A Review and Characterization of Progressive Visual Analytics

Progressive Visual Analytics (PVA) has gained increasing attention over the past years. It brings the user into the loop during otherwise long-running and non-transparent computations by producing intermediate partial results. These partial results can be shown to the user for early and continuous interaction with the emerging end result even while it is still being computed. Yet as clear-cut as this fundamental idea seems, the existing body of literature puts forth various interpretations and instantiations that have created a research domain of competing terms, various definitions, as well as long lists of practical requirements and design guidelines spread across different scientific communities. This makes it more and more difficult to get a succinct understanding of PVA’s principal concepts, let alone an overview of this increasingly diverging field. The review and discussion of PVA presented in this paper address these issues and provide (1) a literature collection on this topic, (2) a conceptual characterization of PVA, as well as (3) a consolidated set of practical recommendations for implementing and using PVA-based visual analytics solutions

Data-driven modelling of compressor stall flutter

Modern aircraft engines need to meet ever more stringent requirements that greatly increase the complexity of design, which strives for enhanced performance, reduced operating costs, emissions and noise simultaneously. The drive for performance leads to the development of thin, lightweight, highly loaded fan and compressor blades which are increasingly more prone to incur high, sustained vibratory stresses and aeroelastic problems such as flutter. The current practice employs preliminary design tools for flutter that are often based on empiricism or simplified analytical models, requiring extensive use of computational fluid dynamics to verify aeroelastic stability. As the industry moves to new designs, fast and accurate prediction tools are needed. In this thesis, data-driven techniques are employed to model the aeroelastic response of compressor blades. Machine learning has been applied to a plethora of engineering problems, with particular success in the field of turbulence modelling. However, conventional, black-box data- driven methods based on simple input parameters require large databases and are unable to generalise. In this work a combination of machine learning techniques and reduced order models is proposed to address both limitations at the same time. Previous knowledge of flutter is introduced in the physics guided framework by formulating relevant, steady state input features, and by injecting results from low-fidelity analytical models. The models are tested on several unseen cascades and it is found that training on even a single geometry yields accurate results. The models developed here allow flutter prediction of fan and compressor flutter stability based on the steady state flow only without a need for any CPU intensive unsteady simulations. Hence, one can predict flutter stability of a given blade for different mechanical properties (mode shape, frequency) at near zero additional cost once the mean flow is known. Moreover, for fan flutter, the model developed here can be integrated with available analytical models of intake to analyse the consequences of intake properties, such as length and acoustic liners location, on the stability of fan blades. The EU goal of climate-neutrality by 2050 requires novel design concepts in aviation which is unachievable without complimentary novel prediction and design tools. The research presented in this thesis will allow one to explore the design space for flutter stability based on steady flow only, and hence offers such an alternative. To the best of the author’s knowledge, no previous research is available on modelling of compressor stall flutter with data-driven techniques.Open Acces

NuScalen pienen modulaarisen reaktorin simulointi ja turvallisuustoiminnot

Small modular reactor (SMR) is a relatively recent concept in the nuclear power industry. Whereas the traditional large scale reactors are facing challenges due to their size, the small modular reactors intend to bypass the problems by utilizing aspects that their small size and modularity enables. However, the transition to SMRs includes many open questions. The energy industry and nuclear safety authorities are accustomed to large scale power plants, whereas experience with SMRs are shallow. This effectively creates a need for SMR studies, some of which this thesis aims to answer to. NuScale SMR was chosen as a focus of this thesis due to the concept’s reasonable level of maturity and its interesting utilization of passive safety systems. In the framework of this thesis, a NuScale SMR simulation model is built using the Apros program. The model is used to validate Apros calculation required for SMR simulation.The second objective of this thesis is to present the specific safety features of NuScale SMR that differ from current nuclear power plants. They are presented from a technical point of view and are briefly projected on Finnish regulatory guides. Feature projection reveals that many of the design features are fundamentally compatible with current guides with a few exceptions. In this thesis we perceive that among others the modular reactor mass production and passive functions could face challenges. The simulation results show that Apros code is capable of SMR and passive safety system modelling. However, the results also show that precise simulation of passive safety systems would benefit from further code development on those fields. The thesis also presents modelling guidelines that are beneficial when Apros is used for SMR modelling.Pienet modulaariset ydinreaktorit (SMR) ovat verrattain uusi konsepti ydinenergiateollisuudessa. Siinä missä tavalliset reaktorit kohtaavat huomattavia haasteita suuren kokonsa vuoksi, pienet modulaariset reaktorit pyrkivät kiertämään ne hyödyntämällä pienen kokonsa ja modulaarisuutensa mahdollistamia ominaisuuksia. Siirtyminen SMR:iin sisältää tosin myös avoimia kysymyksiä. Energiateollisuus ja ydinturvallisuusviranomaiset ovat tottuneet käsittelemään suuren kokoluokan laitoksia ja niihin liittyviä ilmiöitä, kun taas kokemukset SMR:istä ja niiden ilmiöistä ovat vähäisiä. Käytännössä tämä luo tarpeen SMR:iin kohdistuvalle tutkimukselle, jota tämäkin opinnäytetyö pyrkii tukemaan. NuScale SMR valittiin tämän työn tutkimuksen kohteeksi kyseisen konseptin kohtuullisen korkean valmiusasteen ja siinä hyödynnettävien mielenkiintoisten passiivisten ilmiöiden takia. Työssä rakennetaan Apros-ohjelmalla simulointimalli NuScalen konseptin mukaisesta SMR -koelaitteistosta. Mallin avulla validoidaan Aprosin SMR:ien simuloimiseen tarvittavaa laskentaa. Työn toinen tavoite on esittää NuScalen konseptille suunniteltuja erityisesti nykyisistä ydinvoimalaitoksista eriäviä ominaisuuksia teknisestä näkökulmasta, ja verrata niitä Suomen ydinvoimalain ja ydinturvallisuusohjeiden (YVL-ohjeet) turvallisuusvaatimuksiin. Ominaisuuksien projisointi paljastaa, että osa suunnitteluominaisuuksista sopii perustavanlaatuisella tasolla nykyisiin määräyksiin muutamin poikkeuksien. Työssä huomataan, että haasteita on muun muassa modulaaristen reaktoreiden massatuotannon ja passiivisten ominaisuuksien osalta. Simulointitulokset osoittavat Aprosin nykytilassaan kykenevän SMR:ien ja passiivisten turvallisuustoimintojen mallinnukseen. Tulokset kuitenkin osoittavat, että passiivisten systeemien tarkka simulointi hyötyisi kyseisien alueiden koodien jatkokehityksestä.Työssä myös esitetään mallinnusperiaatteita, joita olisi hyvä noudattaa, kun Aprosilla mallinnetaan SMR:iä

Numerical Investigations of Ship Forces During Lockage

Dataset: https://doi.org/10.48437/02.2021.W.9900.000

Novel Blade Design Strategy to Control the Erosion Aggressiveness of Cavitation

With the reduction in size of turbomachinery systems, cavitation aggressiveness is intensified. Erosion, caused by the repeated collapse of gaseous bubbles in proximity to solid surfaces, occurs at rates that dramatically downgrade the life expectancy of rotating parts. As a result, the compacting strategy, meant to reduce cost and improve efficiency, fails for liquid flows. The research undertaken here proposes a novel design method aimed at controlling the erosion aggressiveness of cavitation. The underlying idea is that the cavity closure shock is a determining factor in the intensity of bubble collapse mechanisms: sharp and high amplitude shocks give rise to strong erosion, while low gradient and low amplitude recoveries reduce the erosive intensity. The working hypothesis is tested here, first, by developing a novel inverse design algorithm capable of handling cavitating flow. The code solves the inviscid Euler equations and models blade cavitation using the Tohoku-Ebara barotropic equation of state. Bespoke preconditioning and multigrid procedures are constructed to handle the large amplitudes in flow regime (from hypersonic in the cavity to very low Mach number in the liquid phase). The inverse solver is then used to produce a set of 2D cascade hydrofoil geometries with smoothed shock profiles at cavity closure. The blades are assessed numerically using both steady state and time-resolved approaches. Both hydrodynamic performance, given in terms of swirl, lift and drag, and cavitation dynamics are evaluated. Recently developed erosion prediction methodologies are implemented and demonstrate compelling correlations between the erosion patterns and shock profile. Finally, experimental testing is carried out using a purposefully developed observation platform. The erosive performance of two of the geometries is measured using the paint removal technique. Results reveal a significant improvement in erosive response for the shock smoothed design, thus confirming the numerical findings as well as the validity of the design hypothesis

Thermodynamic modeling and experimental investigation of operating conditions for a SOFC/GT hybrid power plant

The SOFC/GT hybrid power plant is a promising technology to answer the challenges arising from the transition of a fossil energy based and centralized power supply system to a renewable energy based and distributed power supply system. These challenges include high electrical efficiency, fuel flexibility, operational stability, security in power supply, good part-load performance and fast response to load changes. This thesis investigates operating limitations and heat transfer effects as well as stack performance and ambient conditions variations by means of a modular and computationally efficient 0D system model. The model allows for stationary and transient simulations. Model parameters are based on a real hybrid power plant that is currently under commissioning at DLR in Stuttgart. The particular component models are based on experimental data of different level of detail or factory acceptance test protocols from suppliers, where possible. If experimental results are unavailable, component parameters are based on actual design and material specifications to allow the best model parametrization and thus best prediction of operating characteristics possible. The comparison of adiabatic and non-adiabatic simulation results emphasize the importance of proper heat transfer considerations. The consecutively performed heat transfer variation simulations support this correlation. The effects on efficiency are significant, as expected, while the operating range is severely affected by heat transfer effects, as well. An electrical efficiency (HHV) loss of about 4 percentage points is noticed in contrast to the adiabatic results, whereas the operating range is expanded by about 2kW in high power range due to relaxed cooling air requirements in the non-adiabatic scenario. The electrical efficiency (HHV) remains above 0.53 in the operating range of around 17kW to 39kW, peaking short of 0.56. The stack performance variation has only moderate influence on electrical efficiency where a gain in electrical efficiency (HHV) of up to 4 percentage points is observed with stack performance increase. However, stack performance degradation imposes a significant system constraint, in particular for the high power operating range. The maximum power is reduced from 39kW down to 24kW , while the electrical efficiency (HHV) is reduced by about 2 percentage points. The ambient conditions variation refers to temperature and pressure variations, while Central European climatic conditions are assumed. The temperature variation shows a high power operating range constraint of about 5kW once very low temperatures are investigated. The investigated pressure range shows quite similar results. However, the isothermal power range is reduced by about 60% for the temperature variation while the impact of pressure variation results in a reduction of about 10% . The changes in electrical efficiency (HHV) are limited in the range below 1 percentage point. The system is exposed to a transient daily ambient temperature profile, chosen from historic weather data to form a challenging scenario. However, the system does not show a significant response to the imposed daily temperature profile, indicating high operating stability for Central European climatic conditions. Eventually, the system is exposed to a challenging combined power and temperature profile. The isothermal power reduction by about 25% is performed in less than 5min while further power reduction to 50% requires a stack temperature adaption for about 1.7h . The system follows the profile without problems, however, reaching steady state after the temperature change requires about a week’s time due to the heat stored within the system and the related surface losses. Altogether, this work allows to investigate the details of system characteristics and operating restrictions for the represented hybrid power plant. It allows to understand the effects imposed by internal and external system challenges and can predict hazardous operating regimes, to be handled with care in the real pilot power plant