shabnam sadeghi esfahlani

ABSTRACT This paper presents the result of an optimisation study by linear, quadratic, Kriging and radial basis meta-models in order to augment the crashworthiness characteristic of cellular structures. Thin-walled cellular structures (honeycomb) have the ability to absorb impact energy during crashing, thus it is important to enhance the crushing efficiency and optimise the structural reliability. The optimisation carried out in this study is aimed at maximising the energy absorption characteristics using meta-models while considering some limitation on the maximum force as a constraint. Achieving these characteristics is an important factor in crashworthiness analysis, which minimises the damage in dynamic performance. The objective of using various meta-models is to qualify the meta-model in crashworthiness analysis using different point selection schemes and different number of points. The optimisation is performed in two stages; through experimental design methods in which a set of sampling points is selected from design space and polynomial fitting in order to optimise the objective. It is concluded that D-optimal best suits response surface method for model approximation. Kriging performed best by space filling and the best point selection scheme for radial basis surrogate is latin hypercube design. The results show that for optimising the crashworthiness characteristics of honeycomb, Kriging and quadratic response surface (RS) are best, in terms of accuracy and robustness point of view and the radial basis neural network would be the second best. During this optimisation, the RS was combined with detailed geometrically simplified finite element model of honeycomb cell using ANSYS/LS-DYNA, LS-DYNA and LS-opt packages. Approximated functions combined with the finite element analysis were an effective tool to optimise highly non-linear impact problems. This has led to the development of validated algorithm that enabled the development of the optimised solutions.

This paper proposes the use of a non-immersive virtual reality rehabilitation system ReHabgame developed using Microsoft Kinect and the Thalmic Labs Myo gesture control armband. The ReHabgame was developed based on two third-person video games that provide a feasible possibility of assessing postural control and functional reach tests. It accurately quantifies specific postural control mechanisms including timed standing balance, functional reach tests using real-time anatomical landmark orientation, joint velocity, and acceleration while end trajectories were calculated using an inverse kinematics algorithm. The game was designed to help patients with neurological impairment to be subjected to physiotherapy activity and practice postures of daily activities. The subjective experience of the ReHabgame was studied through the development of an Engagement Questionnaire (EQ) for qualitative, quantitative and Rasch model. The Monte-Carlo Tree Search (MCTS) and Random object (ROG) genera...

Safe cycling requires situational awareness to identify and perceive hazards in the environment to react to and avoid dangerous situations. Concurrently, tending to external distractions leads to a failure to identify hazards or to respond appropriately in a time-constrained manner. Hazard perception training can enhance the ability to identify and react to potential dangers while cycling. Although cycling on the road in the presence of driving cars provides an excellent opportunity to develop and evaluate hazard perception skills, there are obvious ethical and practical risks, requiring extensive resources to facilitate safety, particularly when involving children. Therefore, we developed a Cycling and Hazard Perception virtual reality (VR) simulator (CHP-VR simulator) to create a safe environment where hazard perception can be evaluated and/or trained in a real-time setting. The player interacts in the virtual environment through a stationary bike, where sensors on the bike transf...

This paper describes an avenue for artificial and computational intelligence techniques applied within games research to be deployed for purposes of physical therapy. We provide an overview of prototypical research focussed on the application of motion sensor input devices and virtual reality equipment for rehabilitation of motor impairment: an issue typical of patients of traumatic brain injuries. We highlight how advances in procedural content generation and player modelling can stimulate development in this area by improving quality of rehabilitation programmes and measuring patient performance.

Fused Deposition Modelling (FDM) is a widely used additive manufacturing process. It utilizes a variety of homogeneous and heterogeneous materials for product development. A new manufacturing process termed as Hybrid Fused Deposition Modelling (HFDM) has been used for the manufacture of various copper metal mesh (99.99% pure)/PLA (polylactic acid or polylactide) plastic composites. These products have been subjected to standardized experimental testing for evaluating properties such as tear resistance, tensile strength, water absorption, hardness, and flexural strength. The tests have been conducted to analyse the effectiveness of the HFDM process in manufacturing stronger composites compared to commercially available PLA and copper-infused PLA. Microstructural characterization has also been carried out to analyse the bond between the plastic and metal mesh layers. The results have been promising and demonstrate the effectiveness of HFDM to produce Cu/PLA composites with superior mechanical properties compared to parent FDM-printed PLA plastic as well as copper-infused FDM-printed PLA. Multiple copper mesh layers have been placed strategically within the test specimens to study their effect on the composites made by HFDM. The experimental results show that the process is capable of manufacturing high-quality composites (Cu/PLA) with tailored properties for various engineering applications.

Additive Manufacturing (AM) is gaining enormous attention from academic and industrial sectors for product development using different materials. Fused Deposition Modelling (FDM) is a popular AM method that works with thermoplastics. This process offers benefits of customisation both in terms of hardware and software in the case of desktop-based FDM systems. Enhancement of mechanical properties for the traditional thermoplastic material is a widely researched area and various materials have been added to achieve this goal. This paper focuses on the manufacture of glass fiber reinforced plastic (GFRP) composites using Hybrid Fused Deposition Modelling (HFDM). Commonly available polylactic acid or polylactide (PLA) material was inter-laced with 0.03 mm thick glass fiber sheets to manufacture GFRP products followed by tensile testing. This was done to investigate whether adding more layers increases the tensile strength of the GFRP products or not. Furthermore, the maximum number of gl...

Abstract This paper proposes the development of a system incorporating inertial measurement unit (IMU), a consumer-grade digital camera and a fire detection algorithm simultaneously with a nano Unmanned Aerial Vehicle (UAV) for inspection purposes. The video streams are collected through the monocular camera and navigation relied on the state-of-the-art indoor/outdoor Simultaneous Localisation and Mapping (SLAM) system. It implements the robotic operating system (ROS) and computer vision algorithm to provide a robust, accurate and unique inter-frame motion estimation. The collected onboard data are communicated to the ground station and used the SLAM system to generate a map of the environment. A robust and efficient re-localization was performed to recover from tracking failure, motion blur, and frame lost in the data received. The fire detection algorithm was deployed based on the color, movement attributes, temporal variation of fire intensity and its accumulation around a point. The cumulative time derivative matrix was utilized to analyze the frame-by-frame changes and to detect areas with high-frequency luminance flicker (random characteristic). Color, surface coarseness, boundary roughness, and skewness features were perceived as the quadrotor flew autonomously within the clutter and congested area. Mixed Reality system was adopted to visualize and test the proposed system in a physical environment, and the virtual simulation was conducted through the Unity game engine. The results showed that the UAV could successfully detect fire and flame, autonomously fly towards and hover around it, communicate with the ground station and simultaneously generate a map of the environment. There was a slight error between the real and virtual UAV calibration due to the ground truth data and the correlation complexity of tracking real and virtual camera coordinate frames.

There is some evidence that disordered self-processing in autism spectrum disorders is linked to the social impairments characteristic of the condition. To investigate whether bodily self-consciousness is altered in autism spectrum disorders as a result of multisensory processing differences, we tested responses to the full body illusion and measured peripersonal space in 22 adults with autism spectrum disorders and 29 neurotypical adults. In the full body illusion set-up, participants wore a head-mounted display showing a view of their ‘virtual body’ being stroked synchronously or asynchronously with respect to felt stroking on their back. After stroking, we measured the drift in perceived self-location and self-identification with the virtual body. To assess the peripersonal space boundary we employed an audiotactile reaction time task. The results showed that participants with autism spectrum disorders are markedly less susceptible to the full body illusion, not demonstrating the...

This paper proposes the use of a non-immersive virtual reality rehabilitation system "ReHabgame" developed using Microsoft Kinect™ and the Thalmic™ Labs Myo gesture control armband. The ReHabgame was developed based on two third-person video games that provide a feasible possibility of assessing postural control and functional reach tests. It accurately quantifies specific postural control mechanisms including timed standing balance, functional reach tests using real-time anatomical landmark orientation, joint velocity, and acceleration while end trajectories were calculated using an inverse kinematics algorithm. The game was designed to help patients with neurological impairment to be subjected to physiotherapy activity and practice postures of daily activities. The subjective experience of the ReHabgame was studied through the development of an Engagement Questionnaire (EQ) for qualitative, quantitative and Rasch model. The Monte-Carlo Tree Search (MCTS) and Random objec...

—Rehabiliation robotics combined with video game technology provides a means of assisting in the rehabilitation of patients with neuromuscular disorders by performing various facilitation movements. The current work presents ReHabGame, a serious game using a fusion of implemented technologies that can be easily used by patients and therapists to assess and enhance sensorimotor performance and also increase the activities in the daily lives of patients. The game allows a player to control avatar movements through a Kinect Xbox, Myo armband and rudder foot pedal, and involves a series of reach-grasp-collect tasks whose difficulty levels are learnt by a fuzzy interface. The orientation, angular velocity, head and spine tilts and other data generated by the player are monitored and saved, whilst the task completion is calculated by solving an inverse kinematics algorithm which orientates the upper limb joints of the avatar. The different values in upper body quantities of movement provide fuzzy input from which crisp output is determined and used to generate an appropriate subsequent rehabilitation game level. The system can thus provide personalised, autonomously-learnt rehabilitation programmes for patients with neuromuscular disorders with superior predictions to guide the development of improved clinical protocols compared to traditional theraputic activities.

This paper describes an avenue for artificial and computational intelligence techniques applied within games research to be deployed for purposes of physical therapy. We provide an overview of prototypical research focussed on the application of motion sensor input devices and virtual reality equipment for rehabilitation of motor impairment: an issue typical of patients of traumatic brain injuries. We highlight how advances in procedural content generation and player modelling can stimulate development in this area by improving quality of rehabilitation programmes and measuring patient performance.

—Artificial and Computational Intelligence in computer games play an important role that could simulate various aspects of real life problems. Development of artificial intelligence techniques in real time decision-making games can provide a platform for the examination of tree search algorithms. In this paper, we present a rehabilitation system known as RehabGame in which the Monte-Carlo Tree Search algorithm is used. The objective of the game is to combat the physical impairment of stroke/ brain injury casualties in order to improve upper limb movement. Through the process of a real-time rehabilitation game, the player decides on paths that could be taken by her/his upper limb in order to reach virtual goal objects. The system has the capability of adjusting the difficulty level to the player s ability by learning from the movements made and generating further subsequent objects. The game collects orientation, muscle and joint activity data and utilizes them to make decisions on game progression. Limb movements are stored in the search tree which is used to determine the location of new target virtual fruit objects by accessing the data saved in the background from different game plays. It monitors the enactment of the muscles strain and stress through the Myo armband sensor and provides the next step required for the rehabilitation purpose. The results from two samples show the effectiveness of the Monte-Carlo Tree Search in the RehabGame by being able to build a coherent hand motion. It progresses from highly achievable paths to the less achievable ones, thus configuring and personalizing the rehabilitation process.

This paper presents the result of an optimisation study by linear, quadratic, Kriging and radial basis meta-models in order to augment the crashworthiness characteristic of cellular structures. Thin-walled cellular structures (honeycomb) have the ability to absorb impact energy during crashing, thus it is important to enhance the crushing efficiency and optimise the structural reliability. The optimisation carried out in this study is aimed at maximising the energy absorption characteristics using meta-models while considering some limitation on the maximum force as a constraint. Achieving these characteristics is an important factor in crashworthiness analysis, which minimises the damage in dynamic performance. The objective of using various meta-models is to qualify the meta-model in crashworthiness analysis using different point selection schemes and different number of points. The optimisation is performed in two stages; through experimental design methods in which a set of sampling points is selected from design space and polynomial fitting in order to optimise the objective. It is concluded that D-optimal best suits response surface method for model approximation. Kriging performed best by space filling and the best point selection scheme for radial basis surrogate is latin hypercube design. The results show that for optimising the crashworthiness characteristics of honeycomb, Kriging and quadratic response surface (RS) are best, in terms of accuracy and robustness point of view and the radial basis neural network would be the second best. During this optimisation, the RS was combined with detailed geometrically simplified finite element model of honeycomb cell using ANSYS/LS-DYNA, LS-DYNA and LS-opt packages. Approximated functions combined with the finite element analysis were an effective tool to optimise highly non-linear impact problems. This has led to the development of validated algorithm that enabled the development of the optimised solutions.

Structural optimization for crashworthiness criteria is of particular signisignificance especially at early stage of design. The comparative study of Kriging and radial basis function network (RBFN) was performed in order to improve the crashworthiness eects of honeycomb. Improving
the crashworthiness characteristic of honeycomb was achieved using LS-OPTr and domain reduction strategy. This optimization is performed on the basis of validated numerical simulation to establish
the approximated model to illustrate the relationship between the responses and design variables. The
results showed that Kriging meta-model is excelled in accuracy, robustness and efficiency compared
to radial basis function (RBF) and crashworthiness characteristic of honeycomb is improved by 4%.

Engineers in many industries have been simulating design behavior using traditional methods employing
the conventional wisdoms gained from professional practice conducted over many years. In this study an approach is
proposed for optimal design of multilevel system under uncertainties. We extend the numerical analysis target to
probabilistic design approach by treating stochastic quantities as random variables and parameters and posing
reliability-based design restrictions. When used in simulation, once the random variables of boundary conditions,
geometry and material properties are specified for a specific analysis case, the input variables are studied
simultaneously by using statistical sampling methods. The parametric finite element analysis (FEA) model is then
invoked repeatedly, performing deterministic analyses over the resulting input parameters. The case studies assessed
in this investigation has shown that effects of different parameters in relation to specific physical properties that
have the greatest impact can be evaluated. In this way the probabilistic analysis was used to identify the steps
needed for future optimization and that how FE simulation technology can be used to understand production
processes uncertainties and related parameter variations in manufacturing process leading to increased product
reliability and quality.

Thin walled cellular structures have the ability to absorb impact energy during crashing thus it is important to enhance the crashing efficiency and optimise the structural reliability. This paper discusses the honeycomb cell configuration optimization procedure. For the design optimization, the response surface method (RSM) is used to formulate the complex design where the energy absorption (EA) representing the structure’s ability of absorbing energy was selected as objective, the Y split side parting length w1 , w2 , and thickness T1 are defined as three design variables, and the maximum crushing force (Max.F) occurs as constraint. During this distinctive optimization, the (RSM) was combined with detailed geometrically simplified finite element (FE) model using ANSYS/LS-DYNA (pre-processor), LS-DYNA (solver) and LS-Opt (optimiser). RSM combined with (FE)model without user intervention, was the effective tool to optimize non-linear impacted cellular structures. Optimal design achieved through LS-OPT is compared to the validated results for accuracy and effectiveness.