Many testing and benchmarking scenarios in software and systems engineering depend on the systematic generation of graph models. For instance, tool qualification necessitated by safety standards would require a large set of consistent (well-formed or malformed) instance models specific to a domain. However, automatically generating consistent graph models which comply with a metamodel and satisfy all well-formedness constraints of industrial domains is a significant challenge. Existing solutions which map graph models into first-order logic specification to use back-end logic solvers (like Alloy or Z3) have severe scalability issues. In the paper, we propose a graph solver framework for the automated generation of consistent domain-specific instance models which operates directly over graphs by combining advanced techniques such as refinement of partial models, shape analysis, incremental graph query evaluation, and rule-based design space exploration to provide a more efficient guidance. Our initial performance evaluation carried out in four domains demonstrates that our approach is able to generate models which are 1-2 orders of magnitude larger (with 500 to 6000 objects!) compared to mapping-based approaches natively using Alloy.

Design space exploration (DSE) aims to find optimal design candidates of a domain with respect to different objectives where design candidates are constrained by complex structural and numerical restrictions. 14,18] aims to find such candidates that are reachable from an initial model by applying a sequence of exploration rules. Solving a rule-based DSE problem is a difficult challenge due to the inherently dynamic nature of the problem.In the current paper, we propose to integrate multi-objective optimization techniques by using Non-dominated Sorting Genetic Algorithms (NSGA) to drive rule-based design space exploration. For this purpose, finite populations of the most promising design candidates are maintained wrt. different optimization criteria. In our context, individuals of a generation are defined as a sequence of rule applications leading from an initial model to a candidate model. Populations evolve by mutation and crossover operations which manipulate (change, extend or combine) rule execution sequences to yield new individuals.Our multi-objective optimization approach for rule-based DSE is domain independent and it is automated by tooling built on the Eclipse framework. The main added value is to seamlessly lift multi-objective optimization techniques to the exploration process preserving both domain independence and a high-level of abstraction. Design candidates will still be represented as models and the evolution of these models as rule execution sequences. Constraints are captured by model queries while objectives can be derived both from models or rule applications. Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from Permissions@acm.org.

The effectiveness of a novel actuation architecture developed to control flutter and post-flutter is investigated in this paper. To this purpose, the performance of an active control strategy in various operational conditions is experimentally examined. A physical prototype, consisting of a wing section with multiple spoilers mounted on an aeroelastic apparatus, has been designed and assembled to carry out open- and closed-loop operations. Wind tunnel aeroelastic testing are performed with a plunging and pitching apparatus specifically designed to simulating wing sections with prescribed stiffness characteristics, including torsional structural nonlinearities responsible of a stable nonlinear post-flutter limit cycle behavior. Five surface mounted spoilers located at 15% of the chord from the leading edge are used to control aeroelastic vibrations in pre- and post-flutter. The spoilers design, including selection of best size and chord position and considering the geometrical constraints, has been carried out by CFD simulation, with the objective of maximizing the aerodynamic pitching moment used to stabilize the lifting surface at the various speeds. The spoiler actuations are commanded by an active control system as to extend the flight region in the natural post-flutter condition. A simple PID algorithm is implemented to test the efficiency of the control system design to suppress flutter oscillation. A trial and error tuning of the gain has been executed on-site during the experimental campaign. Only the pitch angle is used as state feedback in the control laws to stabilize the system above the open-loop flutter velocity. Results and pertinent conclusions are outlined.

The use of organic refrigerants or supercritical CO2 (sCO2) as a working fluid in closed loop power cycles has the potential to revolutionise power generation. Thermodynamic cycle efficiency can be improved by selecting bespoke working fluids that best suit a given combination of heat source and heat sink temperatures, but thermal efficiency can be maximised by pairing this with a custom made turbine. This work describes the development and design of a new 100kW thermal laboratory-scale test loop at the University of Queensland. The loop has capabilities for characterising both simple and recuperated refrigerant and sCO2 organic Rankine cycles in relation to overall cycle performance and for the experimental characterisation of radial inflow turbines. The aim of this facility is to generate high quality validation data and to gain new insight into overall loop performance, control operation, and loss mechanisms that prevail in all loop components, including radial turbines when operating with supercritical fluids. The paper describes the current test loop and provides details on the available test modes: an organic Rankine cycle mode, a closed loop Brayton cycle mode, and heat exchanger test mode and their respective operating ranges. The bespoke control and data acquisition system has been designed to ensure safe loop operation and shut down and to provide high quality measurement of signals from more than 60 sensors within the loop and test turbine. For each measurement, details of the uncertainty quantification in accordance with ASME standards are provided, ensuring data quality. Data from the commissioning of the facility is provided in this paper. This data confirms controlled operation of the loop and the ability to conduct both cycle characterisation tests and turbomachinery tests.

In this paper, an outlook about the present of electrical aviation is given. The relatively small energy density of current battery technologies is adequate to build usable electric car, but not suitable for electric aircraft. Because of the very limited amount of energy available on-board, a couple of percent in efficiency can give significant increase in range and flight time, hence the development of more efficient propulsion system and E-motor is as important as the development of battery technologies. Current research results at the University of Dunaujvaros show, that building E-motors from amorphous materials is possible, and can easily increase the efficiency of high speed E-motors.