An enhanced software operational profile model

2007 ◽  
Author(s):  
Zhen Wu ◽  
Luo-Ming Meng
Keyword(s):  
Profile Model ◽  
Operational Profile

Adaptive flow assignment for CO2 transcritical power cycle (CTPC): An engine operational profile-based off-design study

Energy ◽  
2021 ◽  
Vol 225 ◽  
pp. 120262
Author(s):  
Ligeng Li ◽  
Hua Tian ◽  
Lingfeng Shi ◽  
Jingyu Wang ◽  
Min Li ◽  
...  
Keyword(s):  
Design Study ◽  
Power Cycle ◽  
Operational Profile ◽  
Flow Assignment

scholarly journals Improving the composition and marketing of commercial baby foods: a Nutrient Profile Model

2021 ◽  
Vol 80 (OCE1) ◽  
Author(s):  
J.E. Cade ◽  
J. Hutchinson ◽  
H. Rippin ◽  
D. Threapleton ◽  
A. Morpeth ◽  
...  
Keyword(s):  
Nutrient Profile ◽  
Baby Foods ◽  
Profile Model

scholarly journals An empirical analysis on the operational profile of liquefied natural gas carriers with steam propulsion plants

2020 ◽  
pp. 1-20
Author(s):  
Carlos González Gutiérrez ◽  
Santiago Suárez de la Fuente ◽  
Jean-Marc Bonello ◽  
Richard Bucknall
Keyword(s):  
Natural Gas ◽  
Greenhouse Gases ◽  
Empirical Analysis ◽  
Continuous Monitoring ◽  
Simulation Models ◽  
Energy Performance ◽  
Liquefied Natural Gas ◽  
Liquid Hydrocarbons ◽  
Operational Profile ◽  
Emission Studies

Abstract Liquefied natural gas (LNG) offers negligible NOx and SOx emissions as well as reductions in CO2 compared with other liquid hydrocarbons. LNG is a significant player in the global energy mix, with a projection of 40% increase in demand for the next two decades. It is anticipated that the expected rise in demand will cause the fleet of LNG carriers (LNGC) to expand. This work concentrates on steam-powered LNGC, which accounted for 47% of the LNGC fleet in 2018. It performs an empirical analysis of continuous monitoring data that provide high levels of accuracy and transparency. The analysis is done on data collected from 40 LNGCs for over a year to estimate the fleet's operational profile, fuel mix and energy performance. The findings of this work are relevant for bottom-up analysis and simulation models that depend on technical assumptions, but also for emission studies such as the upcoming Fourth International Maritime Organization Greenhouse Gases study.

scholarly journals Coupled Engine-Propeller Selection Procedure to Minimize Fuel Consumption at a Specified Speed

2021 ◽  
Vol 9 (1) ◽  
pp. 59
Author(s):  
Mina Tadros ◽  
Roberto Vettor ◽  
Manuel Ventura ◽  
Carlos Guedes Soares
Keyword(s):  
Fuel Consumption ◽  
Selection Procedure ◽  
Optimization Procedure ◽  
Operating Point ◽  
Power Prediction ◽  
Ship Routing ◽  
Marine Propellers ◽  
Operational Profile ◽  
Calm Water ◽  
Engine Operating Point

This study presents a practical optimization procedure that couples the NavCad power prediction tool and a nonlinear optimizer integrated into the Matlab environment. This developed model aims at selecting a propeller at the engine operating point with minimum fuel consumption for different ship speeds in calm water condition. The procedure takes into account both the efficiency of the propeller and the specific fuel consumption of the engine. It is focused on reducing fuel consumption for the expected operational profile of the ship, contributing to energy efficiency in a complementary way as ship routing does. This model assists the ship and propeller designers in selecting the main parameters of the geometry, the operating point of a fixed-pitch propeller from Wageningen B-series and to define the gearbox ratio by minimizing the fuel consumption of a container ship, rather than only maximizing the propeller efficiency. Optimized results of the performance of several marine propellers with different number of blades working at different cruising speeds are also presented for comparison, while verifying the strength, cavitation and noise issues for each simulated case.

scholarly journals MotifPrototyper: A Bayesian profile model for motif families

2004 ◽  
Vol 101 (29) ◽  
pp. 10523-10528 ◽  
Author(s):  
E. P. Xing ◽  
R. M. Karp
Keyword(s):  
Profile Model
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