• 제목/요약/키워드: optimize multiple responses

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Multiple wall dampers for multi-mode vibration control of building structures under earthquake excitation

  • Rahman, Mohammad Sabbir;Chang, Seongkyu;Kim, Dookie
    • Structural Engineering and Mechanics
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    • 제63권4호
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    • pp.537-549
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    • 2017
  • One of the main concerns of civil engineering researchers is developing or modifying an energy dissipation system that can effectively control structural vibrations, and keep the structural response within tolerable limits during unpredictable events like earthquakes, wind and any kind of thrust load. This article proposes a new type of mass damper system for controlling wideband earthquake vibrations, called Multiple Wall Dampers (MWD). The basic principle of the Tuned Mass Damper (TMD) was used to design the proposed wall damper system. This passive energy dissipation system does not require additional mass for the damping system because the boundary wall mass of the building was used as a damper mass. The multi-mode approach was applied to determine the location and design parameters of the dampers. The dampers were installed based on the maximum amplitude of modes. To optimize the damper parameters, the multi-objective optimization Response Surface Methodology was used, with frequency response and maximum displacement as the objective functions. The obtained structural responses under different earthquake forces demonstrated that the MWD is one of the most capable tools for reducing the responses of multi-storied buildings, and this system can be practically used for new and existing building structures.

An interactive multicriteria simulation optimization method

  • Shin, Wan-Seon;Boyle, Carolyn-R.
    • 한국경영과학회:학술대회논문집
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    • 대한산업공학회/한국경영과학회 1992년도 춘계공동학술대회 발표논문 및 초록집; 울산대학교, 울산; 01월 02일 May 1992
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    • pp.117-126
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    • 1992
  • This study proposes a new interactive multicriteria method for determining the best levels of the decision variables needed to optimize a stochastic computer simulation with multiple response variables. The method, called the Pairwise Comparison Stochastic Cutting Plane (PCSCP) method, combines good features from interactive multiple objective mathematical programming methods and response surface methodology. The major characteristics of the PCSCP algorithm are: (1) it interacts progressively with the decision maker (DM) to obtain his preferences, (2) it uses good experimental design to adequately explore the decision space while reducing the burden on the DM, and (3) it uses the preference information provided by the DM and the sampling error in the responses to reduce the decision space. This paper presents the basic concepts of the PCSCP method along with its performance for solving randomly selected test problems.

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A novel heuristic search algorithm for optimization with application to structural damage identification

  • Nobahari, Mehdi;Ghasemi, Mohammad Reza;Shabakhty, Naser
    • Smart Structures and Systems
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    • 제19권4호
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    • pp.449-461
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    • 2017
  • One of the most recent methods of structural damage identification is using the difference between structures responses after and before damage occurrence. To do this one can formulate the damage detection problem as an inverse optimization problem where the extents of damage in each element are considered as the optimizations variables. To optimize the objective function, heuristic methods such as GA, PSO etc. are widely utilized. In this paper, inspired by animals such as bat, dolphin, oilbird, shrew etc. that use echolocation for finding food, a new and efficient method, called Echolocation Search Algorithm (ESA), is proposed to properly identify the site and extent of multiple damage cases in structural systems. Numerical results show that the proposed method can reliably determine the location and severity of multiple damage cases in structural systems.

Multi-response optimization for milling AISI 304 Stainless steel using GRA and DFA

  • Naresh, N.;Rajasekhar, K.
    • Advances in materials Research
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    • 제5권2호
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    • pp.67-80
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    • 2016
  • The objective of the present work is to optimize process parameters namely, cutting speed, feed rate, and depth of cut in milling of AISI 304 stainless steel. In this work, experiments were carried out as per the Taguchi experimental design and an $L_{27}$ orthogonal array was used to study the influence of various combinations of process parameters on surface roughness (Ra) and material removal rate (MRR). As a dynamic approach, the multiple response optimization was carried out using grey relational analysis (GRA) and desirability function analysis (DFA) for simultaneous evaluation. These two methods are considered in optimization, as both are multiple criteria evaluation and not much complicated. The optimum process parameters found to be cutting speed at 63 m/min, feed rate at 600 mm/min, and depth of cut at 0.8 mm. Analysis of variance (ANOVA) was employed to classify the significant parameters affecting the responses. The results indicate that depth of cut is the most significant parameter affecting multiple response characteristics of GFRP composites followed by feed rate and cutting speed. The experimental results for the optimal setting show that there is considerable improvement in the process.

GA-optimized Support Vector Regression for an Improved Emotional State Estimation Model

  • Ahn, Hyunchul;Kim, Seongjin;Kim, Jae Kyeong
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제8권6호
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    • pp.2056-2069
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    • 2014
  • In order to implement interactive and personalized Web services properly, it is necessary to understand the tangible and intangible responses of the users and to recognize their emotional states. Recently, some studies have attempted to build emotional state estimation models based on facial expressions. Most of these studies have applied multiple regression analysis (MRA), artificial neural network (ANN), and support vector regression (SVR) as the prediction algorithm, but the prediction accuracies have been relatively low. In order to improve the prediction performance of the emotion prediction model, we propose a novel SVR model that is optimized using a genetic algorithm (GA). Our proposed algorithm-GASVR-is designed to optimize the kernel parameters and the feature subsets of SVRs in order to predict the levels of two aspects-valence and arousal-of the emotions of the users. In order to validate the usefulness of GASVR, we collected a real-world data set of facial responses and emotional states via a survey. We applied GASVR and other algorithms including MRA, ANN, and conventional SVR to the data set. Finally, we found that GASVR outperformed all of the comparative algorithms in the prediction of the valence and arousal levels.

Neutronic design of pulsed neutron facility (PNF) for PGNAA studies of biological samples

  • Oh, Kyuhak
    • Nuclear Engineering and Technology
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    • 제54권1호
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    • pp.262-268
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    • 2022
  • This paper introduces a novel concept of the pulsed neutron facility (PNF) for maximizing the production of the thermal neutrons and its application to medical use based on prompt gamma neutron activation analysis (PGNAA) using Monte Carlo simulations. The PNF consists of a compact D-T neutron generator, a graphite pile, and a detection system using Cadmium telluride (CdTe) detector arrays. The configuration of fuel pins in the graphite monolith and the design and materials for the moderating layer were studied to optimize the thermal neutron yields. Biological samples - normal and cancerous breast tissues - including chlorine, a trace element, were used to investigate the sensitivity of the characteristic γ-rays by neutron-trace material interactions and the detector responses of multiple particles. Around 90 % of neutrons emitted from a deuterium-tritium (D-T) neutron generator thermalized as they passed through the graphite stockpile. The thermal neutrons captured the chlorines in the samples, then the characteristic γ-rays with specific energy levels of 6.12, 7.80 and 8.58 MeV were emitted. Since the concentration of chlorine in the cancerous tissue is twice that in the normal tissue, the count ratio of the characteristic g-rays of the cancerous tissue over the normal tissue is approximately 2.

A new study in designing MTMDs in SDOF and MDOF systems based on the spectral analysis method

  • Baigoly, Morteza;Shargh, Farzan H.;Rofooei, Fayaz R.
    • Earthquakes and Structures
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    • 제19권4호
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    • pp.243-259
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    • 2020
  • This study aims to optimize, design, and predict the MTMDs performance in SDOF systems using spectral analysis, and then apply their results to MDOF structures. Given the importance of spectral analysis in the design of new engineering structures, achieving a method for designing TMDs based on this theory can be of great importance for structural designers. In this study, several convenient combinations of MTMDs in an SDOF system are first considered to minimize the maximum displacement. For calculating the frequency ratios of dampers, an innovative technique is adopted in which the values of different modal responses obtained from the spectral analysis are approached together. This procedure is done using a harmony search (HS) algorithm. Also, using the random vibration theory, the damping ratio of the dampers is obtained. Then, an equation is presented for predicting the performance of MTMDs. For evaluating this equation, three structures with different stories are designed. Some of the presented combinations of dampers are added to them. The time history analyses are employed to analyze the structures under 30 different accelerograms. The findings indicated that the proposed equation could efficiently predict the performance of the MTMDs. Furthermore, four different patterns of damper distribution along the height of the structures are defined. The effect of them on the maximum deformation of the structures in time history analyses is discussed, and an equation is presented to estimate this effect. The results indicated that the average and maximum error percentages of the proposed equations are about three and seven percent, respectively, compared to the time history analyses results, which are negligible values.

Drivers of Crop Productivity and Resource Use Efficiencies in Apple between Western and Eastern States in the US

  • Kim, Soo-Hyung
    • 한국농림기상학회:학술대회논문집
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    • 한국농림기상학회 2015년도 하계 학술발표논문집
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    • pp.18-28
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    • 2015
  • Apple is cultivated under various climatic conditions in many parts of the world. Better understanding of how climate, genotype, soil, and management factors interact to determine crop productivity will improve our ability to optimize crop selection, management strategies, and resource use efficiencies. We developed and applied a physiology-based apple canopy model to evaluate how climatic factors and crop phenotypes interact to determine biomass accumulation, radiation use efficiency (RUE), and water use efficiency (WUE) at multiple production sites between western and eastern states of the US including WA, CA, NY, WV, and PA. Our results indicate that solar radiation is a dominant factor limiting biomass production in the eastern states while VPD is the primary factor governing crop water use across eastern and western states during the peak growing season. Crop RUE and WUE were strongly correlated in the western states but not in the eastern states while VPD showed highly negative correlation with both RUE and WUE across all locations. The RUE improved with increasing fraction of diffuse radiation ($f_{df}$) and the $RUE-f_{df}$ relationships revealed distinctive responses between western and eastern states. Overall, the eastern locations exhibited slightly higher RUE and WUE than the western locations. However, overall productivity and total water use were greater in the western states. A clear decline of productivity with increasing temperature and afternoon VPD past an optimum was predicted in the western locations but this pattern was less clear in the eastern locations. We also discuss potential phenotypes with specific physiological and morphological traits that are differentially suitable for western and eastern locations. Our results provide plausible, spatially explicit explanations and insights to disentangle the complex relationships between crop productivity, resource use efficiencies, phenotype, and climate drivers in apple grown in the US.

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