Optimisation of data analysis method for a fluidized bed combustion test rig

Nowadays the used fuel variety in power boilers is widening and new boiler constructions and running models have to be developed. This research and development is done in small pilot plants where more faster analyse about the boiler mass and heat balance is needed to be able to find and do the right decisions already during the test run. The barrier on determining boiler balance during test runs is the long process of chemical analyses of collected input and outputmatter samples. The present work is concentrating on finding a way to determinethe boiler balance without chemical analyses and optimise the test rig to get the best possible accuracy for heat and mass balance of the boiler. The purpose of this work was to create an automatic boiler balance calculation method for 4 MW CFB/BFB pilot boiler of Kvaerner Pulping Oy located in Messukylä in Tampere. The calculation was created in the data management computer of pilot plants automation system. The calculation is made in Microsoft Excel environment, which gives a good base and functions for handling large databases and calculations without any delicate programming. The automation system in pilot plant was reconstructed und updated by Metso Automation Oy during year 2001 and the new system MetsoDNA has good data management properties, which is necessary for big calculations as boiler balance calculation. Two possible methods for calculating boiler balance during test run were found. Either the fuel flow is determined, which is usedto calculate the boiler's mass balance, or the unburned carbon loss is estimated and the mass balance of the boiler is calculated on the basis of boiler's heat balance. Both of the methods have their own weaknesses, so they were constructed parallel in the calculation and the decision of the used method was left to user. User also needs to define the used fuels and some solid mass flowsthat aren't measured automatically by the automation system. With sensitivity analysis was found that the most essential values for accurate boiler balance determination are flue gas oxygen content, the boiler's measured heat output and lower heating value of the fuel. The theoretical part of this work concentrates in the error management of these measurements and analyses and on measurement accuracy and boiler balance calculation in theory. The empirical part of this work concentrates on the creation of the balance calculation for the boiler in issue and on describing the work environment.

Optimisation of energy provision with supplemental parenteral nutrition in critically ill patients: a randomised controlled clinical trial.

BACKGROUND: Enteral nutrition (EN) is recommended for patients in the intensive-care unit (ICU), but it does not consistently achieve nutritional goals. We assessed whether delivery of 100% of the energy target from days 4 to 8 in the ICU with EN plus supplemental parenteral nutrition (SPN) could optimise clinical outcome. METHODS: This randomised controlled trial was undertaken in two centres in Switzerland. We enrolled patients on day 3 of admission to the ICU who had received less than 60% of their energy target from EN, were expected to stay for longer than 5 days, and to survive for longer than 7 days. We calculated energy targets with indirect calorimetry on day 3, or if not possible, set targets as 25 and 30 kcal per kg of ideal bodyweight a day for women and men, respectively. Patients were randomly assigned (1:1) by a computer-generated randomisation sequence to receive EN or SPN. The primary outcome was occurrence of nosocomial infection after cessation of intervention (day 8), measured until end of follow-up (day 28), analysed by intention to treat. This trial is registered with ClinicalTrials.gov, number NCT00802503. FINDINGS: We randomly assigned 153 patients to SPN and 152 to EN. 30 patients discontinued before the study end. Mean energy delivery between day 4 and 8 was 28 kcal/kg per day (SD 5) for the SPN group (103% [SD 18%] of energy target), compared with 20 kcal/kg per day (7) for the EN group (77% [27%]). Between days 9 and 28, 41 (27%) of 153 patients in the SPN group had a nosocomial infection compared with 58 (38%) of 152 patients in the EN group (hazard ratio 0·65, 95% CI 0·43-0·97; p=0·0338), and the SPN group had a lower mean number of nosocomial infections per patient (-0·42 [-0·79 to -0·05]; p=0·0248). INTERPRETATION: Individually optimised energy supplementation with SPN starting 4 days after ICU admission could reduce nosocomial infections and should be considered as a strategy to improve clinical outcome in patients in the ICU for whom EN is insufficient. FUNDING: Foundation Nutrition 2000Plus, ICU Quality Funds, Baxter, and Fresenius Kabi.

Automated formulation of optimisation models for steel beam structures

Over 70% of the total costs of an end product are consequences of decisions that are made during the design process. A search for optimal cross-sections will often have only a marginal effect on the amount of material used if the geometry of a structure is fixed and if the cross-sectional characteristics of its elements are property designed by conventional methods. In recent years, optimalgeometry has become a central area of research in the automated design of structures. It is generally accepted that no single optimisation algorithm is suitable for all engineering design problems. An appropriate algorithm, therefore, mustbe selected individually for each optimisation situation. Modelling is the mosttime consuming phase in the optimisation of steel and metal structures. In thisresearch, the goal was to develop a method and computer program, which reduces the modelling and optimisation time for structural design. The program needed anoptimisation algorithm that is suitable for various engineering design problems. Because Finite Element modelling is commonly used in the design of steel and metal structures, the interaction between a finite element tool and optimisation tool needed a practical solution. The developed method and computer programs were tested with standard optimisation tests and practical design optimisation cases. Three generations of computer programs are developed. The programs combine anoptimisation problem modelling tool and FE-modelling program using three alternate methdos. The modelling and optimisation was demonstrated in the design of a new boom construction and steel structures of flat and ridge roofs. This thesis demonstrates that the most time consuming modelling time is significantly reduced. Modelling errors are reduced and the results are more reliable. A new selection rule for the evolution algorithm, which eliminates the need for constraint weight factors is tested with optimisation cases of the steel structures that include hundreds of constraints. It is seen that the tested algorithm can be used nearly as a black box without parameter settings and penalty factors of the constraints.