Stinger Structural Analysis Using Fully Coupled Model for Pipelay Operations

2021 ◽  
Author(s):  
Anupam Gupta ◽  
Sudhakar Tallavajhula ◽  
Sachin Mathakari
Author(s):  
Anupam Gupta ◽  
Sudhakar Tallavajhula ◽  
Sachin Mathakari

Abstract With the growing demands and increasing challenges in deep-water pipeline installation, it is increasingly important to optimize stinger capacity assessment procedure for higher level of accuracy and cost-efficiency as compared to the traditional approach which is highly conservative. The traditional approach combines maximum stresses from three different analyses for environmental loads, vessel motions and pipeline forces to calculate the dynamic performance of a stinger. This approach ignores the coupled behavior between stinger, vessel and pipeline leading to conservative results and over-design which significantly underestimates the operational limits of the stinger structure. The main objective of this study is to develop a simple yet optimized and accurate stinger design and analysis procedure by considering the combined effect of vessel motion, pipeline forces and environmental loading on stinger structure. This is achieved by performing a Fully Coupled Analysis (FCA) in time domain, with capability to capture the impact of stiffness and hydro-elastic properties of stinger and pipeline. The fully coupled model also allows inclusion of hydrodynamic loads on installation vessel as compared to use of vessel motion RAOs in the traditional approach. Forces from this time-history analysis are extracted and mapped onto the structural model to check for structural strength using API and AISC codes. This paper presents a comparison between structural analysis results obtained from Fully Coupled Analysis (FCA) and traditional approach. Results from the FCA procedure have shown significant improvement in the operational limits of stinger.


2020 ◽  
Vol 579 ◽  
pp. 411894
Author(s):  
Valerio Apicella ◽  
Carmine Stefano Clemente ◽  
Daniele Davino ◽  
Damiano Leone ◽  
Ciro Visone

Water ◽  
2020 ◽  
Vol 12 (3) ◽  
pp. 808 ◽  
Author(s):  
Fernando De Sales ◽  
David E. Rother

The study introduces a new atmosphere-land-aquifer coupled model and evaluates terrestrial water storage (TWS) simulations for Southern California between 2007 and 2016. It also examines the relationship between precipitation, groundwater, and soil moisture anomalies for the two primary aquifer systems in the study area, namely the Coastal Basin and the Basin and Range aquifers. Two model designs are introduced, a partially-coupled model forced by reanalysis atmospheric data, and a fully-coupled model, in which the atmospheric conditions were simulated. Both models simulate the temporal variability of TWS anomaly in the study area well (R2 ≥ 0.87, P < 0.01). In general, the partially-coupled model outperformed the fully-coupled model as the latter overestimated precipitation, which compromised soil and aquifer recharge and discharge. Simulations also showed that the drought experienced in the area between 2012 and 2016 caused a decline in TWS, evapotranspiration, and runoff of approximately 24%, 65%, and 11%, and 20%, 72% and 8% over the two aquifer systems, respectively. Results indicate that the models first introduced in this study can be a useful tool to further our understanding of terrestrial water storage variability at regional scales.


2020 ◽  
Author(s):  
Baijun Tian

&lt;p&gt;The double-Intertropical Convergence Zone (ITCZ) bias is one of the most outstanding problems in climate models. This study seeks to examine the double-ITCZ bias in the latest state-of-the-art fully coupled global climate models that participated in Coupled Model Intercomparison Project (CMIP) Phase 6 (CMIP6) in comparison to their previous generations (CMIP3 and CMIP5 models). To that end, we have analyzed the long-term annual mean tropical precipitation distributions and several precipitation bias indices that quantify the double-ITCZ biases in 75 climate models including 24 CMIP3 models, 25 CMIP3 models, and 26 CMIP6 models. We find that the double-ITCZ bias and its big inter-model spread persist in CMIP6 models but the double-ITCZ bias is slightly reduced from CMIP3 or CMIP5 models to CMIP6 models.&lt;/p&gt;


Sign in / Sign up

Export Citation Format

Share Document