Designs, Volume 5, Issue 1 (March 2021) – 24 articles

The paper describes the design of a fuzzy motion control system of an autonomous underwater vehicle. A mathematical model of the underwater vehicle is synthesized. A fuzzy regulator for controlling the depth of immersion autonomous underwater vehicle is designed. The quality of control for step control, harmonic control, as well as various types of exogenous disturbances, is investigated. The comparison of the functioning quality of the designed fuzzy controller with the proportional–derivative controller is made. It is shown that the designed fuzzy controller provides a higher quality of control compared to the proportional–derivative controller. The proposed fuzzy controller provides high-quality control of the plant under uncertainties. 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

At global level nowadays, there is a general movement towards the goal of a ‘zero-emission’ energy systems. It will require a necessary energy transition characterized by a continuous increase of generation facilities from renewable energy sources (RES), from a massive increase in energy efficiency and, contemporary, an increased use of electricity to meet the energy needs traditionally required through the direct use of fossil fuels. In order to provide end-users with a greater knowledge and awareness of their energy consumption and the benefits of distributed use of renewable energy sources, it is fundamental to employ a smart metering progress which can enable an evolved and ‘smart’ management of the production–demand binomial and an active participation in the energy system. The importance of functionalities implemented in a smart meter—for end-user engagement, empowerment, and awareness—is presented in the paper. For instance, we present a simple optimization functionality for photovoltaic (PV) and storage system sizing based on load and production duration curves and historical data collected by the smart meter with fine resolution. The ease of this functionality uses a data history with extremely high resolutions, which are able to measure the power ramps that occur when an appliance or any other load is connected. An example of application of the smart meter functionality and test cases’ analysis are reported to demonstrate the effectiveness of the tool. Full article

In the present paper, an optimized design procedure capable of providing the geometry of a high efficiency compact hydraulic propeller turbine for low head is proposed and developed. The turbine preliminary design is based on fundamental turbomachinery mean-line equations and on the employment of statistical correlations, which relate the main geometrical parameters to the fundamental design parameters. The first obtained geometry represents the starting point of an automated aerodynamic single point optimization procedure based on a genetic algorithm generating and updating a wide database of turbine geometries. The approach employs a three-dimensional (3D) Reynolds averaged Navier–Stokes (RANS) solver for the construction of the corresponding database of performance. A meta-model, such as an artificial neural network (ANN), is used to speed up the design optimization process. The procedure has been applied on the practical case of a novel simplified hydraulic propeller turbine prototype for very low heads. The adopted design optimization procedure is able to modify the turbine blade and vane geometries in order to achieve automatically the targeted net head and the maximum for the total to total internal efficiency once diameter, mass flow rate, and rotational speed are assigned. Full article

This research aims to test the feasibility of a prototype of a newly designed thermal engine for a hybrid propulsion vehicle. This study consists of the implementation of an innovative supercharger for city car internal combustion engine ICE (900 cc). The preliminary proposal presented here is to mechanically disconnect the compressor/turbine device, supporting the rotation of the compressor with a dedicated electric motor and connecting a turbine to a generator. Mechanical decoupling will allow both machines to be designed for operating closer to their maximum performance point, for most of the expected real field of operation. Specifically, the turbine is likely to have a lower rotation speed than the original group and will, therefore, be slightly larger. The advantage is that, while in the current supercharger groups the surplus at high regimes is discharged through the waste-gate valve without expanding in a turbine, in the configuration proposed, all the energy of the combustible gases is used by the turbine to generate electrical power that can be used where required. Once the motorization of the vehicle (999 cc) has been fixed, the two turbomachines will have to be studied and designed, looking where possible, for commercial components. Finally, a computational fluid dynamic CFD will be needed to verify the validity of the choice, followed by careful experimentation campaigns. Full article

Over the last two decades, Doha, the capital city of Qatar, has undergone rapid urbanization. The city has capitalized large-scale urban and infrastructural projects resulting in a loss of historical areas of heritage value to people. Recent construction of the Doha Metro is opening avenues for place-making of transit towns through a framework envisioned by the need to shape compact, livable and sustainable neighborhoods and to mitigate the effects of urbanization on valuable historical heritage sites. Due to its historic significance, the Qatar National Museum (QNM)-Souq Waqif corridor is the case study selected for exploring and defining a framework for a contextualized place-making transit-oriented development (TOD) model. The research design is structured by reviewing the literature about TODs and the need for place-making model in Qatar, followed by collecting visual data from municipal authorities, through site visits, and site observations. The data are then analyzed to propose a novel masterplan, rooted in key urban design components of place-making. The insights will contribute to proposals for context-driven design strategies to enhance livability of the site and to extend its application to other potential transit hubs in metropolitan Doha and in the Middle East. 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

A turbo roundabout uses spiral circulatory roads for effectively counteracting the problems faced in modern multilane roundabouts. First developed in 1996, the turbo roundabout has an advantage over the conventional roundabout regarding capacity and safety. Turbo roundabouts are still in the developing phase in North America, but even in the European subcontinent where they exist in large numbers, reliable analytical studies on the critical parameters of roundabout visibility are lacking. Visibility (sight distance) helps to shape the geometry of the intersection and aids in safety. This paper presents the mathematical characteristics of the intersection geometry and intersection sight distance (ISD) of the turbo roundabout. Mathematical formulas are presented for the sight distance from the approaching vehicle to the conflicting-entering and circulating vehicles. The maximum lateral clearances to the conflicting vehicles are derived using mathematical optimization. The developed analytical method is verified graphically using AutoCAD. To assist in practical applications, design aids for the maximum lateral clearance are presented. The presented method and design aids should aid in promoting safety at turbo roundabouts. Full article

Digital Image Correlation (DIC) is a powerful tool used to evaluate displacements and deformations in a non-intrusive manner. By comparing two images, one from the undeformed reference states of the sample and the other from the deformed target state, the relative displacement between the two states is determined. DIC is well-known and often used for post-processing analysis of in-plane displacements and deformation of the specimen. Increasing the analysis speed to enable real-time DIC analysis will be beneficial and expand the scope of this method. Here we tested several combinations of the most common DIC methods in combination with different parallelization approaches in MATLAB and evaluated their performance to determine whether the real-time analysis is possible with these methods. The effects of computing with different hardware settings were also analyzed and discussed. We found that implementation problems can reduce the efficiency of a theoretically superior algorithm, such that it becomes practically slower than a sub-optimal algorithm. The Newton–Raphson algorithm in combination with a modified particle swarm algorithm in parallel image computation was found to be most effective. This is contrary to theory, suggesting that the inverse-compositional Gauss–Newton algorithm is superior. As expected, the brute force search algorithm is the least efficient method. We also found that the correct choice of parallelization tasks is critical in attaining improvements in computing speed. A poorly chosen parallelization approach with high parallel overhead leads to inferior performance. Finally, irrespective of the computing mode, the correct choice of combinations of integer-pixel and sub-pixel search algorithms is critical for efficient analysis. The real-time analysis using DIC will be difficult on computers with standard computing capabilities, even if parallelization is implemented, so the suggested solution would be to use graphics processing unit (GPU) acceleration. Full article

With the rising demand for electric vehicles (EVs), it is also becoming increasingly important for policymakers to devise measures on how best to handle spent EV batteries. Policymakers need to devise a system that ensures the economic efficiency of recycling used EV batteries, and support the effective operation of such a system with legal and policy measures. This study aims to present, in a systematic manner, the policy measures needed to foster an environment that actively makes use of spent EV batteries, based on a review of Korean practices and experiences. Based on in-depth interviews with experts, this study explains why the policy measures it recommends are essential, what obstacles stand in the way of implementing those measures and how we may overcome them, as well as other factors we should consider when implementing these measures. As a result, we identified top-priority policy tasks, such as defining regulatory provisions that apply to each stage using spent batteries, as well as clarifying the cost- and profit-sharing structure. We also explored potential and major obstacles and factors that may stand in the way of the implementation of recommended policy measures. Full article

Design science (DS) approaches have been emerging in engineering, management and other disciplines operating at the interface between design research and the natural or social sciences. Research informed by DS is challenging because it involves “mixing oil with water”, using a famous phrase of Herbert Simon. A key challenge here is the dual role of theory: one can develop a “theory of” any empirical phenomenon to explain its characteristics and outcomes, or alternatively, develop a “theory for” generating this phenomenon, focused on solving problems and enlarging possibilities. To clearly distinguish these two perspectives, we talk about theorizing in relation to theory-of and framing related to theory-for. A state-of-the-art review of how DS is applied by management researchers results in two main findings. First, explicit (re)framing efforts appear to be highly instrumental in challenging a given theoretical paradigm and thereby reduce the risk of being constrained to it; these findings confirm the generative nature of design activity. Moreover, many studies reviewed draw on knowledge formats that synthesize descriptive-explanatory and prescriptive-normative knowledge. Our main findings are subsequently integrated into a DS methodology, which may especially be of interest to design-oriented disciplines that tend to adopt a rather intuitive (undefined) notion of theory. Full article

The purpose of this paper is to propose a novel process failure mode and effect analysis (PFMEA) approach for the reliable design of assembly activities to prevent product defects due to errors during the assembly of complex products. PFMEA is approached as an integrated method that, in addition to implementing recommended actions, supports the design of worksheets, equipment, and layout of the assembly lines of complex systems, early in the design phase of the product. As a result, the innovative design-job element sheets (D-JESs), which report work instructions to the operator for assembly cycles, are defined before the design of the production and assembly process. The modification of the PFMEA structure, the implementation of proper recommended actions, and the designs of D-JESs, equipment, and assembly layout, early in the design phase of the product, are the novel contributions of the paper. The integrated method assures to effectively design the assembly process directly during the product design to avoid errors that could promote dissatisfaction of the end-users. It is practical to use and does not require large investments, implementation of new technologies, or complex additional training. Its practical application is demonstrated using a case study concerning a manufacturer of train wagons via manual assembly lines. Full article

This study discusses a general framework to identify the unsteady features of a flow past an oscillating aerofoil in deep dynamic stall conditions. In particular, the work aims at demonstrating the advantages for the design process of the Spectral Proper Orthogonal Decomposition in accurately producing reliable reduced models of CFD systems and comparing this technique with standard snapshot-based models. Reynolds-Averaged Navier-Stokes system of equations, coupled with $k-\omega$ SST turbulence model, is used to produce the dataset, the latter consisting of a two-dimensional NACA 0012 aerofoil in the pitching motion. Modal analysis is performed on both velocity and pressure fields showing that, for vectored values, a proper tuning of the filtering process allows for better results compared to snapshot formulations and extract highly correlated coherent flow structures otherwise undetected. Wider filters, in particular, produce enhanced coherence without affecting the typical frequency response of the coupled modes. Conversely, the pressure field decomposition is drastically affected by the windowing properties. In conclusion, the low-order spectral reconstruction of the pressure field allows for an excellent prediction of aerodynamic loads. Moreover, the analysis shows that snapshot-based models better perform on the CFD values during the pitching cycle, while spectral-based methods better fit the loads’ fluctuations. Full article

Traditional timber houses in tropics have specific environmental characteristics that evolved considering material constraints, local construction technology and climate. To provide occupants with the necessary comfort, these naturally ventilated houses adopted several passive design strategies. Moreover, occupants have unique living patterns which may have contributed towards achieving indoor thermal comfort. However, scientific knowledge regarding these issues is still limited. Therefore, considering traditional timber houses of Bangladesh as sample cases, this study aims to investigate existing relationship between an indoor thermal environment and an occupant’s living pattern within these tropical houses. Physical measurement of thermal parameters and questionnaire surveys followed by personal observations were conducted. Findings show that indoor air temperature (AT °C) fluctuates readily with that outdoors without a timelag resulting in daytime overheating. The occupant’s daytime thermal sensation is mostly slightly warm to hot. Semi-open and outdoor shaded spaces become a way to cope with the daytime overheating period. Occupants frequently use indoor spaces during the night when thermal sensation ranges between neutral to slightly cool. Finally, from the findings an interpretational graph has been developed relating indoor thermal environment with occupant’s living pattern within a traditional timber house. Findings will contribute to professionals and policy-makers developing architectural design strategies that may impact the occupant’s well-being in future. Full article

The use of machine-learning techniques is becoming more and more frequent in solving all those problems where it is difficult to rationally interpret the process of interest. Intrusion detection in networked systems is a problem in which, although it is not fundamental to interpret the measures that one is able to obtain from a process, it is important to obtain an answer from a classification algorithm if the network traffic is characterized by anomalies (and hence, there is a high probability of an intrusion) or not. Due to the increased adoption of SW-defined autonomous systems that are distributed and interconnected, the probability of a cyber attack is increased, as well as its consequence in terms of system reliability, availability, and even safety. In this work, we present the application of different machine-learning models to the problem of anomaly classification in the context of local area network (LAN) traffic analysis. In particular, we present the application of a K-nearest neighbors (KNN) and of an artificial neural network (ANN) to realize an algorithm for intrusion detection systems (IDS). The dataset used in this work is representative of the communication traffic in common LAN networks in military application in particular typical US Air Force LAN. This work presents a training phase of the different models based on a multidimensional-scaling preprocessing procedure, based on different metrics, to provide higher performance and generalization with respect to model prediction capability. The obtained results of KNN and ANN classifiers are compared with respect to a commonly used index of performance for classifiers evaluation. Full article

Photography can be used for pleasure and art but can also be used in many disciplines of science, because it captures the details of the moment and can serve as a proving tool due to the information it preserves. During the period of the Apollo program (1969 to 1972), the National Aeronautics and Space Administration (NASA) successfully landed humans on the Moon and showed hundreds of photos to the world presenting the travel and landings. This paper uses computer simulations and geometry to examine the authenticity of one such photo, namely Apollo 17 photo GPN-2000-00113. In addition, a novel approach is employed by creating an experimental scene to illustrate details and provide measurements. The crucial factors on which the geometrical analysis relies are locked in the photograph and are: (a) the apparent position of the Earth relative to the illustrated flag and (b) the point to which the shadow of the astronaut taking the photo reaches, in relation to the flagpole. The analysis and experimental data show geometrical and time mismatches, proving that the photo is a composite. Full article

The district heating (DH) industry has been characterized by continuous innovation for several decades, but there is limited knowledge on the characteristics of the sector’s innovation activities, arguably the most important information for understanding how the sector can continue to develop and further support the energy transition of society. We perform a systematic literature review (SLR) to identify the types of innovation, the levels of innovation and the relation between different innovations in the DH sector. A total of 899 articles are analyzed and coded into eight groups: fuel, supply, distribution, transfer, DH system, city system, impact and business. Most of the articles (68%) were identified in the groups: “supply”, “DH system,” and “impact”, with a focus on DH from a system or production perspective and its environmental impact. We find that there is limited research on DH firms” challenges, including management perspectives, such as asset management and customer focus. Despite this potential, we find only a limited number of articles related to innovation. Not much scholarly attention has been given to areas of large cost-saving, especially capital cost. Full article

In every business, the production of knowledge, coming from the process of effective information, is recognized as a strategic asset and source of competitive advantage. In the field of railways, a vast amount of data are produced, which is necessary to be assessed, deployed in an optimum way, and used as a mechanism, which will lead to making the right decisions, aiming at saving resources and maintain the fundamental principle of the railways which is the passengers’ safety. This paper uses stored-inactive data from a Greek railway company, and uses the method of data mining and applies machine learning techniques to create strategic decision support and draw up a risk and control plan for trains. We make an effort to apply Machine Learning open source software (Weka) to the obsolete procedures of maintenance of the rolling stock of the company (hand-written work orders from the supervisors to the technicians, dealing with the dysfunctions of a train unit by experience, the lack of planning and coding of the malfunctions and the maintenance schedule). Using the J48 and M5P algorithms from the Weka software, data are recorded, processed, and analyzed that can help monitor or discover, with great accuracy, the prevention of possible damage or stresses, without the addition of new recording devices—monitoring on trains, with the aim of predicting the diagnosis of the train fleet. The innovative method is capable of being used as a tool for the optimization of the management’s performance of the trains to provide the appropriate information for the implementation of planning and the technical ability of the trains in order to achieve the greatest target of importance for the railways, which is the passengers’ safety. Full article

Microbubble generators are of considerable importance to a range of scientific fields from use in aquaculture and engineering to medical applications. This is due to the fact the amount of sea life in the water is proportional to the amount of oxygen in it. In this paper, experimental measurements and computational Fluid Dynamics (CFD) simulation are performed for three water flow rates and three with three different air flow rates. The experimental data presented in the paper are used to validate the CFD model. Then, the CFD model is used to study the effect of diverging angle and throat length/throat diameter ratio on the size of the microbubble produced by the Venturi-type microbubble generator. The experimental results showed that increasing water flow rate and reducing the air flow rate produces smaller microbubbles. The prediction from the CFD results indicated that throat length/throat diameter ratio and diffuser divergent angle have a small effect on bubble diameter distribution and average bubble diameter for the range of the throat water velocities used in this study. Full article

In a deregulated market, energy can be exchanged like a commodity and the market agents including generators, distributors, and the end consumers can trade energy independently settling the price, volume, and the supply terms. Bilateral contracts (BCs) have been applied to hedge against price volatility in the electricity spot market. This work introduces a model to find all solutions for the equilibria implementing the Raiffa–Kalai–Smorodinski (RKS) and the Nash Bargaining Solution (NBS) approaches in an electricity market based on BCs. It is based on creating “holes” around an existing equilibrium within the feasibility set, yielding a new (smaller) feasibility set at each iteration. This research has two players: a generation company (GC) and an electricity supplier company (ESC), aiming to achieve the highest profit for each of them. The results present all possible RKS and NBS, in addition to showing all assigned energies for a case study at different time frames. The multiple equilibria solutions allow the ESC and the GC to apply different strategies knowing that they can still achieve an optimal solution. 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

The article presents an analysis of the intellectual property market in the field of enhanced oil recovery (EOR) methods. The search retrospectively covers the period from 2010 to 2020. Russia, China, and the United States are the leading countries in enhanced oil recovery methods. Canada, Germany, and Saudi Arabia also have a high level of patent activity compared with other countries. Semantic and statistical analysis of the obtained sample of documents made it possible to highlight the areas of intensive patenting, high competitiveness, as well as mainstream methods of enhanced oil recovery. The analysis of the leading companies’ patent portfolios revealed the similarities and differences in their structure. Tatneft, ConocoPhillips Co., Sinopec, and PetroChina Co. are actively patenting in the field of thermal enhanced oil recovery, which has been identified as the mainstream. BASF SE is focused on the production of chemicals, including chemicals for oil production. The Saudi Arabian Oil Company produces light oil using waterflooding and physicochemical methods. Software dominates the patent collection sector in the EORs of Gazpromneft STC and Lukoil. Full article