Prediction of the annual performance of marine organic Rankine cycle power systems

The increasing awareness about the environmental impact of shipping and the increasingly stricter regulations introduced by the International Maritime Organization are driving the development of solutions to reduce the pollutant emissions from ships. While some previous studies focused on the implementation of a specific technology, others considered a wider perspective and investigated the feasibility of the integration of various technologies on board vessels. Among the screened technologies, organic Rankine cycle (ORC) power systems represent a viable solution to utilize the waste heat contained in the main engine exhaust gases to produce additional power for on board use. The installation of ORC power systems on board ships could result in a reduction of the CO2 emissions by 5 – 10 %. Although a number of methods to derive the optimal design of ORC units in marine applications have been proposed, these methods are complex, computationally expensive and require specialist knowledge to be included as part of a general optimization procedure to define the optimal set of technologies to be implemented on board a vessel. This study presents a novel method to predict the performance of ORC units installed on board vessels, based upon the characteristics of the main engine exhaust gases and the ship sailing profile. The method is not computationally intensive, and is therefore suitable to be used in the context of large optimization problems, such as holistic optimization and evaluation of a ship performance given the operational profile, weather and route. The model predicted the annual energy production of two case studies with an accuracy within 4

Health economic analysis of laparoscopic lavage versus Hartmann's procedure for diverticulitis in the randomized DILALA trial

BACKGROUND: Open surgery with resection and colostomy (Hartmann's procedure) has been the standard treatment for perforated diverticulitis with purulent peritonitis. In recent years laparoscopic lavage has emerged as an alternative, with potential benefits for patients with purulent peritonitis, Hinchey grade III. The aim of this study was to compare laparoscopic lavage and Hartmann's procedure with health economic evaluation within the framework of the DILALA (DIverticulitis – LAparoscopic LAvage versus resection (Hartmann's procedure) for acute diverticulitis with peritonitis) trial. METHODS: Clinical effectiveness and resource use were derived from the DILALA trial and unit costs from Swedish sources. Costs were analysed from the perspective of the healthcare sector. The study period was divided into short‐term analysis (base‐case A), within 12 months, and long‐term analysis (base‐case B), from inclusion in the trial throughout the patient's expected life. RESULTS: The study included 43 patients who underwent laparoscopic lavage and 40 who had Hartmann's procedure in Denmark and Sweden during 2010–2014. In base‐case A, the difference in mean cost per patient between laparoscopic lavage and Hartmann's procedure was €–8983 (95 per cent c.i. –16 232 to –1735). The mean(s.d.) costs per patient in base‐case B were €25 703(27 544) and €45 498(38 928) for laparoscopic lavage and Hartmann's procedure respectively, resulting in a difference of €–19 794 (95 per cent c.i. –34 657 to –4931). The results were robust as demonstrated in sensitivity analyses. CONCLUSION: The significant cost reduction in this study, together with results of safety and efficacy from RCTs, support the routine use of laparoscopic lavage as treatment for complicated diverticulitis with purulent peritonitis

Waste heat recovery technologies for offshore platforms

none5siThis article aims at finding the most suitable waste heat recovery technology for existing and future offshore facilities. The technologies considered in this work are the steam Rankine cycle, the air bottoming cycle and the organic Rankine cycle. A multi-objective optimization approach is employed to attain optimal designs for each bottoming unit by selecting specific functions tailored to the oil and gas sector, i.e. yearly CO2 emissions, weight and economic revenue. The test case is the gas turbine-based power system serving an offshore platform in the North Sea. Results indicate that the organic Rankine cycle technology presents larger performances compared to steam Rankine cycle units, whereas the implementation of air bottoming cycle modules is not attractive from an economic and environmental perspective compared to the other two technologies. Despite the relatively high cost of the expander and of the primary heat exchanger, organic Rankine cycle turbogenerators appear thus to be the preferred solution to abate CO2 emissions and pollutants on oil and gas facilities. As a practical consequence, this paper provides guidelines for the design of high-efficiency, cost-competitive and low-weight power systems for offshore installationsrestrictedL. Pierobon;A. Benato;E. Scolari;F. Haglind;A. StoppatoL., Pierobon; Benato, Alberto; E., Scolari; F., Haglind; Stoppato, Ann

Prediction of properties of new halogenated olefins using two group contribution approaches

AbstractThe increasingly restrictive regulations for substances with high ozone depletion and global warming potentials are driving the search for new sustainable fluids with low environmental impact. Recent research works have pointed out the great potential of fluorine- and chlorine-based olefins as refrigerants and solvents, due to their environmentally-friendly features. However there is a lack of experimental data of their thermophysical properties. In this work we present two models based on a group contribution method, using a classical approach and neural networks, to predict the critical temperature, critical pressure, normal boiling temperature, acentric factor, and ideal gas heat capacity of organic fluids containing chlorine and/or fluorine. The accuracy of the prediction capacity of the two models is analyzed, and compared with equivalent methods in the literature. The models showed an average reduction of the absolute relative deviation for all the studied properties of more than 50%, compared to other methods. In addition, it was observed that the neural-network-based model yielded a better accuracy than the classical approach in the prediction of all the properties, except for the acentric factor, due to the lack of experimental data for this property