Optimisation of nonlinear motion cueing algorithm based on genetic algorithm

Motion cueing algorithms (MCAs) are playing a significant role in driving simulators, aiming to deliver the most accurate human sensation to the simulator drivers compared with a real vehicle driver, without exceeding the physical limitations of the simulator. This paper provides the optimisation design of an MCA for a vehicle simulator, in order to find the most suitable washout algorithm parameters, while respecting all motion platform physical limitations, and minimising human perception error between real and simulator driver. One of the main limitations of the classical washout filters is that it is attuned by the worst-case scenario tuning method. This is based on trial and error, and is effected by driving and programmers experience, making this the most significant obstacle to full motion platform utilisation. This leads to inflexibility of the structure, production of false cues and makes the resulting simulator fail to suit all circumstances. In addition, the classical method does not take minimisation of human perception error and physical constraints into account. Production of motion cues and the impact of different parameters of classical washout filters on motion cues remain inaccessible for designers for this reason. The aim of this paper is to provide an optimisation method for tuning the MCA parameters, based on nonlinear filtering and genetic algorithms. This is done by taking vestibular sensation error into account between real and simulated cases, as well as main dynamic limitations, tilt coordination and correlation coefficient. Three additional compensatory linear blocks are integrated into the MCA, to be tuned in order to modify the performance of the filters successfully. The proposed optimised MCA is implemented in MATLAB/Simulink software packages. The results generated using the proposed method show increased performance in terms of human sensation, reference shape tracking and exploiting the platform more efficiently without reaching the motion limitations.

Development of a dynamic surface roughness monitoring system based on artificial neural networks (ANN) in milling operation

Dynamic surface roughness prediction during metal cutting operations plays an important role to enhance the productivity in manufacturing industries. Various machining parameters such as unwanted noises affect the surface roughness, whatever their effects have not been adequately quantified. In this study, a general dynamic surface roughness monitoring system in milling operations was developed. Based on the experimentally acquired data, the milling process of Al 7075 and St 52 parts was simulated. Cutting parameters (i.e., cutting speed, feed rate, and depth of cut), material type, coolant fluid, X and Z components of milling machine vibrations, and white noise were used as inputs. The original objective in the development of a dynamic monitoring system is to simulate wide ranges of machining conditions such as rough and finishing of several materials with and without cutting fluid. To achieve high accuracy of the resultant data, the full factorial design of experiment was used. To verify the accuracy of the proposed model, testing and recall/verification procedures have been carried out and results showed that the accuracy of 99.8 and 99.7 % were obtained for testing and recall processes.

Students and staff perceptions of project/design based learning in an engineering curriculum

This paper focuses on the students and staff perceptions of project/design-based learning in an engineering curriculum. Engineering at Deakin University has used project/design based learning as one of its engineering learning principles for further development in learning and teaching. It is required to improve the learning and teaching process as a holistic approach from the perspective of students’ and staff over the entire degree program. Engaging students are an important aspect of the project/design based learning model which it helps students to be self-directed active learners. A project/design based learning environment helps a curriculum to practice career related skills for students, such as practical learning, problem solving, collaborative teamwork, innovative creative designs, active learning, and engagement with real-world assignments. The focus of this paper is to analyse the impact of project/design-based learning in an engineering curriculum. From the quantitative and qualitative analysis performed, the results are analysed and presented from a students’ and staff perspective about project/design based learning within the curriculum. This paper is also concerned with enhancing staff and students engagement through project/design based learning. The feedback was sought from students on project/design-based learning. Additional feedback is also needed from staff members who teach and perform research in engineering design. The survey results shows more than 50% of students and 75% of staff views on project/design based learning proven that the impact of project/design based learning is helps to enhance of student and staff interaction in the School of Engineering at Deakin University.

Project-oriented design-based learning in engineering education

The School of Engineering at Deakin University (SOE-DU) is committed to provide authentic and unique learning experiences to students. Over the last five years, SOE-DU has undertaken a study to develop a unique teaching and learning model. The proposed model was based on the Project- Oriented Design Based Learning (PODBL) philosophy which is unique within Australia and in the world. Fundamentally, the framework balances project-driven pedagogy with a design-focused practice in response to industry needs. This paper focuses on the development of PODBL and articulating how it helps nurture creative and industry-ready professional engineers.

The role of the facilitator in a project/design based learning environment

The Project Oriented Design Based Learning (PODBL) is a teaching and learning approach (TLA) that is based on engineering design activities undertaken during a project. PODBL encourages independent learning and a deep approach to student learning outcomes. The Centre for Advanced Design in Engineering Training (CADET) is a new engineering building with cutting edge technology facilities at Deakin University. It acts as a catalyst for a pedagogical change in the way that Engineering is delivered. This paper is focused on the role of the facilitator in a project/design based learning environment and it also looks in to appropriate staff development training for a project/design based learning environment.

Nonlinear excitation control of synchronous generators based on adaptive backstepping method

n this paper, the design of a nonlinear excitation control of a synchronous generator is presented where the generator is connected to a single machine infinite bus (SMIB) system. An adaptive backstepping method is used to design the excitation controller with an objective of enhancing the overall dynamic stability of the SMIB system under different contingencies. In this paper, two types of contingencies are considered- i) unknown parameters and physical quantities during the controller design process and ii) controller performance evaluation under different system configurations such as three-phase short circuit faults. The adaption law, which is mainly based on the formulation of Lyapunov function, is used to estimate the unknown parameters which guarantee the convergence of different physical quantities of synchronous generators, e.g., the relative speed, terminal voltage, etc. The effectiveness of the proposed scheme is evaluated under different system configurations as mentioned in the second contingency and compared to that of an existing adaptive backstepping controller and a conventional power system stabilizer (PSS). Simulation results demonstrate the superiority of the proposed control scheme over the existing controllers.

Robust optimal motion cueing algorithm based on the linear quadratic regulator method and a genetic algorithm

The aim of this paper is to design and develop an optimal motion cueing algorithm (MCA) based on the genetic algorithm (GA) that can generate high-fidelity motions within the motion simulator's physical limitations. Both, angular velocity and linear acceleration are adopted as the inputs to the MCA for producing the higher order optimal washout filter. The linear quadratic regulator (LQR) method is used to constrain the human perception error between the real and simulated driving tasks. To develop the optimal MCA, the latest mathematical models of the vestibular system and simulator motion are taken into account. A reference frame with the center of rotation at the driver's head to eliminate false motion cues caused by rotation of the simulator to the translational motion of the driver's head as well as to reduce the workspace displacement is employed. To improve the developed LQR-based optimal MCA, a new strategy based on optimal control theory and the GA is devised. The objective is to reproduce a signal that can follow closely the reference signal and avoid false motion cues by adjusting the parameters from the obtained LQR-based optimal washout filter. This is achieved by taking a series of factors into account, which include the vestibular sensation error between the real and simulated cases, the main dynamic limitations, the human threshold limiter in tilt coordination, the cross correlation coefficient, and the human sensation error fluctuation. It is worth pointing out that other related investigations in the literature normally do not consider the effects of these factors. The proposed optimized MCA based on the GA is implemented using the MATLAB/Simulink software. The results show the effectiveness of the proposed GA-based method in enhancing human sensation, maximizing the reference shape tracking, and reducing the workspace usage.

Evaluating assessment practices in design based learning environment

This investigation is focused on evaluating assessment practices in design based learning environment. The School of Engineering at Deakin University practices project/design based learning as one of its learning and teaching approach. When identifying graduate attributes particularly for undergraduate engineering programs in Australia, the program accrediting body Engineers Australia (EA) initiates a set of graduate attribute elements which was mentioned in “Stage1 competencies and elements of competency”. Stage1 competencies state that one of the important engineering application ability for graduates is ‘application of systematic engineering synthesis and design processes’. By practicing the design focused learning environment and evaluating students perceptions, This investigation examines students’ experiences of assessment practices in their curriculum through an online survey given to the same cohort of students in third year and fourth year undergraduate engineering.

Evaluation of student learning outcomes in fourth year engineering mechatronics through design based learning curriculum

This paper focuses on evaluation of student learning outcomes in fourth year engineering mechatronics through design based learning curriculum. The purpose of all engineering degrees is to provide strong grounding with principles of engineering science and technology. By learning engineering methods and approaches in an academic environment, graduates can enter the world of work and tackle real world problems with innovation and creativity. In many cases, academic staff are responsible for driving and setting high expectations in their classrooms. Sometimes staff are expected to teach subjects outside their expertise. This research paper is concerned with evaluating student learning outcomes through feedback sought from students on design-based learning approach.

Identifying inorganic material affinity classes for peptide sequences based on context learning

There is a growing interest in identifying inorganic material affinity classes for peptide sequences due to the development of bionanotechnology and its wide applications. In particular, a selective model capable of learning cross-material affinity patterns can help us design peptide sequences with desired binding selectivity for one inorganic material over another. However, as a newly emerging topic, there are several distinct challenges of it that limit the performance of many existing peptide sequence classification algorithms. In this paper, we propose a novel framework to identify affinity classes for peptide sequences across inorganic materials. After enlarging our dataset by simulating peptide sequences, we use a context learning based method to obtain the vector representation of each amino acid and each peptide sequence. By analyzing the structure and affinity class of each peptide sequence, we are able to capture the semantics of amino acids and peptide sequences in a vector space. At the last step we train our classifier based on these vector features and the heuristic rules. The construction of our models gives us the potential to overcome the challenges of this task and the empirical results show the effectiveness of our models.

A non-fullerene electron acceptor based on central carbazole and terminal diketopyrrolopyrrole functionalities for efficient, reproducible and solution-processable bulk-heterojunction devices

A novel, solution-processable non-fullerene electron acceptor, 6,6′-((9-(heptadecan-9-yl)-9H-carbazole-2,7-diyl)bis(thiophene-5,2-diyl))bis(2,5-bis(2-ethylhexyl)-3-(thiophen-2-yl)-2,5-dihydropyrrolo[3,4-c]pyrrole-1,4-dione) (coded as N7), based on central carbazole and terminal diketopyrrolopyrrole building blocks was designed, synthesized and characterized. N7 displayed excellent solubility, thanks to its design allowing incorporation of numerous lipophilic chains, thermal stability, and afforded a 2.30% power conversion efficiency with a high open-circuit voltage (1.17 V) when tested with the conventional donor polymer poly(3-hexylthiophene) in solution-processable bulk-heterojunction devices. To our knowledge, not only is N7 the first reported chromophore based on carbazole and diketopyrrolopyrrole functionalities but the open-circuit voltage reported here is among the highest values for a single junction bulk-heterojunction device that has been fabricated using a simple device architecture, with reproducible outcomes and with no special treatment.

A research agenda for design-based learning in engineering education

It is often argued that ‘design’ is an (perhaps the) essential characteristic of engineering practice; that, “Design requires unique knowledge, skills, and attitudes common to all engineering disciplines, and it is these attributes that distinguish engineering as a profession.” Hence, it is not surprising to see engineering design identified as a key element of engineering education. There are a range of pedagogical models described, badged with a range of names, that are suggested as approaches to teaching engineering design, for example: project-based learning, problem-based learning, design-based learning, conceive-design-implement-operate (CDIO), problem-oriented project-based learning, social design based learning and project-oriented, design-based learning. While significant literature on engineering design education generally exists, many authors note open questions regarding optimal pedagogical approaches, and opportunities for further evaluation and research. In this paper we draw on literature about design education and DBL in engineering education, and synthesise themes that present a potential research agenda for those educators involved in DBL in engineering education.A search of the research literature was conducted using terms related to DBL in engineering education, including ‘Engineering Design’, ‘Design Education’, ‘Engineering + Project Based Learning’, ‘Engineering + Problem Based Learning’ and ‘Engineering + Design Based Learning’. The literature thus collected was expanded by inspecting the lists of references in the initially identified literature set for further potentially relevant literature. This process was repeated until no further related literature was identified, and resulted in 124 items. All collected literature was carefully reviewed for explicitly identified suggestions for future research. The authors also considered the literature set as a whole to identify additional research possibilities implied by aspects of DBL practice commonly addressed weakly, or not at all, in the available published research. From the results of this review, a set of themes was synthesised by grouping related research recommendations and possibilities. In the following section the identified research themes are presented and, for each, a summary of the supporting literature is given and a central research question is formulated by the authors.

In situ MRI of operating solid-state Lithium metal cells based on ionic plastic crystal electrolytes

Solid-state ion conductors based on organic ionic plastic crystals (OIPCs) are a promising alternative to conventional liquid electrolytes in lithium battery applications. The OIPC-based electrolytes are safe (nonflammable) and flexible in terms of design and operating conditions. Magnetic resonance imaging (MRI) is a powerful noninvasive method enabling visualization of various chemical phenomena. Here, we report a first quantitative in situ MRI study of operating solid-state lithium cells. Lithium ion transfer into the OIPC matrix during the ongoing discharge of the anode results in partial liquefaction of the electrolyte at the metal interface. The developed liquid component enhances the ion transport across the interface and overall battery performance. Displacement of the liquefaction front is accompanied by a faster Li transfer through the grain boundaries and depletion at the cathode. The demonstrated solid-liquid hybrid properties, inherent in many OIPCs, combine benefits of highly conductive ionic liquids with safety and flexibility of solids.

Parametric urbanism in practice: Investigating new approaches based on analytically driven methods.

Growing popularity in parametric urbanism has prompted investigation into the effects digital parametric systems have had on the way we design. This research proposes a new method of Problem Centric System Design, encouraging working methods that are led by both the designer’s aspirations and the requirements of the design problem.