Can the Four-Hour Installation Dwell Time Be Reduced?

2021 ◽  
Author(s):  
Carlos D. Girão ◽  
Igor Meira ◽  
José Carlos Veiga

Abstract A correct bolted flanged joint tightening procedure includes retorquing to restore short-term creep relaxation and embedment losses; the ASME PCC-1-2019 Tightening Method recommends a minimum of 4 hours of dwell time before retightening the bolts. It is known that in an industrial plant, maintenance costs come mostly from process downtime in addition to the labor and the tools necessary to perform the operation. Reducing the retorque waiting time would make installation quicker and avoid additional — and unnecessary — costs, returning the plant to revenue operation sooner. This paper explores whether different gasket styles should have the same dwell time between the installation and retorque, and what would be the dwell time to minimize plant downtime without compromising the gasket performance. The study was performed using a test rig based on a 4” class 300 ASME B16.5 flange equipped with eight strain-gauged bolts that correlates bolt elongation with applied stress. Four dwell times (15min, 1h, 4h and 24h) and different gasket styles and materials such as PTFE, CFG and metallic gaskets were tested. Additionally, two ASME PCC – 1 installation methods were compared and reported: Legacy Cross-Pattern Numbering System and Alternative Assembly Pattern #3. The former is the typical method for flanged joint tightening operations, while the latter offers a simpler, faster execution.

2020 ◽  
Vol 98 (Supplement_3) ◽  
pp. 39-40
Author(s):  
Kendi Tjardes ◽  
Katy Lippolis

Abstract One hundred four Angus calves were ranked by gender, BW, age, and dam parity, and assigned to 1 of 4 pre-weaning treatments: 1) nose flaps for 7-d prior to weaning (NF), 2) traditional weaning (TRAD), 3) traditional weaning and creep feed for 3-wk prior to weaning (TRADC), or 4) nose flaps for 7-d prior to weaning and creep feed for 3-wk prior to weaning (NFC). Cow-calf pairs were housed in dry lot pens on d -28. From d -21 to 0, calves in creep treatments were provided free choice access to creep feed. Nose flaps were placed on d -7, and calves were weaned on d 0. Calves were vaccinated and dewormed on d -21 and 0. There was no difference (P ≥ 0.97) in calf BW on d -28 or -21. During the 7-d period that nose flaps were placed, NFC calves had greater (P ≤ 0.0001) ADG than NF and TRAD calves, and tended to have greater (P ≤ 0.10) ADG than TRADC calves. At weaning on d 0, TRADC and NFC calves tended to have greater BW (P = 0.07) and had greater overall change in BW (P < 0.0001) during the pre-weaning period than TRAD and NF calves. Additionally, there was a greater (P ≤ 0.001) increase in BW of NFC and TRADC cows during the pre-weaning period compared to NF and TRAD cows. From d -21 to 0 there was no differences (P > 0.41) in plasma concentrations for Bovine Viral Diarrhea Virus (BVD). By d 14, the TRADC calves had the greatest plasma concentrations for BVD (P < 0.04). Therefore, providing short-term creep feed prior to placing nose flaps can improve pre-weaning calf and cow performance compared to traditional and nose flap weaning without creep feed supplementation, however, did not improve response to vaccination.


2021 ◽  
Vol 149 ◽  
pp. 106562
Author(s):  
Yidong Gan ◽  
Matthieu Vandamme ◽  
Yu Chen ◽  
Erik Schlangen ◽  
Klaas van Breugel ◽  
...  

2006 ◽  
Vol 519-521 ◽  
pp. 1041-1046 ◽  
Author(s):  
Brian Wilshire ◽  
H. Burt ◽  
N.P. Lavery

The standard power law approaches widely used to describe creep and creep fracture behavior have not led to theories capable of predicting long-term data. Similarly, traditional parametric methods for property rationalization also have limited predictive capabilities. In contrast, quantifying the shapes of short-term creep curves using the q methodology introduces several physically-meaningful procedures for creep data rationalization and prediction, which allow straightforward estimation of the 100,000 hour stress rupture values for the aluminum alloy, 2124.


2012 ◽  
Vol 73 ◽  
pp. 144-152 ◽  
Author(s):  
Shengzhi Li ◽  
Zumrat Eliniyaz ◽  
Lanting Zhang ◽  
Feng Sun ◽  
Yinzhong Shen ◽  
...  

2018 ◽  
Vol 25 (3) ◽  
pp. 713-722 ◽  
Author(s):  
Seen Chan Kim ◽  
Jae-Hyeok Shim ◽  
Woo-Sang Jung ◽  
Yoon Suk Choi

2010 ◽  
Vol 527 (29-30) ◽  
pp. 7505-7509 ◽  
Author(s):  
Huiran Cui ◽  
Feng Sun ◽  
Ke Chen ◽  
Lanting Zhang ◽  
Rongchun Wan ◽  
...  

Author(s):  
Hideo Hiraguchi

Abstract Recently the Discrete Cosine Transform[1], [2], [3] which is a modified Fourier Transform has begun to be used to express coefficients of creep equations using the power law or the exponential law such as Bailey-Norton law[4], [5] and θ Projection[6], [7], [8], [9], [10]. In addition, the Discrete Cosine Transform has begun to be used to express a creep equation itself. We have already found that the Discrete Cosine Transform can express the temperature and stress dependence property of the coefficients of the creep equations at the same time by the two-dimensional Discrete Cosine Transform using 8 × 8 discrete signals[11]. Furthermore, we have already found that the Discrete Cosine Transform can fit measured creep strain values very well from the primary creep region to the tertiary creep region using 8 discrete signals and it can estimate creep strain values between the measured points by interpolation very well[12]. However it has not been known if the Discrete Cosine Transform can predict the long term creep curve by using the short term creep data yet. Therefore, as a next stage, we tried to estimate the long term creep curve from the short term creep data of gas turbine materials by extrapolation using the Discrete Cosine Transform. As a result, we were able to obtain a useful numerical analysis method by utilizing the Discrete Cosine Transform Coefficients and others as a new extrapolation method. It is found that this new numerical method would be able to predict the configuration of 150,000-hour creep curve by using 500-hour to 13,000-hour short term creep data.


2020 ◽  
Vol 134 ◽  
pp. 106105 ◽  
Author(s):  
Yidong Gan ◽  
Matthieu Vandamme ◽  
Hongzhi Zhang ◽  
Yu Chen ◽  
Erik Schlangen ◽  
...  

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