• Title/Summary/Keyword: predictive equation

Search Result 246, Processing Time 0.03 seconds

A Behavior of Welding Distortion at the Thick Weldment of AA5083 (후판 AA5083합금 용접부의 변형 거동)

  • 신상범;이동주
    • Proceedings of the KWS Conference
    • /
    • 2004.05a
    • /
    • pp.234-236
    • /
    • 2004
  • The purpose of this study is to establish the predictive equation of welding distortion at the thick AA5083 alloy weldment. In order to do it, the extensive FE analysis was peformed to identify the principal factor controlling welding distortion. Based on the results, the predictive equations of transverse shrinkage and angular distortion at the thick AA5083 alloy weldment were formulated as the function of heat intensity (Q), in-plane(Di) and bending(Db) rigidity.

  • PDF

Predictive Growth Models of Bacillus cereus on Dried Laver Pyropia pseudolinearis as Function of Storage Temperature (저장온도에 따른 마른김(Pyropia pseudolinearis)의 Bacillus cereus 성장예측모델 개발)

  • Choi, Man-Seok;Kim, Ji Yoon;Jeon, Eun Bi;Park, Shin Young
    • Korean Journal of Fisheries and Aquatic Sciences
    • /
    • v.53 no.5
    • /
    • pp.699-706
    • /
    • 2020
  • Predictive models in food microbiology are used for predicting microbial growth or death rates using mathematical and statistical tools considering the intrinsic and extrinsic factors of food. This study developed predictive growth models for Bacillus cereus on dried laver Pyropia pseudolinearis stored at different temperatures (5, 10, 15, 20, and 25℃). Primary models developed for specific growth rate (SGR), lag time (LT), and maximum population density (MPD) indicated a good fit (R2≥0.98) with the Gompertz equation. The SGR values were 0.03, 0.08, and 0.12, and the LT values were 12.64, 4.01, and 2.17 h, at the storage temperatures of 15, 20, and 25℃, respectively. Secondary models for the same parameters were determined via nonlinear regression as follows: SGR=0.0228-0.0069*T1+0.0005*T12; LT=113.0685-9.6256*T1+0.2079*T12; MPD=1.6630+0.4284*T1-0.0080*T12 (where T1 is the storage temperature). The appropriateness of the secondary models was validated using statistical indices, such as mean squared error (MSE<0.01), bias factor (0.99≤Bf≤1.07), and accuracy factor (1.01≤Af≤1.14). External validation was performed at three random temperatures, and the results were consistent with each other. Thus, these models may be useful for predicting the growth of B. cereus on dried laver.

The Measurement and Estimation of Lower Flash Points for n-Propanol+Acetic acid and n-Propanol+n-Propionic Systems (n-Propanol+acetic acid 및 n-propanol+n-propionic acid 계의 하부 인하점 측정 및 예측)

  • Ha, Dong-Myeong;Lee, Sung-Jin
    • Journal of the Korean Society of Safety
    • /
    • v.22 no.4
    • /
    • pp.37-42
    • /
    • 2007
  • Flash points for the flammable binary systems, n-propanol+acetic acid and n-propanol+n-propionic acid, were measured by Cleveland open cup tester. The Raoult's law, the van Laar equation and the UNIQUAC equation were used for predicting flash points and were compared with experimentally-derived data. The calculated values based on the van Laar and UNIQUAC equations were found to be better than those based on the Raoult's law. And the predictive curve of the flash point prediction model based on the UNIQUAC equation described the experimentally-derived data more effectively than was the case when the prediction model was based upon the the van Laar equation.

Predictive Analyses for Activities of the Upper Extremity and Daily Living based on Impairment of the Upper Extremity in People with Stroke - Preliminary Study using Clinical Scales - (뇌졸중 환자의 위팔 손상 수준에 따른 위팔 활동과 일상생활 활동의 예측도 분석 - 임상적 평가를 이용한 예비 연구 -)

  • Jung, Young-Il;Woo, Young-Keun
    • PNF and Movement
    • /
    • v.16 no.3
    • /
    • pp.495-503
    • /
    • 2018
  • Purpose: This study analyzes the predictive power of upper extremity activity and the activities of daily living in patients with stroke using an easy-to-use evaluation tool. Methods: The Fugl-Meyer assessment (FMA) of the upper extremity and action research arm test (ARAT) are performed, and the Korean modified Barthel index (K-MBI) is measured. The predictive power of the upper extremity activity level and the daily activity level are analyzed using regression analysis. The statistical significance level is 0.05. Results: The coefficient of determination, R2, for predicting the ARAT using FMA was high at 0.88, but the regression equation for predicting the K-MBI using the FMA and ARAT did not show a statistically significant difference. Conclusion: The assessment of the upper extremity should be performed at the activity level, as well as the impairment level. The assessment for predicting the activities of daily living should be carried out for each level of the international classification of functioning (ICF), disability, and health, which can be linked to daily life, in addition to the assessment of the upper arm. Future research should conduct more diverse analyses using the ICF assessment tools at various levels.

Development of a Predictive Model Describing the Growth of Staphylococcus aureus in Ready-to-Eat Sandwiches (즉석섭취 샌드위치에서의 Staphylococcus aureus 성장예측모델 개발)

  • Park, Hae-Jung;Bae, Hyun-Joo
    • Journal of the FoodService Safety
    • /
    • v.2 no.2
    • /
    • pp.91-96
    • /
    • 2021
  • This study was performed to provide fundamental data on hygiene and quality control of ready-to-eat sandwiches. Predictive models were developed to the kinetics of Staphylococcus aureus growth in these sandwiches as a function of temperature (10, 15, 25, and 35℃). The result of the primary model that used the Gompertz equation showed that the lag phase duration (LPD) and generation time (GT) decreased and the exponential growth rate (EGR) increased with increasing storage temperature. The secondary model showed an R2 for M and B of 0.9967 and 09916, respectively. A predictive growth model of the growth degree as a function of temperature was developed. L(t)=A+Cexp(-exp(-B(t-M))) (A=Initial contamination level, C=MPD-A, B=0.473166-0.045040*Temp-0.001718*Temp*Temp, M=19.924824-0.627442*Temp-0.004493*Temp*Temp, t=time, Temp=temperature). This model showed an R2 value of 0.9288. All the models developed in this study showed a good fit.

Development of Standardized Predictive Models for Traditional Korean Medical Diagnostic Pattern Identification in Stroke Subjects: A Hospital-based Multi-center Trial

  • Jung, Woo-Sang;Cho, Seung-Yeon;Park, Seong-Uk;Moon, Sang-Kwan;Park, Jung-Mi;Ko, Chang-Nam;Cho, Ki-Ho;Kwon, Seungwon
    • The Journal of Korean Medicine
    • /
    • v.40 no.4
    • /
    • pp.49-60
    • /
    • 2019
  • Objectives: To develop a standardized diagnostic pattern identification equation for stroke patients, our group conducted a study to derive the predictive logistic equations. However, the sample size was relatively small. In the current study, we aimed to derive new predictive logistic equations for each diagnostic pattern using an expanded number of subjects. Methods: This study was a hospital-based multi-center trial recruited stroke patients within 30 days of symptom onset. Patients' general information, and the variables related to diagnostic pattern identification were measured. The diagnostic pattern of each patient was identified independently by two Korean Medicine Doctors. To derive a predictive model for pattern identification, binary logistic regression analysis was applied. Results: Among the 1,251 patients, 385 patients (30.8%) had the Fire Heat Pattern, 460 patients (36.8%) the Phlegm Dampness Pattern, 212 patients (16.9%) the Qi Deficiency Pattern, and 194 patients (15.5%) the Yin Deficiency Pattern. After the regression analysis, the predictive logistic equations for each pattern were determined. Conclusion: The predictive equations for Fire Heat, Phlegm Dampness, Qi Deficiency, and Yin Deficiency would be useful to determine individual stroke patients' pattern identification in the clinical setting. However, further studies using objective measurements are necessary to validate these data.

Physical activity level, total daily energy expenditure, and estimated energy expenditure in normal weight and overweight or obese children and adolescents (소아청소년의 비만여부에 따른 신체활동수준, 1일 총에너지소비량 및 에너지필요추정량의 평가)

  • Kim, Myung Hee;Kim, Eun Kyung
    • Journal of Nutrition and Health
    • /
    • v.45 no.6
    • /
    • pp.511-521
    • /
    • 2012
  • The purposes of this study were to assess the physical activity level (PAL) and the total daily energy expenditure (TEE) as well as to evaluate the validity of prediction equation for the estimated energy requirement (EER) in normal weight and overweight or obese children and adolescents. The subjects comprised of 100 healthy Korean students aged between 7-18. The anthropometric data was collected. PAL was calculated from the physical activity diary by the 24-hour recall method, and the resting metabolic rate (RMR) was measured by an open-circuit indirect calorimetry using a ventilated hood system. Daily energy expenditure was PAL multiplied by RMR. EER was calculated by using the prediction equation published in KDRIs. There was no significant difference in the means of age and height between the 46 obese subjects and 54 nonobese subjects. The weight and BMI of the obese group (60.2 kg, $25.3kg/m^2$) were significantly higher than those of the nonobese group (42.4 kg, $18.4kg/m^2$). However, PAL was not significantly different between the two groups (nonobese 1.45, obese 1.46). TEE of the obese group (2,212 kcal/day) was significantly higher than that of the nonobese group (1,774 kcal/day). EER (individual PA) and EER (light PA) were significantly higher than TEE (p < 0,001); however, EER (sedentary PA) was not significantly different with TEE in the two groups. These results showed that the levels of physical activity were the same as the sedentary activity both in the nonobese and obese Korean students; moreover, the predictive equation for EER published in KDRI overestimated the TEE of Korean children and adolescents. Therefore, in further research, a new predictive equation for EER should be developed for Korean children and adolescents through the doubly labeled water method.

Development of a New Munk-type Breaker Height Formula Using Machine Learning (머신러닝을 이용한 새로운 Munk-type 쇄파파고 예측식의 제안)

  • Choi, Byung-Jong;Nam, Hyung-Sik;Lee, Kwang-Ho
    • Journal of Navigation and Port Research
    • /
    • v.45 no.3
    • /
    • pp.165-172
    • /
    • 2021
  • Breaking wave is one of the important design factors in the design of coastal and port structures as they are directly related to various physical phenomena occurring on the coast, such as onshore currents, sediment transport, shock wave pressure, and energy dissipation. Due to the inherent complexity of the breaking wave, many empirical formulas have been proposed to predict breaker indices such as wave breaking height and breaking depth using hydraulic models. However, the existing empirical equations for breaker indices mainly were proposed via statistical analysis of experimental data under the assumption of a specific equation. In this study, a new Munk-type empirical equation was proposed to predict the height of breaking waves based on a representative linear supervised machine learning technique with high predictive performance in various research fields related to regression or classification challenges. Although the newly proposed breaker height formula was a simple polynomial equation, its predictive performance was comparable to that of the currently available empirical formula.

A Study on the Prediction of Shrinkage and Residual Stress for the HY-100 Weldment Considering the Phase Transformation (상 변태를 고려한 HY-100강 용접부의 수축 및 잔류응력 예측에 관한 연구)

  • Lee, Hee-Tae;Shin, Sang-Beom
    • Journal of Welding and Joining
    • /
    • v.25 no.1
    • /
    • pp.42-48
    • /
    • 2007
  • For high performance and structural stability, application of high strength steel has continuously increased. However, the change of the base metal gives rise to problems with the accuracy management of the welded structure. It is attributed to the martensite phase transformation of the high strength low alloy steel weldment. The purpose of this study is to establish the predictive equation of transverse shrinkage and residual stress for the HY-100 weldment. In order to do it, high speed quenching dilatometer tests were performed to define a coefficient of thermal expansion(CTE) at the heating and cooling stage of HY-100 with various cooling rates. Uncoupled thermal-mechanical finite element(FE) models with CTE were proposed to evaluate the effect of the martensite phase transformation on transverse shrinkage and residual stresses at the weldment. FEA results were verified by comparing with experimental results. Based on the results of extensive FEA and experiments, the predictive equation of transverse shrinkage and longitudinal shrinkage force at the HY-100 weldment were formulated as the function of welding heat input/in-plane rigidity and welding heat input respectively.

Study on Analysis Process for Slip Torque Design Control of Impact Hammer Drills (임팩트햄머 드릴의 슬립토크 설계 제어를 위한 분석 프로세스 고찰)

  • Kim, Seung Hyeon;Kwon, Sang Youp;Ko, Dong Shin;Hur, Deog Jae;Dong, Kwang Ho
    • Journal of the Korean Society for Precision Engineering
    • /
    • v.33 no.5
    • /
    • pp.401-407
    • /
    • 2016
  • This paper describes the derivation methodology of the working torque predictive model that can be used in the initial design stages of the impact hammer tool. The working torque control mechanism is designed, taking into account various factors, such as the force of the spring and friction. Firstly, the analysis dynamic model for working environments was modeled as an additional bush and spring, and verified by comparing the test results of the working torque. Secondly, the main performance parameters of the working torque were theoretically defined by analyzing the operating mechanism. The equation to predict the working torque was derived using the dynamic analysis results according to the value changes of the parameters. The prediction equation of the working torque was validated by comparing the predicted results with the experimental data. The error difference between the experimental data and the predictive model results was found to be 8.62%.