Fraunhofer Chalmers Research Centre for Industrial Mathematics
Chalmers Publication LibraryNot a member yet
70439 research outputs found
Sort by
Opportunities for Flexible Operation of a Combined Heat and Power Plant in Power Systems with Volatile Electricity Prices
No full textTo combat climate change,renewable energysources are preferred in energy systems. Among these are wind and solar, which are characterised by low operational costs and that their energy output depends on weather conditions. The implementation of large amounts of non-dispatchable power generation, that are placed early in the meritorder,results in larger and more frequent variations in netpower supply in the energy system. This, consequently, leads to volatile electricity prices. For existing power plants to operate profitably in such systems, they need to have flexible operating strategies to profit from high electricity prices. Furthermore, it is preferable to avoid power production during hours with low electricity prices without having to shut down the plant. In this study, a combined cycle gas turbine combined heat and power(CCGT-CHP) plant located in Gothenburg, Sweden has been analysed in order to find profitable operational strategies for scenarios of possible future energy markets.
This study is performed in two steps. In the first, a detailed steady-state process model is derived based on an analysis of historical process data and operating patterns at the reference plant. In the second step, the process model was linearised and implemented into an optimisation model to analyse the CCGT-CHP plant’s profitability and operational strat egies in possible future energy systems. Linear equations were derived for power and heat output, as well as fuel consumption, using factorial design and linear regression methods. The equations were validated against process model outputs.
The study concludes that the profitability of flexibilisation measures is highly dependent on the energy system in place. In general, an increased share of non dispatchable power sources increases the profitability of operating the plant with full steam turbine bypass. This strategy further implies alternative strategies for both gas turbine and supplementary firing operations. However, the optimisation model without the possibility of steam turbine bypass, given historical power market data, proposed a similar operation as the one used at the reference CCGT-CHP plant during the reference year. Nonetheless, fuel taxation and future energy systems could give rise to the need for new operating strategies. If the fuel price is increased, full steam turbine bypass is vital to operate in a profitable manner. That is, operate the plant for heat production. However, for a changed electricity mix in the system, the CCGT-CHP plant could have an important part in the electricity system as well
Design of a generic subsystem fixture for physical squeak and rattle prediction
No full textToday Volvo Car Corporation uses parts of the body-in-white to build a fixture for
the instrument panels. However, there is a need for a generic subsystem fixture that
can be used instead of the cut-out parts of the body-in-white. The use of a fixture
will lower the cost for future testing and decrease the manual work, since the generic
fixture will replace a number of cut-out parts from the models. The structure of the
generic fixture should thus have some flexibility in geometry, so that it fits a wide
range of instrument panel models.
This thesis focus on two vehicle models which will be called model A and B. A
benchmark study is performed to get a better understanding of the body-in-whites
an particularly in the region where the instrument panels are mounted in the cars.
In that, a modal analysis is performed as well as stiffness analysis with the solver
Nastran. A meshed solid block is used to allocate the design space of the fixture.
The block with the connection parts placed inside are used to perform topology optimisation,
where the solid block is the design space and the connection parts is the
non-design space. Results from the topology optimisation give guidance on where
to place beams and other material when designing the fixture. Using Catia V5 and
having the platform drawing of the shaker rig, the design of the fixture was created.
The main structural components of the fixture are plates, beams and AluflexTM
components. In Ansa, the model of the fixture is meshed and a modal analysis is
performed. Static and dynamic stiffness analysis are also performed, locally and
globally, to investigate the stiffness with respect to the body-in-whites.
The main structure of the proposed fixture was shown to have higher global stiffness
compared to the body-in-whites. This gives a good foundation for future work.
However, local stiffnesses in the connection points are much lower compared to the
body-in-whites. This is based on the results from Aluflex, which gives the fixture
its generic features. A conclusion from this is that other materials than aluminium
profiles needs to be used for parts of the design. Future work could reveal the success
of such design strategy. Although steel has a higher density, it can be used in
a sophisticated way with other materials to create high rigidity and low weight.
Keywords: generic, fixture, topology optimisation, static and dynamic stiffness,
AluflexTM
Järnvägsbro över länsväg 216 Detaljutformning och preliminär dimensionering av en förspänd trågbalkbro
No full textPedestrian delays at Artillerigatan - A multi-method analysis of a select crosswalk in Gothenburg
No full text
Maskininlärning för diagnosticering av perifer neuropati
No full textThis report investigates the possibility of diagnosing peripheral neuropathy with the help of
non-parametic classification methods. Peripheral neuropathy is a disease state characterized
by damage on the nerves furthest out in the nervous system, with symptoms first occuring in
the feet. The data used in this project comes from Dr. William Kennedys research group at
University of Minnesota. The data contains 401 observations of 120 healthy controls and 65
individuals with presumed peripheral neuropathy due to chemotherapy, (where 18 individuals
have been confirmed having peripheral neuropathy through other examination procedures).
The data is collected with a dynamic sweat test, a new diagnostic method to discover unusual
sweating patterns and therefore also peripheral neuropathy. In this project we compare three
different machine learning methods to classify subjects as sick (peripheral neuropathy) and
healthy (no peripheral neuropathy): k-NN, random forest and neural networks. These methods
differ in their complexity, all with their disadvantages and advantages. To evauluate which
classification method that works the best a cross-validation was performed, with a modified
version of Cohen’s kappa. How good these classification methods perform depends on which
measuring area the data comes from, either foot, calf or foot and calf combined. The best
classification method was shown to be random forest, this for the calf-measurements where
the covarariates are chosen by backward stepwise selection. This method correctly classifies
67% of the sick individuals and 96% of the healthy controls. With the best model trained on
foot-measurements most undetermined sick individuals are being classified as sick, while for
the best model trained on calf-measurement most of the undetermined sick individuals are
classified as healthy. This could hint towards that the symptoms of peripheral neuropathy
first appears in the feet, something that is in line with the clinical reality