Deeppipe: Theory-guided LSTM method for monitoring pressure after multi-product pipeline shutdown

2021 ◽  
Vol 155 ◽  
pp. 518-531
Author(s):  
Jianqin Zheng ◽  
Jian Du ◽  
Yongtu Liang ◽  
Chang Wang ◽  
Qi Liao ◽  
...  
Keyword(s):  
Product Pipeline

Management of the sulfur content in the gasoline transport logistics chain in a multi-product pipeline

2018 ◽  
Vol 36 (23) ◽  
pp. 2024-2028
Author(s):  
Elcio Cruz de Oliveira ◽  
Livio Garcia da Costa ◽  
Viviane de Jesus Leite ◽  
Leticia Correa Capistrano
Keyword(s):  
Sulfur Content ◽  
Product Pipeline ◽  
Transport Logistics

Detailed scheduling distribution of real multi-product pipeline

2021 ◽  
Vol 42 (4) ◽  
pp. 505
Author(s):  
Asma Berrichi ◽  
Wassila Abdellaoui ◽  
Djamel Bennacer ◽  
Fouad Maliki ◽  
Latefa Ghomri
Keyword(s):  
Product Pipeline

Direct filling—the technology of viscous product batching from the pressure product pipeline

2013 ◽  
Vol 42 (6) ◽  
pp. 500-505 ◽  
Author(s):  
B. L. Salamandra ◽  
L. I. Tyves ◽  
K. B. Salamandra ◽  
G. K. Korendyasev
Keyword(s):  
Product Pipeline

Effects of Density and Viscosity Measurements Errors at the Pipeline Batch Tracking System

2008 ◽  
Author(s):  
Marais Liebenberg ◽  
David Eduardo G. P. Bueno ◽  
Claudia C. Magalha˜es
Keyword(s):  
South African ◽  
Tracking System ◽  
Time Of Arrival ◽  
Other Information ◽  
Operational Information ◽  
Relevant Role ◽  
Pipeline Segment ◽  
Measurements Errors ◽  
Flow Simulator ◽  
Product Pipeline

Batch Tracking System (BTS) is commonly found as pipeline operational real time functionality within operator companies’ control room. It tracks batches, offering amongst other information their volumes, positions and Estimated Time of Arrival (ETA). In order to reliably calculate those system outputs, BTS requires operational information like pressures, temperatures and flow rates, elevation profile, as well as some fluid physical properties, being the most important ones density and viscosity. This work aims to track the actual necessity of measuring those variables and to establish their impact on ETA in a 700km long South African multi-product pipeline network. Thus, the flow dynamic was analysed using a commercial pipeline flow simulator, where the network operational scenario was entirely reproduced and then variations of density and viscosity were introduced to track the effects on batches’ ETA, per pipeline segment. As a result of the study, which employed usual refined products such as petrol and Diesel, it was identified: (i) both variables played a relevant role on the ETA estimation requiring to be accurately determined, even though viscosity is the most relevant; (ii) viscosity showed a more predictable behaviour as flow resistance shall take place independently of the elevation profile; (iii) density was highly dependent of the elevation profile; and (iv) the biggest ETA accumulated variation verified was around 128 minutes (due to a variation of –20% in the viscosity value) and the lowest one around 4 minutes (due to a variation of –2% in the density value).

DNA product pipeline

Nature ◽  
1992 ◽  
Vol 357 (6378) ◽  
pp. 520-522
Keyword(s):  
Product Pipeline

Spin-In or Spin-Out?

2000 ◽  
Vol 1 (2) ◽  
pp. 109-116 ◽  
Author(s):  
Joe Tidd ◽  
Simon Barnes
Keyword(s):  
Venture Capital ◽  
Life Science ◽  
Corporate Venturing ◽  
Technology Acquisition ◽  
Pharmaceutical Firms ◽  
Wide Range ◽  
Corporate Venture ◽  
Venture Capital Firms ◽  
The One ◽  
Product Pipeline

This paper examines the variety of corporate venturing activities in the pharmaceutical and life science sectors, identifies the range of initiators, motives and structures, and evaluates the potential opportunities for professional venture capital firms. On the one hand, pharmaceutical companies need to maintain the new product pipeline that has increased the demand for technology acquisition, and on the other, mergers and rationalization within the sector have resulted in a significant growth in technology divestment. Both trends have boosted corporate venturing activity. The study examines the venture activities of nine pharmaceutical firms, fourteen life science companies and seven corporate venture capital funds. The authors conclude that, while there is a wide range of venturing options, there is considerable confusion in the industry over ends and means. Specifically, many firms have failed to differentiate sufficiently between strategic, financial and operational goals, and have therefore created inappropriate forms of corporate venture.

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