Editor’s Choice Articles

Over the last few years, autonomous vehicles (AVs) have witnessed tremendous worldwide interest. Although AVs have been extensively studied in the literature regarding their benefits, implications, and public acceptance, research on the physical infrastructure requirements for autonomous vehicles is still in the infancy stage. For the road infrastructure, AVs can be very promising; however, AVs might introduce new risks and challenges. This paper investigates the impact of AVs on the physical infrastructure with the objective of revealing the infrastructure changes and challenges in the era of AVs. In AVs, the human factor, which is the major factor that influences the geometric design, will not be a concern anymore so the geometric design requirements can be relaxed. On the other hand, the decrease in the wheel wander, because of the lane-keeping system, and the increase in the lane capacity, because of the elimination of the human factor, will bring an accelerated rutting potential and will quickly deteriorate the pavement condition. Additionally, the existing structural design methods for bridges are not safe to support autonomous truck platoons. For parking lots, AVs have the potential to significantly increase the capacity of parking lots using the blocking strategy. However, the implementation of this parking strategy faces multiple issues such as the inconsistent marking system. Finally, AVs will need new infrastructure facilities such as safe harbor areas. Full article

The execution of manual material handling activities in the workplace exposes workers to large lumbar loads that increase the risk of musculoskeletal disorders and low back pain. In particular, the redesign of the workplace is making the execution of pulling activities more common, as an alternative to lifting and carrying tasks. The biomechanical analysis of the task revealed a substantial activation of the spinal muscles. This suggests that the user may benefit from the assistance of a back-support exoskeleton that reduces the spinal muscle activity and their contribution to lumbar compression. This work addresses this challenge by exploiting the versatility of an active back-support exoskeleton. A control strategy was specifically designed for assisting pulling that modulates the assistive torques using the forearm muscle activity. These torques are expected to adapt to the user’s assistance needs and the pulled object mass, as forearm muscle activity is considered an indicator of grip strength. We devised laboratory experiments to assess the feasibility and effectiveness of the proposed strategy. We found that, for the majority of the subjects, back muscle activity reductions were associated with the exoskeleton use. Furthermore, subjective measurements reveal advantages in terms of perceived support, comfort, ease of use, and intuitiveness. Full article

Recent population migrations have led to numerous accidents and deaths. Little research has been done to help migrants in their journey. For this reason, a literature review of the latest research conducted in previous years is required to identify new research trends in human-swarm interaction. This article presents a review of techniques that can be used in a robots swarm to find, locate, protect and help migrants in hazardous environment such as militarized zone. The paper presents a swarm interaction taxonomy including a detailed study on the control of swarm with and without interaction. As the interaction mainly occurs in cluttered or crowded environment (with obstacles) the paper discussed the algorithms related to navigation that can be included with an interaction strategy. It focused on comparing algorithms and their advantages and disadvantages. Full article

In modern vehicle development, suspension components have to meet many boundary conditions. In noise, vibration, and harshness (NVH) development these are for example eigenfrequencies and frequency response function (FRF) amplitudes. Component geometry parameters, for example kinematic hard points, often affect multiple of these targets in a non intuitive way. In this article, we present a practical approach to find optimized parameters for a component design, which fulfills an FRF target curve. By morphing an initial component finite element model we create training data for an artificial neural network (ANN) which predicts FRFs from geometry parameter input. Then the ANN serves as a metamodel for an evolutionary algorithm optimizer which identifies fitting geometry parameter sets, meeting an FRF target curve. The methodology enables a component design which considers an FRF as a component target. In multiple simulation examples we demonstrate the capability of identifying component designs modifying specific eigenfrequency or amplitude features of the FRFs. Full article

This study utilises the Pareto approach to highlight the energy losses that mainly originate from the phenomena of tiny, initiated events created by end-users of electricity in Australia. Simulation modelling was applied through two stages to examine residential households’ electricity consumption behaviour in New South Wales, Australia. Stage one analysis applied Hierarchical agglomerative clustering and a dendrogram to denote the respective Euclidean distance between the different clusters. Heat maps and threshold value area charts were used to compare the mean power demand for six respective clusters. Stage two used ‘sensitivity analysis’ to investigate how uncertainty in the electricity demand can be allocated to the uncertainty of energy losses. The findings envision practical solutions to dealing with the variability of energy losses and the proposal to set new demand-side strategies associated with individuals. Retail prices of electricity in Australia have risen by roughly 60% since 2007. The research contributes to knowledge about the roots of energy losses in Australia, creating a $210M cost value. Energy losses are of significant economic value, while also impacting energy security. The first limitation of this study is using approaches from complexity theory to grasp the philosophical issues behind the research design and clarifying which insights suit what kind of evidence, thus identifying the data that needed to be collected. The second limitation is that this study’s methodology used a mostly quantitative approach that describes and explains a complex phenomenon in depth more than exploring and confirming that phenomenon. The third and final limitation is that this study’s context is also limited regarding selected sample criteria. The context is limited to a particular demographic area in New South Wales (NSW) in Australia and is also limited to residential houses (not industrial or commercial), which was opposed by data availability and access. The research draws on ‘peak and off-peak’ scales of electricity demand cause energy losses. The research shows the role of the phenomena of spontaneous emergence as a non-linked constraint which is the main issue that splits the optimal solution into pieces and significantly complicates the solution task. Demand side management (DSM) of electricity can be improved from this to construct new demand-side strategies. The study is structured around understanding the consequences of the scalability of events and the clustering dynamic of non-linearity through relevance complexity concepts exclusive to spontaneous emergence (SE), power laws (PLs), Paretian approach (PA), and tiny initiated events (TIEs). We examined the issues of the spontaneous emergence of non-linear, dynamic behaviour involved in the electricity demand of end-users on the basis of pushing individual systems of end-users to the edge of self-organised criticality (SOC). Revising the demand system’s complexity has value in constituting a core domain of interest in what is new in the field of demand side management (DSM), thus contributing to understanding end-users’ behaviour-driven energy losses from both theoretical and empirical perspectives. Full article

In the era of Industry 4.0, remote monitoring and controlling appliance/equipment at home, institute, or industry from a long distance with low power consumption remains challenging. At present, some smart phones are being actively used to control appliances at home or institute using Internet of Things (IoT) systems. This paper presents a novel smart automation system using long range (LoRa) technology. The proposed LoRa based system consists of wireless communication system and different types of sensors, operated by a smart phone application and powered by a low-power battery, with an operating range of 3–12 km distance. The system established a connection between an android phone and a microprocessor (ESP32) through Wi-Fi at the sender end. The ESP32 module was connected to a LoRa module. At the receiver end, an ESP32 module and LoRa module without Wi-Fi was employed. Wide Area Network (WAN) communication protocol was used on the LoRa module to provide switching functionality of the targeted area. The performance of the system was evaluated by three real-life case studies through measuring environmental temperature and humidity, detecting fire, and controlling the switching functionality of appliances. Obtaining correct environmental data, fire detection with 90% accuracy, and switching functionality with 92.33% accuracy at a distance up to 12 km demonstrated the high performance of the system. The proposed smart system with modular design proved to be highly effective in controlling and monitoring home appliances from a longer distance with relatively lower power consumption. Full article

As an alternative to powder-bed based processes, metal parts can be additively manufactured by extrusion based additive manufacturing. In this process, a highly filled polymer filament is deposited and subsequently debindered and sintered. Choosing a proper orientation of the part that satisfies the requirements of the debinding and sintering processes is crucial for a successful manufacturing process. To determine the optimal orientation for debinding, first, the part must be scaled in order to compensate the sinter induced shrinkage. Then, a finite element analysis is performed to verify that the maximum stresses due to the dead load do not exceed the critical stress limits. To ease this selection process, an approach based on open source software is shown in this article to efficiently determine a part’s optimal orientation during debinding. This automates scaling, debinding simulation, and postprocessing for all six main directions. The presented automated simulation framework is examined on three application examples and provides plausible results in a technical context for all example parts, leading to more robust part designs and a reduction of experimental trial and error. Therefore, the presented framework is a useful tool in the product development process for metal extrusion additive manufacturing applications. Full article

While schools struggle financially, capital for purchasing physical learning aids is often cut. To determine if costs could be reduced for learning aids, this study analyzed classroom-based distributed digital manufacturing using 3-D printing of open-source learning aid designs. Learning aid designs are analyzed in detail for their economic viability considering printing and assembly costs with purchased components and compared to equivalent or inferior commercial products available on Amazon. The results show current open-source 3-D printers are capable of manufacturing useful learning aids and that doing so provides high economic savings in the classroom. Overall, the average learning aid would save teachers 86% when fabricating it themselves. The results show that the average design evaluated was downloaded over 1,500 times and the average savings per year per open-source learning aid design was USD 11,822. To date, the 38 learning aid designs evaluated in this study saved over USD 45,000 each and the total of all of them saved the international educational community over USD 1.7 million. It is clear that investing in the development of open-source learning aids for students provides a return on investment (ROI) for investors hoping to improve education, on average, of more than 100%. Full article

The European Commission has identified the building industry as one of the key sectors to achieve its 2020 strategy to create conditions for smart, sustainable, and inclusive growth. In this frame, the aim of Horizon 2020′s Eensulate project is the development of innovative lightweight and highly insulating energy efficient unitized building façades, suitable for both new and existing buildings. The Eensulate façade module integrates two components developed within the project: Vacuum Insulated Glass (VIG) for architectural purposes, with a U-value of 0.3 W/sqm∙K; a highly insulating foam for automated manufacturing and insulation for the spandrel part. This article presents the Eensulate façade system design simulations and achievements related to VIG integration to solve issues that emerged by the utilization of its innovative components (sealant thermal bridge and getter strips). VIG design and testing have gradually changed the façade module and consequently, façade components have been progressively designed to achieve the expected target of 0.641 W/sqm∙K for thermal transmittance. The results demonstrate that the target can be achieved by aluminum profiles, Ethylene Propylene Diene Monomer (EPDM) thermal bridge, and additional insulating components, obtaining a new product for unitized façades able to reduce energy consumption in buildings with large glass surfaces. Full article

In this paper, a model for a single stage plasma gasification system for marine vessels characterized by significant waste production is proposed. The main objective of the model is to investigate the effects of different feedstock compositions on key parameters, such as electrical power produced and heat recovered. The different types of waste generated onboard are described along with their environmental impacts. Specific attention is given to solid wastes, sewage sludge and plastic wastes as potential feedstock. Their average generation, proximate and ultimate analysis are defined, as input to the process model. The process assumptions used in the simulation model are illustrated. The system model is divided into five units: the pre-treatment unit; the gasification unit; the syngas cleaning unit; the energy conversion unit; and the heat recovery unit. Four operational scenarios are investigated to consider several variations of composition of the main feedstock. From the results of the simulations, the system model shows good feedstock flexibility, and the possibility of operating in net electricity gain conditions. The cold gas efficiency of the process is also assessed and its maximum value is obtained for the highest concentrations of sewage sludge (33.3%) and plastic (16.7%). Other parameters investigated are the combustion temperature, sorbent consumption in the cleaning process, feedstock and syngas lower heating value LHV. Full article

Design is about understanding the system and its users. Although User Experience (UX) research methodologies aim to explain the benefits of a holistic measurement approach including explicit (e.g., self-reported) and implicit (e.g., automatic and unconscious biophysiological reactions) data to better understand the global user experience, most of the personas and customer journey maps (CJM) seen in the literature and practice are mainly based on perceived and self-reported users’ responses. This paper aims to answer a call for research by proposing an experimental design based on the collection of both explicit and implicit data in the context of an authentic user experience. Using an inductive clustering approach, we develop a data driven CJM that helps understand, visualize, and communicate insights based on both data typologies. This novel tool enables the design development team the possibility of acquiring a broad portrait of both experienced (implicit) and perceived (explicit) users’ experiences. Full article

Emerging 3D printing technologies are enabling the rapid fabrication of complex designs with favorable properties such as mechanically efficient lattices for biomedical applications. However, there is a lack of biocompatible materials suitable for printing complex lattices constructed from beam-based unit cells. Here, we investigate the design and mechanics of biocompatible lattices fabricated with cost-effective stereolithography. Mechanical testing experiments include material characterization, lattices rescaled with differing unit cell numbers, topology alterations, and hierarchy. Lattices were consistently printed with 5% to 10% lower porosity than intended. Elastic moduli for 70% porous body-centered cube topologies ranged from 360 MPa to 135 MPa, with lattices having decreased elastic moduli as unit cell number increased. Elastic moduli ranged from 101 MPa to 260 MPa based on unit cell topology, with increased elastic moduli when a greater proportion of beams were aligned with the loading direction. Hierarchy provided large pores for improved nutrient transport and minimally decreased lattice elastic moduli for a fabricated tissue scaffold lattice with 7.72 kN/mm stiffness that is suitable for bone fusion. Results demonstrate the mechanical feasibility of biocompatible stereolithography and provide a basis for future investigations of lattice building blocks for diverse 3D printed designs. Full article

This paper presents the development of an electromagnetic energy harvester for electrical supply of a sensor unit integrated on the rotating inner ring of a rolling bearing. This energy harvester is of special interest for condition monitoring tasks on rotating shafts. A sensory monitor on the inner ring can detect wear conditions at an early stage. The harvester works without mechanical and energetic contact to surrounding components by utilizing the rotational energy of the shaft. The functionality of the Energy Harvester is enabled by the inertia principle, which is caused by an asymmetrical mass distribution. We provide simulations to validate the designs. This work includes simulation studies on the electrical power output of the harvester. Therefore, the necessary simulation of the magnetic problems is realized in a substitute simulation environment. The harvester design enables existing machines to be equipped with the harvester to provide an energy supply on rotating shafts. This clamp connection enables shaft mounting independent of location without mechanical work on the shaft. With an electrical power of up to 163.6 m W, at 3600 rpm, the harvester is used as an energy supply, which enables sensor-based monitoring of slow wear processes. Full article

This paper proposes a deep deterministic policy gradient (DDPG) based nonlinear integral backstepping (NIB) in combination with model free control (MFC) for pitch angle control of variable speed wind turbine. In particular, the controller has been presented as a digital twin (DT) concept, which is an increasingly growing method in a variety of applications. In DDPG-NIB-MFC, the pitch angle is considered as the control input that depends on the optimal rotor speed, which is usually derived from effective wind speed. The system stability according to the Lyapunov theory can be achieved by the recursive nature of the backstepping theory and the integral action has been used to compensate for the steady-state error. Moreover, due to the nonlinear characteristics of wind turbines, the MFC aims to handle the un-modeled system dynamics and disturbances. The DDPG algorithm with actor-critic structure has been added in the proposed control structure to efficiently and adaptively tune the controller parameters embedded in the NIB controller. Under this effort, a digital twin of a presented controller is defined as a real-time and probabilistic model which is implemented on the digital signal processor (DSP) computing device. To ensure the performance of the proposed approach and output behavior of the system, software-in-loop (SIL) and hardware-in-loop (HIL) testing procedures have been considered. From the simulation and implementation outcomes, it can be concluded that the proposed backstepping controller based DDPG is more effective, robust, and adaptive than the backstepping and proportional-integral (PI) controllers optimized by particle swarm optimization (PSO) in the presence of uncertainties and disturbances. Full article

To remain competitive in the market, it is crucial to reduce the time and costs involved in product development. Design for manufacturing and assembly is an engineering methodology that can reduce costs without compromising reliability, performance and time to market objectives. This paper presents a case study for an in-market Table Top Chain (TTC) conveyor system used by a reputed company in Saudi Arabia. TTC conveyor systems are extensively used by major food companies around the world for transporting packaged bottles, glass and cans. There are three main types of these systems, i.e., straight running, side flexing and multiflex. This work focuses on the redesign of a side flexing TTC conveyor system. The existing design of the TTC conveyor system was analysed using the DFMA 9.3 software. The outcomes of the initial analysis were utilised to redesign the TTC conveyor system for cost and design efficiency improvements. The optimum design was selected using Pugh controlled convergence method and further tested for its structural performance using finite element analysis. The redesigned model showed substantial improvements with cost reductions of 29% and an increase in design efficiency from 1.7% to 5%. Finite element analysis has also been carried out with SolidWorks 2019 to validate the structural integrity of the new concept design. Full article

Computational fluid dynamics (CFD) can help in understanding the nature of leakage flow phenomena inside the rotary positive displacement machines (PDMs). However, due to the lack of experimental results, the analysis of leakage flows in rotary PDMs by CFD has not yet been fully validated. Particle image velocimetry (PIV) tests with a microscopic lens and phase-lock were conducted to obtain the velocity field around the tip gap in an optical Roots blower. The three-dimensional unsteady CFD model of the Roots blower with the dynamic grids generated by Screw Compressor Rotor Grid Generation (SCORG) was established to predict the gap flow under the same operating conditions. The images obtained by the PIV tests were analyzed and some factors which compromise the quality of test results in the gap flow were identified, such as reflections and transparency of the window. The flow fields obtained by CFD have the same flow pattern and velocity magnitude as the experimental results in the majority of observed regions but overestimate the leakage flow velocity. The CFD results show a vortex induced by the leakage flow in the downstream region of the gap. The flow losses in the tip gap mainly happen at the entrance upstream of the gap. Finally, some suggestions for future work are discussed. Full article