dx.doi.org/10.3390/app12199786.

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Additive manufacturing (AM) of metallic materials is increasingly being adopted in numerous sectors, such as biomedicine, aerospace or automotive industries, due to its versatility in the creation of complex geometries and the minimisation of material waste when compared to traditional subtractive methods. In order to ensure a reliable operation of these parts, however, an in-depth study of the effect of additive manufacturing on mechanical properties, including tensile, fatigue and fracture resistance, is necessary. Among the vast number of methods and materials, this project is focused in one of the most promising techniques for the industry: Selective Laser Melting (SLM) for the production of a tools steel, in particular C300 steel components for the automotive sector. The main objective of this paper is to optimise some of the key parameters in the printing process, such as laser power, laser speed and hatch spacing. These variables are essential to obtain parts with good resistance. To that purpose, tensile tests were performed in 3D printed specimens, and then elastoplastic properties were extracted, organised and analysed through a design of experiments for the subsequent output fitting using the response surface methodology.

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7

Ukar, E., A. Lamikiz, L. N. Lopez De Lacalle, D. Del Pozo, F. Liebana, and A. Sanchez. "Laser polishing parameter optimisation on selective laser sintered parts." International Journal of Machining and Machinability of Materials 8, no. 3/4 (2010): 417. http://dx.doi.org/10.1504/ijmmm.2010.036148.

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8

Huxol, Andrea, and Franz-Josef Villmer. "DoE Methods for Parameter Evaluation in Selective Laser Melting." IFAC-PapersOnLine 52, no. 10 (2019): 270–75. http://dx.doi.org/10.1016/j.ifacol.2019.10.041.

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9

Liu, Junnan, and Xiaoyu Zhang. "Parameter-Adaptive Compensation (PAC) for Processing Underwater Selective Absorption." IEEE Signal Processing Letters 27 (2020): 2178–82. http://dx.doi.org/10.1109/lsp.2020.3042126.

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10

Kosterev, A. A., Y. A. Bakhirkin, F. K. Tittel, S. Blaser, Y. Bonetti, and L. Hvozdara. "Photoacoustic phase shift as a chemically selective spectroscopic parameter." Applied Physics B 78, no. 6 (April 2004): 673–76. http://dx.doi.org/10.1007/s00340-004-1519-1.

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11

Pilipović, Ana, Bogdan Valentan, and Mladen Šercer. "Influence of SLS processing parameters according to the new mathematical model on flexural properties." Rapid Prototyping Journal 22, no. 2 (March 21, 2016): 258–68. http://dx.doi.org/10.1108/rpj-08-2014-0092.

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Purpose The purpose of this paper is the selection of production parameters in selective laser sintering – SLS for the production of quality products (e.g. good mechanical properties). The manufacturing procedure affects the properties, which is especially significant in additive procedures, as the products are not cheap and the procedure and material need to be optimally selected. Design/methodology/approach The paper presents an analysis of the fabrication parameters in selective laser sintering (SLS) that affect the flexural properties of the finished product. Findings The influence of a new parameter has been found, the overlay ratio, and using the mathematical and scheme method, the selection of parameters for obtaining the optimal flexural properties has been proposed. Originality/value The paper presents a new mathematical model for the calculation of the processing parameters in SLS of polymer products and gives a diagram for the determination of which parameters are the best to use for practical purposes.

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12

Naiju, C. D., K. Annamalai, S. Karthik, and Ramaraj Goutham. "Fatigue Reliability of Selective Laser Sintered (SLS) Components Using Weibull Analysis." Applied Mechanics and Materials 232 (November 2012): 891–94. http://dx.doi.org/10.4028/www.scientific.net/amm.232.891.

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Selective laser sintered metallic specimens were tested for fatigue cycles to failure and analyzed for reliability. In this study, Taguchi’s experimental techniques were used to develop a modified L9 orthogonal array. Three different process parameters, laser power, scan spacing and slice thickness were selected for manufacturing the components. Fatigue testing was carried out as per ASTM standards and relationship of the process parameters on the fatigue cycles to failure was investigated. ANOVA method was used to find the dependence of the process parameters and to find the influence of main process parameter on fatigue cycles to failure of the specimens. Laser power was found to be the most significant factor compared to scan speed and slice thickness. Two-parameter Weibull method was used for the reliability studies by which reliability was estimated for different cycles to failure.

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13

Dong, Wei, Jiandong Li, and Zhuo Lu. "Parameter Estimation for Correlated MIMO Channels with Frequency-Selective Fading." Wireless Personal Communications 52, no. 4 (January 31, 2009): 813–28. http://dx.doi.org/10.1007/s11277-009-9664-9.

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14

TEO, K. A. D., and S. OHNO. "Finite Parameter Model for Doubly-Selective Channel Estimation in OFDM." IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences E90-A, no. 11 (November 1, 2007): 2395–403. http://dx.doi.org/10.1093/ietfec/e90-a.11.2395.

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15

Aksikas, Ahmed, Ilyasse Aksikas, Robert E. Hayes, and Fraser J. Forbes. "Optimal Boundary Control for Selective Catalytic Reduction Distributed Parameter Model." IFAC-PapersOnLine 51, no. 32 (2018): 286–91. http://dx.doi.org/10.1016/j.ifacol.2018.11.397.

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16

Hassan, Amal S., Rasha S. Elshaarawy, and Heba F. Nagy. "Parameter estimation of exponentiated exponential distribution under selective ranked set sampling." Statistics in Transition New Series 23, no. 4 (December 1, 2022): 37–58. http://dx.doi.org/10.2478/stattrans-2022-0041.

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Abstract Partial ranked set sampling (PRSS) is a cost-effective sampling method. It is a combination of simple random sample (SRS) and ranked set sampling (RSS) designs. The PRSS method allows flexibility for the experimenter in selecting the sample when it is either difficult to rank the units within each set with full confidence or when experimental units are not available. In this article, we introduce and define the likelihood function of any probability distribution under the PRSS scheme. The performance of the maximum likelihood estimators is examined when the available data are assumed to have an exponentiated exponential (EE) distribution via some selective RSS schemes as well as SRS. The suggested ranked schemes include the PRSS, RSS, neoteric RSS (NRSS), and extreme RSS (ERSS). An intensive simulation study was conducted to compare and explore the behaviour of the proposed estimators. The study demonstrated that the maximum likelihood estimators via PRSS, NRSS, ERSS, and RSS schemes are more efficient than the corresponding estimators under SRS. A real data set is presented for illustrative purposes.

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17

Liao, Hsin Te, and Manh Trung Le. "Optimization on Selective Fiber Laser Sintering of Metallic Powder." Advanced Materials Research 472-475 (February 2012): 2519–30. http://dx.doi.org/10.4028/www.scientific.net/amr.472-475.2519.

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Purpose – The objective of this study is to investigate the effect of various parameters on rapid prototyping parts for processes of sintering metallic powder by using fiber laser via the design of experiments (DOE) method. Design/methodology/approach – Experiments based on the DOE method were utilized to determine an optimal parameter setting for achieving a minimum amount of porosities in specimens during the selective laser sintering (SLS) process. Analysis of variance (ANOVA) was further conducted to identify significant factors. Findings – A regression model predicting percentages of porosities under various conditions was developed when the traditional Taguchi’s approach failed to identify a feasible model due to strong interactions of controlled factors. The significant factors to the process were identified by ANOVA. Research limitations/implications – Four controlled factors including pulse frequencies and scan rate of laser beams, laser power and scan line spacing with particle sizes of 5µm of the powder base material had significant influence on the sintering process. Future investigation planned to be carried out for achieving multiple quality targets such as the hardness and the density for 3D parts. Originality/value – The implementation of the DOE method provided a systematic approach to identify an optimal parameter setting of the SLS process; thus, the efficiency of designing optimal parameters was greatly improved. This approach could be easily extended to 3D cases by just including additional parameters into the design. Additionally, utilization of the normality analysis on the residual data ensured that the selected model was adequate and extracted all applicable information from the experimental data.

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18

Lykov, P. A. "The Energy Density as a Reliable Parameter for Characterization of Selective Laser Melting of Various Alloys." Materials Science Forum 946 (February 2019): 972–77. http://dx.doi.org/10.4028/www.scientific.net/msf.946.972.

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Various "energy density" parameters are used very often for comparison of fabrication modes for Selective Laser Melting (SLM) technology. Each SLM mode is determined by a number of process parameters. In this paper the energy density was considered critically as a reliable parameter for characterization of Selective Laser Melting of four various alloys on one SLM machine, on the example of fabrication of cubic specimen. The results obtained show that the energy density can be used for approximate comparison of SLM modes.

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19

Li, Zhonghua, Ibrahim Kucukkoc, David Z. Zhang, and Fei Liu. "Optimising the process parameters of selective laser melting for the fabrication of Ti6Al4V alloy." Rapid Prototyping Journal 24, no. 1 (January 2, 2018): 150–59. http://dx.doi.org/10.1108/rpj-03-2016-0045.

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Purpose Surface roughness is an important evaluation index for industrial components, and it strongly depends on the processing parameters for selective laser molten Ti6Al4V parts. This paper aims to obtain an optimum selective laser melting (SLM) parameter set to improve the surface roughness of Ti6Al4V samples. Design/methodology/approach A response surface methodology (RSM)-based approach is proposed to improve the surface quality of selective laser molten Ti6Al4V parts and understand the relationship between the SLM process parameters and the surface roughness. The main SLM parameters (i.e. laser power, scan speed and hatch spacing) are optimized, and Ti6Al4V parts are manufactured by the SLM technology with no post processes. Findings Optimum process parameters were obtained using the RSM method to minimise the roughness of the top and vertical side surfaces. Obtained parameter sets were evaluated based on their productivity and surface quality performance. The validation tests have been performed, and the results verified the effectivity of the proposed technique. It was also shown that the top and vertical sides must be handled together to obtain better top surface quality. Practical implications The obtained optimum SLM parameter set can be used in the manufacturing of Ti6Al4V components with high surface roughness requirement. Originality/value RSM is used to analyse and determine the optimal combination of SLM parameters with the aim of improving the surface roughness quality of Ti6Al4V components, for the first time in the literature. Also, this is the first study which aims to simultaneously optimise the surface quality of top and vertical sides of titanium alloys.

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20

Chen, Yingyan, Hongze Wang, Yi Wu, and Haowei Wang. "Predicting the Printability in Selective Laser Melting with a Supervised Machine Learning Method." Materials 13, no. 22 (November 10, 2020): 5063. http://dx.doi.org/10.3390/ma13225063.

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Though selective laser melting (SLM) has a rapidly increasing market these years, the quality of the SLM-fabricated part is extremely dependent on the process parameters. However, the current metallographic examination method to find the parameter window is time-consuming and involves subjective assessments of the experimenters. Here, we proposed a supervised machine learning (ML) method to detect the track defect and predict the printability of material in SLM intelligently. The printed tracks were classified into five types based on the measured surface morphologies and characteristics. The classification results were used as the target output of the ML model. Four indicators had been calculated to evaluate the quality of the tracks quantitatively, serving as input variables of the model. The data-driven model can determine the defect-free process parameter combination, which significantly improves the efficiency in searching the process parameter window and has great potential for the application in the unmanned factory in the future.

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21

Aggarwal, Neha, Kamanasish Debnath, Sonam Mahajan, Aranya B. Bhattacherjee, and Man Mohan. "Selective entanglement in a two-mode optomechanical system." International Journal of Quantum Information 12, no. 04 (June 2014): 1450024. http://dx.doi.org/10.1142/s0219749914500245.

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We analyze an optomechanical system formed by a mechanical mode and the two optical modes of an optomechanical cavity for the realization of a strongly quantum correlated three-mode system. We show that the steady state of the system shows three possible bipartite continuous variable (CV) entanglements in an experimentally accessible parameter regime, which are robust against temperature. We further show that selective entanglement between the mechanical mode and any of the two optical modes is also possible by the proper choice of the system parameters. Such a two-mode optomechanical system can be used for the realization of CV quantum information interfaces and networks.

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22

Kang, Burong, Zhengan Huang, and Lei Zhang. "Selective-Opening Security for Public-Key Encryption in the Presence of Parameter Subversion." Security and Communication Networks 2021 (October 23, 2021): 1–16. http://dx.doi.org/10.1155/2021/5895809.

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In public-key encryption (PKE), ciphertexts received by a receiver may be possibly correlated and the security of a PKE relies on honestly generated system parameters. Security against selective opening attacks (SOA) for PKE guarantees that even when an attacker has broken into a subset of honestly generated ciphertexts and opened them (i.e., seeing plaintexts and random bits), the unopened ciphertexts remain secure. While security against parameter subversion attacks (PSA) for PKE requires that even when the public system parameters are maliciously generated, a PKE scheme should be secure. In this paper, we initiate the study of PKE secure against both SOA and PSA. To capture SOA and PSA simultaneously, we formulate a new security notion called indistinguishability under selective opening attacks and parameter subversion attacks (IND-SO-PSA). Further, we define the lossy trapdoor function and all-but-many lossy trapdoor function in the presence of PSA (LTF-PSA and ABM-LTF-PSA correspondingly) and propose an instantiation with the efficiently-embeddable group (EG). Applying these new primitives, we construct a PKE scheme that is proven to be IND-SO-PSA secure.

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23

Ju, Cheng, Richard Wyss, Jessica M. Franklin, Sebastian Schneeweiss, Jenny Häggström, and Mark J. van der Laan. "Collaborative-controlled LASSO for constructing propensity score-based estimators in high-dimensional data." Statistical Methods in Medical Research 28, no. 4 (December 11, 2017): 1044–63. http://dx.doi.org/10.1177/0962280217744588.

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Propensity score-based estimators are increasingly used for causal inference in observational studies. However, model selection for propensity score estimation in high-dimensional data has received little attention. In these settings, propensity score models have traditionally been selected based on the goodness-of-fit for the treatment mechanism itself, without consideration of the causal parameter of interest. Collaborative minimum loss-based estimation is a novel methodology for causal inference that takes into account information on the causal parameter of interest when selecting a propensity score model. This “collaborative learning” considers variable associations with both treatment and outcome when selecting a propensity score model in order to minimize a bias-variance tradeoff in the estimated treatment effect. In this study, we introduce a novel approach for collaborative model selection when using the LASSO estimator for propensity score estimation in high-dimensional covariate settings. To demonstrate the importance of selecting the propensity score model collaboratively, we designed quasi-experiments based on a real electronic healthcare database, where only the potential outcomes were manually generated, and the treatment and baseline covariates remained unchanged. Results showed that the collaborative minimum loss-based estimation algorithm outperformed other competing estimators for both point estimation and confidence interval coverage. In addition, the propensity score model selected by collaborative minimum loss-based estimation could be applied to other propensity score-based estimators, which also resulted in substantive improvement for both point estimation and confidence interval coverage. We illustrate the discussed concepts through an empirical example comparing the effects of non-selective nonsteroidal anti-inflammatory drugs with selective COX-2 inhibitors on gastrointestinal complications in a population of Medicare beneficiaries.

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NAGATO, Keisuke, Morio TOMIZAWA, Takayuki OSA, and Yoshitaka USHIKU. "In-situ observation of selective-laser melting and process-parameter search." Proceedings of Mechanical Engineering Congress, Japan 2020 (2020): S13203. http://dx.doi.org/10.1299/jsmemecj.2020.s13203.

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25

Ren, Xi, Changlin Liu, and Minghui Zeng. "S11 Parameter Calculation of Frequency Selective Surface Based on Deep Learning." Journal of Physics: Conference Series 1865, no. 4 (April 1, 2021): 042022. http://dx.doi.org/10.1088/1742-6596/1865/4/042022.

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26

Chang, Liang, Geoffrey Ye Li, Jingchun Li, and Rong Li. "Blind Parameter Estimation of GFDM Signals Over Frequency-Selective Fading Channels." IEEE Transactions on Communications 64, no. 3 (March 2016): 1120–31. http://dx.doi.org/10.1109/tcomm.2016.2523502.

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27

Kempen, K., L. Thijs, J. Van Humbeeck, and J. P. Kruth. "Processing AlSi10Mg by selective laser melting: parameter optimisation and material characterisation." Materials Science and Technology 31, no. 8 (November 3, 2014): 917–23. http://dx.doi.org/10.1179/1743284714y.0000000702.

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28

Guarnieri, Massimo, Enrico Negro, Vito Di Noto, and Piergiorgio Alotto. "A selective hybrid stochastic strategy for fuel-cell multi-parameter identification." Journal of Power Sources 332 (November 2016): 249–64. http://dx.doi.org/10.1016/j.jpowsour.2016.09.131.

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29

Sandgren, Niclas, Petre Stoica, and Frederick J. Frigo. "Area-selective signal parameter estimation for two-dimensional MR spectroscopy data." Journal of Magnetic Resonance 183, no. 1 (November 2006): 50–59. http://dx.doi.org/10.1016/j.jmr.2006.07.018.

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30

Talhi, Bachagha, Frédéric Monette, and Abdelkrim Azzouz. "Effective and selective nitrate electroreduction into nitrogen through synergistic parameter interactions." Electrochimica Acta 58 (December 2011): 276–84. http://dx.doi.org/10.1016/j.electacta.2011.09.044.

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31

Nguyen, Sang V. "Genetic parameter estimates for important traits on the fifth generation in red tilapia in Vietnam." Journal of Agriculture and Development 20, no. 1 (February 26, 2021): 49–57. http://dx.doi.org/10.52997/jad.7.01.2021.

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Genetic parameters comprising heritability, genetic correlation and genotype by environment interaction (GxE) for growth survival rate and body colour at harvest were estimated on the 5th selective generation of red tilapia grown in two environments, freshwater and brackishwater ponds. A total of 116 full-half-sib families was produced as well as 4,432 and 3,811 tagged individuals were tested in freshwater and brackishwater ponds, respectively. Genetic parameters were estimated by ASReml 4.1 software. The heritability for body weight and survival rate was high while medium heritability for body colour in freshwater was observed. The heritability for those traits of red tilapia in brackishwater. Together with the figures in earlier publication on previous generations (G1 to G4) in the same selective population, the expected medium to high response acquires if selection is done for each trait. Genetic correlations among harvest body weight, survival rate and body colour are insignificantly different and ranging from -0.25 to 0.37 (P > 0.05). These results implied that selection on one trait do not influence on responses of the other traits. GxE interaction for body weight and body colour between two tested environments is mostly negligible with genetic correlations ranging from 0.63 - 0.80 while it is important for survival trait (rg = -0.17 ± 0.40).

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DENTSORAS, ARGIRIS J. "A selective, multiple-criteria method for handling constraint violations in well-defined design problems." Artificial Intelligence for Engineering Design, Analysis and Manufacturing 13, no. 3 (June 1999): 205–15. http://dx.doi.org/10.1017/s0890060499133067.

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A selective, multiple-criteria method is proposed for handling constraint violations in well-defined design problems. First, the types of design problems upon which the method may apply are presented and a graph topology is adopted for representing the problem decomposition in the level of design parameter interrelations (design parameter graphs). Next, the problem of constraint violations for the design parameters is discussed. It is shown that these violations can be resolved by modifying the values of the primary design parameters and recalculating the values of the violated parameters. Any “blind” attempt of modifying the values of the primary design parameters for resolving occurring violations may, eventually, create additional violations. The proposed method guides the designer toward those primary design parameters that present the least possibility of creating more violations when their values are modified. This is achieved by applying multiple criteria and by producing a final, sorted list of primary design parameters. The designer may then choose the first element of this list to handle efficiently the violations of the design parameters. Two examples are given on a design space where constraint violations occur. Through these examples, the capability of the proposed method in helping the designer to handle constraint violation is shown. The concluding remarks, except for summarizing the potential of the method, determine its boundaries and include a reference on relative work currently under investigation.

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33

Ansari, Peyman, Asif Ur Rehman, Fatih Pitir, Salih Veziroglu, Yogendra Kumar Mishra, Oral Cenk Aktas, and Metin U. Salamci. "Selective Laser Melting of 316L Austenitic Stainless Steel: Detailed Process Understanding Using Multiphysics Simulation and Experimentation." Metals 11, no. 7 (July 5, 2021): 1076. http://dx.doi.org/10.3390/met11071076.

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The parameter sets used during the selective laser melting (SLM) process directly affect the final product through the resulting melt-pool temperature. Achieving the optimum set of parameters is usually done experimentally, which is a costly and time-consuming process. Additionally, controlling the deviation of the melt-pool temperature from the specified value during the process ensures that the final product has a homogeneous microstructure. This study proposes a multiphysics numerical model that explores the factors affecting the production of parts in the SLM process and the mathematical relationships between them, using stainless steel 316L powder. The effect of laser power and laser spot diameter on the temperature of the melt-pool at different scanning velocities were studied. Thus, mathematical expressions were obtained to relate process parameters to melt-pool temperature. The resulting mathematical relationships are the basic elements to design a controller to instantly control the melt-pool temperature during the process. In the study, test samples were produced using simulated parameters to validate the simulation approach. Samples produced using simulated parameter sets resulting in temperatures of 2000 K and above had acceptable microstructures. Evaporation defects caused by extreme temperatures, unmelted powder defects due to insufficient temperature, and homogenous microstructures for suitable parameter sets predicted by the simulations were obtained in the experimental results, and the model was validated.

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Qian, Ya, Wentao Yan, and Feng Lin. "Parametric study and surface morphology analysis of electron beam selective melting." Rapid Prototyping Journal 24, no. 9 (November 12, 2018): 1586–98. http://dx.doi.org/10.1108/rpj-05-2017-0088.

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Purpose This paper aims to study the effect of processing parameters and the fundamental mechanism of surface morphologies during electron beam selective melting. Design/methodology/approach From the powder-scale level, first, the discrete element method is used to obtain the powder bed distribution that is comparable with the practical condition; then, the finite volume method is used to simulate the particle melting and flowing process. A physically reliable energy distribution of the electron beam is applied and the volume of fluid method is coupled to capture the free boundary flow. Twelve sets of parameters grouped into three categories are examined, focusing on the effect of scan speed, input powder and energy density. Findings According to the results, both melting pool width and depth have a positive relation with the energy density, whereas the melting pool length is insensitive to the scan velocity change. The balling effect is attributed to either an insufficient energy input or the flow instability; the hump effect originates from the mismatch between electron beam moving and the fluid flow. The scan speed is a key parameter closely related to melting pool size and surface morphologies. Originality/value Through a number of case studies, this paper gives a comprehensive insight of the parameter effects and mechanisms of different surface morphologies, which helps to better control the manufacturing quality of electron beam selective melting.

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35

Bai, Shigang, Nataliya Perevoshchikova, Yu Sha, and Xinhua Wu. "The Effects of Selective Laser Melting Process Parameters on Relative Density of the AlSi10Mg Parts and Suitable Procedures of the Archimedes Method." Applied Sciences 9, no. 3 (February 11, 2019): 583. http://dx.doi.org/10.3390/app9030583.

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In view of the importance of accurately measuring the relative density of a selective laser melted (SLMed) part for optimizing the selective laser melting (SLM) processing parameters, suitable procedures of the Archimedes method considering the surface-connected cavities were proposed by comparing the results using the Archimedes method with image analysis. The effects of the SLM processing parameters on the relative density of AlSi10Mg were investigated using the proposed procedures of the Archimedes methods and image analysis. Fourteen SLMed samples were produced by different SLM processing parameters according to Doehlert Matrix. The regression models correlating relative density and three SLM processing parameters (laser power, scan speed, and hatching distance) were built and the optimum parameter combination to get a high relative density was obtained. By plotting the response surfaces and contours of the regression models, it was found that the relative densities are both higher at the combination of the higher scan speed, higher power, and lower hatching distance and at the combination of a lower scan speed, a moderate laser power, and a optional hatching distance. It was also found that the parameter of hatching distance is the crucial parameter to get a high relative density and to get high mechanical property.

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Kurzynowski, Tomasz, Wojciech Stopyra, Konrad Gruber, Grzegorz Ziółkowski, Bogumiła Kuźnicka, and Edward Chlebus. "Effect of Scanning and Support Strategies on Relative Density of SLM-ed H13 Steel in Relation to Specimen Size." Materials 12, no. 2 (January 11, 2019): 239. http://dx.doi.org/10.3390/ma12020239.

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Standard experimental research works are aimed at optimization of Selective Laser Melting (SLM) parameters in order to produce material with relative density over 99% and possibly the highest scanning speed. Typically, cuboidal specimens with arbitrarily selected dimensions are built. An optimum set of parameters, determined on such specimens, is used for building parts with variable cross-section areas. However, it gives no guarantee that the density of variable-section parts produced with so selected parameters will be as high as that of the specimens measured during the parameters optimization process. The goal of this work was to improve the process of SLM parameter selection according to the criterion of maximum relative density, based on the example of AISI H13 tool steel (1.2344). A selection method of scanning strategy ensuring relative density of parts over 99%, irrespective of their dimensions, was determined. The specimens were produced using several variants of support structures. It was found that proper selection of the support strategy prevents development of columnar pores.

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Kim, Woohyun, Khaja Mohaideen Kamal, Dong Joo Seo, and Wang Lai Yoon. "Kinetic Study on CO-Selective Methanation over Nickel-Based Catalysts for Deep Removal of CO from Hydrogen-Rich Reformate." Catalysts 11, no. 12 (November 24, 2021): 1429. http://dx.doi.org/10.3390/catal11121429.

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The CO-selective methanation process is considered as a promising CO removal process for compact fuel processors producing hydrogen, since the process selectively converts the trace of CO in the hydrogen-rich gas into methane without additional reactants. Two different types of efficient nickel-based catalysts, showing high activity and selectivity to the CO methanation reaction, were developed in our previous works; therefore, the kinetic models of the reactions over these nickel-based catalysts have been investigated adopting the mechanistic kinetic models based on the Langmuir chemisorption theory. In the methanation process, the product species can react with the reactant and also affect the adsorption/desorption of the molecules at the active sites. Thus, the kinetic parameter study should be carried out by global optimization handling all the rate equations for the plausible reactions at once. To estimate the kinetic parameters, an effective optimization algorithm combining both heuristic and deterministic methods is used due to the large solution space and the nonlinearity of the objective function. As a result, 14 kinetic parameters for each catalyst have been determined and the parameter sets for the catalysts have been compared to understand the catalytic characteristics.

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Aris-Brosou, Stéphane. "Identifying sites under positive selection with uncertain parameter estimates." Genome 49, no. 7 (July 1, 2006): 767–76. http://dx.doi.org/10.1139/g06-038.

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Codon-based substitution models are routinely used to measure selective pressures acting on protein-coding genes. To this effect, the nonsynonymous to synonymous rate ratio (dN/dS = ω) is estimated. The proportion of amino-acid sites potentially under positive selection, as indicated by ω > 1, is inferred by fitting a probability distribution where some sites are permitted to have ω > 1. These sites are then inferred by means of an empirical Bayes or by a Bayes empirical Bayes approach that, respectively, ignores or accounts for sampling errors in maximum-likelihood estimates of the distribution used to infer the proportion of sites with ω > 1. Here, we extend a previous full-Bayes approach to include models with high power and low false-positive rates when inferring sites under positive selection. We propose some heuristics to alleviate the computational burden, and show that (i) full Bayes can be superior to empirical Bayes when analyzing a small data set or small simulated data, (ii) full Bayes has only a small advantage over Bayes empirical Bayes with our small test data, and (iii) Bayesian methods appear relatively insensitive to mild misspecifications of the random process generating adaptive evolution in our simulations, but in practice can prove extremely sensitive to model specification. We suggest that the codon model used to detect amino acids under selection should be carefully selected, for instance using Akaike information criterion (AIC).Key words: codon substitution models, empirical Bayes, Bayes empirical Bayes, full Bayes, ROC curves, AIC.

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Mohammadifakhr, Mehrdad, Joris de Grooth, Hendrik D. W. Roesink, and Antoine J. B. Kemperman. "Forward Osmosis: A Critical Review." Processes 8, no. 4 (March 30, 2020): 404. http://dx.doi.org/10.3390/pr8040404.

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The use of forward osmosis (FO) for water purification purposes has gained extensive attention in recent years. In this review, we first discuss the advantages, challenges and various applications of FO, as well as the challenges in selecting the proper draw solution for FO, after which we focus on transport limitations in FO processes. Despite recent advances in membrane development for FO, there is still room for improvement of its selective layer and support. For many applications spiral wound membrane will not suffice. Furthermore, a defect-free selective layer is a prerequisite for FO membranes to ensure low solute passage, while a support with low internal concentration polarization is necessary for a high water flux. Due to challenges affiliated to interfacial polymerization (IP) on non-planar geometries, we discuss alternative approaches to IP to form the selective layer. We also explain that, when provided with a defect-free selective layer with good rejection, the membrane support has a dominant influence on the performance of an FO membrane, which can be estimated by the structural parameter (S). We emphasize the necessity of finding a new method to determine S, but also that predominantly the thickness of the support is the major parameter that needs to be optimized.

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Baitimerov, R. M., P. A. Lykov, L. V. Radionova, and E. V. Safonov. "Parameter optimization for selective laser melting of TIAL6V4 alloy by CO2 laser." Bulletin of the South Ural State University series "Mechanical Engineering Industry" 17, no. 03 (2017): 36–40. http://dx.doi.org/10.14529/engin170304.

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Leal, Malena Ley Bun, Barbara Bermudez-Reyes, Patricia del Carmen Zambrano Robledo, and Omar Lopez-Botello. "Parameter optimization of aluminum alloy thin structures obtained by Selective Laser Melting." MRS Advances 4, no. 55-56 (2019): 2997–3005. http://dx.doi.org/10.1557/adv.2019.434.

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ABSTRACTSelective Laser Melting (SLM) involves numerous fabrication parameters, the interaction between those parameters determine the final characteristics of the resulting part and because of the latter, it is considered a complex process. Low-density components is one of the main issues of the SLM process, due to the incorrect selection of process parameters. These defects are undesired in high specialized applications (i.e. aerospace, aeronautic and medical industries). Therefore, the characterization of the defects (pores) found in aluminum parts manufacture by SLM and the relationship with fabrication parameters was performed. A robust orthogonal design of experiments was implemented to determine process parameters, and then parts were manufactured in SLM. Relative density of the samples was then characterized using the Archimedes principle and microscopy; the data was then statistically analyzed in order to determine the optimal process parameters. The main purpose of the present research was to establish the best processing parameters of an in-house SLM system, as well as to characterize the pore geometry in order to fully eliminate pores in a future research.

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Chandler, Howard A., Christopher Feuillade, and George B. Smith. "Selective high‐resolution environmental parameter estimation using sector‐focused matched‐field processing." Journal of the Acoustical Society of America 98, no. 5 (November 1995): 2932. http://dx.doi.org/10.1121/1.414155.

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Kuroda, T., and T. Matsumoto. "Multicarrier signal detection and parameter estimation in frequency-selective Rayleigh fading channels." IEEE Transactions on Vehicular Technology 46, no. 4 (1997): 882–90. http://dx.doi.org/10.1109/25.653062.

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Rao, A. K., Y. F. Huang, and S. Dasgupta. "ARMA parameter estimation using a novel recursive estimation algorithm with selective updating." IEEE Transactions on Acoustics, Speech, and Signal Processing 38, no. 3 (March 1990): 447–57. http://dx.doi.org/10.1109/29.106863.

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Grabska-Barwińska, Agnieszka, Benedict Shien Wei Ng, and Dirk Jancke. "Orientation selective or not? – Measuring significance of tuning to a circular parameter." Journal of Neuroscience Methods 203, no. 1 (January 2012): 1–9. http://dx.doi.org/10.1016/j.jneumeth.2011.08.026.

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Eggeling, C., S. Berger, L. Brand, J. R. Fries, J. Schaffer, A. Volkmer, and C. A. M. Seidel. "Data registration and selective single-molecule analysis using multi-parameter fluorescence detection." Journal of Biotechnology 86, no. 3 (April 2001): 163–80. http://dx.doi.org/10.1016/s0168-1656(00)00412-0.

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Baitimerov, R. M., P. A. Lykov, L. V. Radionova, and E. V. Safonov. "Parameter optimization for selective laser melting of TiAl6V4 alloy by CO2 laser." IOP Conference Series: Materials Science and Engineering 248 (October 2017): 012012. http://dx.doi.org/10.1088/1757-899x/248/1/012012.

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Al Athamneh, Raed, Francy Akkara, and Sa'd Hamasha. "A New Approach for Assessing the Reliability of Electronic Assemblies Using Fuzzy Logic for Multi-criteria Optimization." Journal of Microelectronics and Electronic Packaging 19, no. 1 (January 1, 2022): 39–47. http://dx.doi.org/10.4071/imaps.1665996.

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Abstract The reliability of electronic assemblies is a vital criterion used to assure product quality over its lifetime. Weibull distribution is the most common distribution utilized to describe the reliability data. Most of the studies use the Weibull scale parameter, or characteristic life, to compare alternatives and make a selective decision. This may not lead to achieving the optimal parameters which can be problematic because this method doesn’t consider the variability behavior of the fatigue life. In this study, a new approach for process parameters selection is proposed to find the optimal parameter values that improve the micro-optimality selection process based on reliability data. In this study, a new approach is proposed based on examining the solder joint reliability by using a multi criteria analysis. The fuzzy logic is utilized as a tool to solve the multi criteria problem that is presented from the proposed approach. The reliability of microelectronic connections in thermal cycling operating conditions is used as a validation case study. In the validation case study, the optimal process parameters are found for ball grid array electronic components. Two levels of the solder sphere materials, three levels of the surface finish, and 10 levels of solder paste alloys are studied as process parameters. Using the proposed approach, four quality responses are employed to assess the reliability data, including the scale parameter, the B10 (life at 10% of the population failure), mean-standard deviation response, and the signal to noise ratio (SNR). The fuzzy logic is applied to solve the multiresponse problem. An optimal process parameter setting that considers different quality characteristics was found for the validation case study. ENIG surface finish, SAC305 solder sphere, and material six were the optimal factor levels that are obtained for the aged CABGA208 component using the proposed approach.

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Sisco, Nicholas J., Ping Wang, Ashley M. Stokes, and Richard D. Dortch. "Rapid parameter estimation for selective inversion recovery myelin imaging using an open-source Julia toolkit." PeerJ 10 (March 29, 2022): e13043. http://dx.doi.org/10.7717/peerj.13043.

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Background Magnetic resonance imaging (MRI) is used extensively to quantify myelin content, however computational bottlenecks remain challenging for advanced imaging techniques in clinical settings. We present a fast, open-source toolkit for processing quantitative magnetization transfer derived from selective inversion recovery (SIR) acquisitions that allows parameter map estimation, including the myelin-sensitive macromolecular pool size ratio (PSR). Significant progress has been made in reducing SIR acquisition times to improve clinically feasibility. However, parameter map estimation from the resulting data remains computationally expensive. To overcome this computational limitation, we developed a computationally efficient, open-source toolkit implemented in the Julia language. Methods To test the accuracy of this toolkit, we simulated SIR images with varying PSR and spin-lattice relaxation time of the free water pool (R1f) over a physiologically meaningful scale from 5% to 20% and 0.5 to 1.5 s−1, respectively. Rician noise was then added, and the parameter maps were estimated using our Julia toolkit. Probability density histogram plots and Lin’s concordance correlation coefficients (LCCC) were used to assess accuracy and precision of the fits to our known simulation data. To further mimic biological tissue, we generated five cross-linked bovine serum albumin (BSA) phantoms with concentrations that ranged from 1.25% to 20%. The phantoms were imaged at 3T using SIR, and data were fit to estimate PSR and R1f. Similarly, a healthy volunteer was imaged at 3T, and SIR parameter maps were estimated to demonstrate the reduced computational time for a real-world clinical example. Results Estimated SIR parameter maps from our Julia toolkit agreed with simulated values (LCCC > 0.98). This toolkit was further validated using BSA phantoms and a whole brain scan at 3T. In both cases, SIR parameter estimates were consistent with published values using MATLAB. However, compared to earlier work using MATLAB, our Julia toolkit provided an approximate 20-fold reduction in computational time. Conclusions Presented here, we developed a fast, open-source, toolkit for rapid and accurate SIR MRI using Julia. The reduction in computational cost should allow SIR parameters to be accessible in clinical settings.

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Smeshnoi, I. A., I. N. Pasechnik, E. I. Skobelev, D. A. Timashkov, М. A. Onegin, Yu V. Nikiforov, and S. I. Kontarev. "Infusion Therapy Optimization in Selective Abdominal Surgery." General Reanimatology 14, no. 5 (October 28, 2018): 4–15. http://dx.doi.org/10.15360/1813-9779-2018-5-4-15.

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Purpose. Evaluation of the influence of intra-operative targeted infusion therapy managed by the monitoring of stroke volume variability on post-operative results of major surgeries of gastrointestinal organs.Materials and Methods. The prospective study included 80 patients subjected to selective operative interventions of abdominal organs involving entero-enteroanastomosis. In the experimental group (n=39), the infusion therapy was conducted according to the developed targeted therapy protocol, of which the key parameter was stroke volume variability. In the control group (n=41), infusion therapy was conducted based on routine hemodynamic monitoring (average arterial pressure, heart rate, blood loss level with regard to intra-operative situation). In both groups, operative intervention was carried out in identical conditions (combined anesthesia, identical drugs to induce and maintain anesthesia); the only differences included infusion therapy.Results. In the experimental group versus the control group the intra-operative infusion volume was smaller, the number of patients with complications and the total number of complications were reliably lower, and the gastrointestinal tract functional recovery occurred earlier. Conclusion. A targeted infusion therapy based on a stroke volume variability monitoring as the key parameter allows optimizing the infusion load and facilitates reduction of the number of patients with complications and earlier recovery of gastrointestinal tract functions after major operative abdominal interventions.

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