Inventions, Volume 5, Issue 3 (September 2020) – 27 articles

In this proposed research, clear prospects of a real life marketing scenario, by analyzing a price discount policy and variable demand, are derived. The proposed study presents a production model along with time-dependent and selling price related demand for decaying items. Items deteriorate over time, therefore, considering deterioration in this model makes it more acceptable to the present marketing situation. The concept of delay-in-payments is utilized in this inventory system. In this research, a retailer buys some products, enjoys constant credit-period offers which are provided by the supplier. This model depicts a price discount strategy which is based on purchasing cost to attract more consumers in any business industry. By using this strategy, any manufacturer or business may gain more profit in comparison to methods suggested by earlier literature. The average profit function of the inventory system is maximized analytically and also finds the selling-price per unit and duration of the inventory cycle optimally. A numerical example, along with a case study and their graphical representations, are incorporated to verify the optimality of this research very clearly. The findings of this research have maximized the average profit function more than the existing literature. Full article

Human action recognition has turned into one of the most attractive and demanding fields of research in computer vision and pattern recognition for facilitating easy, smart, and comfortable ways of human-machine interaction. With the witnessing of massive improvements to research in recent years, several methods have been suggested for the discrimination of different types of human actions using color, depth, inertial, and skeleton information. Despite having several action identification methods using different modalities, classifying human actions using skeleton joints information in 3-dimensional space is still a challenging problem. In this paper, we conceive an efficacious method for action recognition using 3D skeleton data. First, large-scale 3D skeleton joints information was analyzed and accomplished some meaningful pre-processing. Then, a simple straight-forward deep convolutional neural network (DCNN) was designed for the classification of the desired actions in order to evaluate the effectiveness and embonpoint of the proposed system. We also conducted prior DCNN models such as ResNet18 and MobileNetV2, which outperform existing systems using human skeleton joints information. Full article

In the present scenario for the development of the unmanned aerial vehicle (UAV), artificial intelligence plays an important role in path planning and obstacle detection. Due to different environments, it is always a task to achieve the proper moment for achieving the target goal while avoiding obstacles with minimum human interference. To achieve the goal with the avoidance of obstacles, individual optimization techniques with metaheuristic algorithms such as fuzzy, particle swarm optimization (PSO), etc. were implemented in various configurations. However, the optimal solution was not attained. Thus, in order to achieve an optimal solution, a hybrid model was developed by using the firefly algorithm and the fuzzy algorithm, establishing multiple features of the individual controller. The path and time optimization were achieved by a standalone controller and a hybrid firefly–fuzzy controller in different conditions, whereby the results of the controller were validated by simulation and experimental results, highlighting the advantages of the hybrid controller over the single controller. Full article

The boiling process is utterly fundamental to the design and safety of water-cooled fission reactors. Both boiling water reactors and pressurised water reactors use boiling under high-pressure subcooled liquid flow conditions to achieve high surface heat fluxes required for their operation. Liquid water is an excellent coolant, which is why water-cooled reactors can have such small sizes and high-power densities, yet also have relatively low component temperatures. Steam is in contrast a very poor coolant. A good understanding of how liquid water coolant turns into steam is correspondingly vital. This need is particularly pressing because heat transfer by water when it is only partially steam (‘nucleate boiling’ regime) is particularly effective, providing a great incentive to operate a plant in this regime. Computational modelling of boiling, using computational fluid dynamics (CFD) simulation at the ‘component scale’ typical of nuclear subchannel analysis and at the scale of the single bubbles, is a core activity of current nuclear thermal hydraulics research. This paper gives an overview of recent literature on computational modelling of boiling. The knowledge and capabilities embodied in the surveyed literature entail theoretical, experimental and modelling work, and enabled the scientific community to improve its current understanding of the fundamental heat transfer phenomena in boiling fluids and to develop more accurate tools for the prediction of two-phase cooling in nuclear systems. Data and insights gathered on the fundamental heat transfer processes associated with the behaviour of single bubbles enabled us to develop and apply more capable modelling tools for engineering simulation and to obtain reliable estimates of the heat transfer rates associated with the growth and departure of steam bubbles from heated surfaces. While results so far are promising, much work is still needed in terms of development of fundamental understanding of the physical processes and application of improved modelling capabilities to industrially relevant flows. Full article

This paper synthesizes the design of an infeed cylindrical grinding system into a total system composed of the grinding mechanism and the grinding machine characteristics. The causalities between the grinding parameters and the machine structures are discussed, and the infeed grinding processes are analyzed as outputs that represent responses to the inputs. These relationships are integrated into a block diagram with closed-loop feedback. A novel model exhibiting practical parameters such as grinding speed, infeed rate and MRR (Material Removal Rate) is proposed. The analysis of the grinding system derived a critical factor, the “grinding time contact,” which governs the transient behaviors of process parameters such as forces and machine deflection. The process parameters during the infeed cycle including spark-out grinding were investigated, and the formulas required for the cycle design are presented. Furthermore, to improve accuracy and productivity, the features of the cycle design are described and procedures for controlling size error and roundness are discussed. Finally, the model was verified with infeed grinding tests applied to both the chuck-type cylindrical and centerless grinding methods. Full article

This work explains the cooling capabilities of ethylene glycol (EG)-based nanofluid containing aluminum oxide (Al₂O₃) as nanoparticles. Because of its enhanced thermophysical properties, Nanofluids are used in many application areas of mechanical and engineering in the form of nanofluid coolants such as electronics and vehicle cooling, transformer, and computer cooling. Depending on the heating and cooling systems, it is also used as an anti-freezing agent, which lowers the freezing point but enhances boiling point and temperature coolant. After using appropriate similarity transformation, the present Koo–Kleinstreuer–Li model for solving the boundary value problem (BVP) is tackled analytically. A comparison is made with a purely analytical approach by a modified version of the semi-analytical Adomian Decomposition Method (ADM), which is introduced by Duan and Rach (Duan–Rach Approach) and shooting technique. Analytical and graphical treatment of the flow regime is carried out, and the behavior of the leading parameters on the velocity, temperature, concentration profile with the behavior of physical quantities i.e., skin friction coefficient, local Nusselt number, and local Sherwood number are illustrated. This study confirms that, due to extraction in width the flow moves away from the lower plate whereas it moves towards near the upper plate and a rapid decrease in temperature is marked when alumina–EG nanofluids are taken into account. Full article

Metal additive manufacturing (AM) has gained much attention in recent years due to its advantages including geometric freedom and design complexity, appropriate for a wide range of potential industrial applications. However, conventional metal AM methods have high-cost barriers due to the initial cost of the capital equipment, support, and maintenance, etc. This study presents a low-cost metal material extrusion technology as a prospective alternative to the production of metallic parts in additive manufacturing. The filaments used consist of copper, bronze, stainless steel, high carbon iron, and aluminum powders in a polylactic acid matrix. Using the proposed fabrication technology, test specimens were built by extruding metal/polymer composite filaments, which were then sintered in an open-air furnace to produce solid metallic parts. In this research, the mechanical and thermal properties of the built parts are examined using tensile tests, thermogravimetric, thermomechanical and microstructural analysis. Full article

Crude oil is the world’s leading fuel source and is the lifeblood of the industrialized nations as it is vital to produce many everyday essentials. This dependency on fossil fuels has resulted in serious environmental issues in recent times. Petroleum contaminated soils must be treated to ensure that human health and the environment remain protected. The restoration of petroleum-polluted soil is a complex project because once petroleum hydrocarbon enters the environment, the individual constituents will partition to various environmental compartments in accordance with their own physical–chemical properties; therefore, the composition and inherent biodegradability of the petroleum hydrocarbon pollutant determines the suitability of a remediation approach. The objective of this study was to assess the prospective of bioremediation as a feasible technique for practical application to the treatment of petroleum hydrocarbon-contaminated soils, by trending the changes in the properties of the petroleum due to biodegradation. Each polluted soil has particularities, thus, the bioremediation approach for each contaminated site is unique. Therefore, hydrocarbon-contaminated sites that have remained polluted for decades due to lack of proper decontamination treatments present in this part of the world would benefit from cost effective treatments. Most bioremediation case studies are usually based on hypothetical assumptions rather than technical or experimental data; providing data that show the capabilities of biodegradation of indigenous microbes on specific oil composition can lead to the creation of strategies to accelerate the biological breakdown of hydrocarbons in soil. Full article

The shift from centralized to distributed generation and the need to address energy shortage and achieve the sustainability goals are among the important factors that drive increasing interests of governments, planners, and other relevant stakeholders in microgrid systems. Apart from the distributed renewable energy resources, fuel cells (FCs) are a clean, pollution-free, highly efficient, flexible, and promising energy resource for microgrid applications that need more attention in research and development terms. Furthermore, they can offer continuous operation and do not require recharging. This paper examines the exciting potential of FCs and their utilization in microgrid systems. It presents a comprehensive review of FCs, with emphasis on the developmental status of the different technologies, comparison of operational characteristics, and the prevailing techno-economic barriers to their progress and the future outlook. Furthermore, particular attention is paid to the applications of the FC technologies in microgrid systems such as grid-integrated, grid-parallel, stand-alone, backup or emergency power, and direct current systems, including the FC control mechanisms and hybrid designs, and the technical challenges faced when employing FCs in microgrids based on recent developments. Microgrids can help to strengthen the existing power grid and are also suitable for mitigating the problem of energy poverty in remote locations. The paper is expected to provide useful insights into advancing research and developments in clean energy generation through microgrid systems based on FCs. Full article

Recurring and increasing large-scale wildfires across the globe (e.g., Southern Europe, California, Australia), as a result of worsening climate conditions with record temperatures, drought, and strong winds, present a challenge to mankind. Early fire detection is crucial for a quick reaction and effective firefighting operations, minimizing the risk to human lives as well as the destruction of assets, infrastructures, forests, and wildlife. Usually, ground firefighting relies on human intervention and dangerous exposition to high temperatures and radiation levels, proving the need for mechanisms and techniques to remotely or autonomously detect and combat fire. This paper proposes an autonomous firefighting system built with a motorized water turret, narrow beam far infrared (FIR) sensors, and a micro-controller running novel algorithms and techniques. Experimental field results validated the technical approach, indicating that when a small fire front is within the field of view of the FIR sensor and within the range of the water jet, it is possible to provide an early alarm and even autonomously extinguish or delay the approaching fire front, increasing the chance for evacuation. Full article

Scientists and researchers are exploring different methods of generating and delivering electrical energy in an economical and reliable way, enabling them to generate electricity focusing on renewable energy resources. All of these possess the natural property of self-changing behavior, so the connection of these separate independent controllable units to the grid leads to uncertainties. This creates an imbalance in active power and reactive power. In order to control the active and reactive power in wind turbine generators with adjustable speed, various control strategies are used to allay voltage and current variations. This research work is focused on the design and implementation of effective control strategies for doubly fed induction generator (DFIG) to control its active and reactive power. A DFIG system with its control strategies is simulated on MATLAB software. To augment the transient stability of DFIG, the simulation results for the active and reactive power of conventional controllers are compared with three types of feed forward neural network controllers, i.e., probabilistic feedforward neural network (PFFNN), multi-layer perceptron feedforward neural network (MLPFFN) and radial basic function feedforward neural network (RBFFN) for optimum performance. Conclusive outcomes clearly manifest the superior robustness of the RBFNN controller over other controllers in terms of rise time, settling time and overshoot value. Full article

Owing to the expensive applications of nanoparticles in engineering sciences, an admirable attention has been intended by researchers on this topic in recent years. The utilization of nanoparticles as asource of energy is intended much attention of investigators in recent decade. This novel attempt investigates the thermal properties of Casson nanofluid containing microorganisms induced by an oscillatory moving surface. The fundamental features of heat and mass phenomenon are inspected by utilizing the temperature-dependent viscosity. Buongiorno’s mathematical model is used to report the famous Brownian motion and thermophoretic diffusion consequences. The flow problem characterizes the partial differential equations for which analytical solution has been computed with a convincible accuracy. The insight physical features are inspected with help of various curves. The physical significances of flow parameters is studied via various graphs. Full article

Decreasing the share of time for the technological training of new product creation is an actual and perspective task. The actuality of the given task always increases with the development of machine-building production. Changes which happen inside the organization of industrial production are connected to the development of consumer demand. Modern tendencies are such that there can be seen a constant lowering of batch products with an increase in the range of their production, and, consequently, a reduction in the production stage of the product life cycle. Under these conditions, it is necessary to react as quickly as possible to changes of external (for example, the arrival of new production orders, adjusting the number of already started production, etc.) and internal conditions (for example, stopping technological equipment for organizational reasons, correcting production routes for parts, etc.). Obviously, the effectiveness of the functioning of the production system will be determined primarily by the right decisions. Errors lead to large material costs and a serious loss of time, which can be fatal for an enterprise. The development goal described in the article is to build a digital model of a production system that allows—on a machine time scale and in the absence of material costs—the analysis of various control scenarios and finding correct solutions in in short time. The methodological basis for constructing such models is the use of simulation modeling with the combination of discrete event and agent modeling. The construction of a model on this principle allows its openness to accumulate information about successful decisions made and use them to solve similar problems in the future. The benefit of this approach is the ability to predict the production situation over time, rational distribution of technological resources, reducing equipment downtime, streamlining the routes of production tasks and determining the stages of acquiring the necessary materials and components. It increases the competitiveness of the enterprise and ensures its economic stability. Full article

This paper presents secondary voltage control by extracting reactive power from renewable power technologies to control load buses voltage in a power system at different operating conditions. The study is performed on a 100% renewable 14-bus system. Active and reactive powers controls are considered based on grid codes of countries with high penetration levels of renewable energy technologies. A pilot bus is selected in order to implement the secondary voltage control. The selection is based on short-circuit calculation and sensitivity analysis. An optimal Proportional Integral Derivative (PID) voltage controller is designed using genetic algorithm. A comparison between system with and without secondary voltage control is presented in terms of voltage profile and total power losses. The optimal voltage magnitudes at busbars are calculated to achieve minimum power losses using optimal power flow. The optimal placement of Phasor Measurement Units (PMUs) is performed in order to measure the voltage magnitude of buses with minimum cost. Optimization and simulation processes are performed using DIgSILENT and MATLAB software applications. Full article

This work presents the production of sewage sludge oil by pyrolysis, shows the physicochemical properties and compares it with commercial diesel. The sewage sludge was dried and mixed to discarded cooking oil to increase the fuel conversion rate due to the pyrolysis process at an initial temperature of 25 °C and a final of 650 °C. The oil was distilled and analyzed in a Proton nuclear magnetic resonance (1H-NMR), Gas Chromatogram and Mass spectrometry (GC-MS), thermogravimetric analysis (TGA) and Fourier transform infrared spectroscopy (FTIR) to perform a structural characterization on the molecular distribution, groups of functions and the product thermal stability. The authors measured fundamental physicochemical properties like viscosity, density and flashpoint and compared the results with the corresponding commercial S-10 diesel properties observing good agreement. Full article

Currently, the privileged position of wind energy producers is being weakened by their enforced participation in the market on equal terms. This requires accurate production forecasting. The main aim of this study is to comparatively examine the wind generation forecasts in Poland and Portugal, as well as to verify their influence on the day-ahead market prices. The statistical analysis revealed significant deviations of the forecasted and actual wind production in both countries, which referred to the corresponding spot and balancing prices caused considerable financial losses by the wind energy suppliers. In this paper, the influence of the wind generation forecasts on the spot prices has been examined through developed the auto-regressive moving average (ARMA), ARMA with exogenous inputs (ARMAX) and non-linear auto-regressive neural network (NAR), NAR with exogenous inputs (NARX)artificial neural network (ANN) models. The results have shown that the usability of the information of forecasted wind generation is not unequivocal in models developed for spot prices in Poland, mainly because of the randomness and volatility of recorded wind generation forecasts. However, in the case of Portugal, the forecasted wind generation occurred to be a valuable input in spot prices models, which results in an improvement in the models’ accuracy. Full article

Demand-Side Generating Assets (DSGAs) relate to existing small diesel Gensets serving the critical loads of infrastructures in unexpected electrical network interruptions. This paper investigates the exploitation of DSGA as potential suppliers of ancillary services (AS), especially in the case of isolated or weak interconnected island power systems such as in Crete. In this regard, their impact on substations’ loading reductions and associated copper losses is presented, using a substation as a case study with a typical touristic load in Crete. DSGA’s impact on such a significant part of reliability enhancement in distribution systems is evaluated, examining different scenarios of DSGA installed capacity. Subsequently, extensive research is carried out regarding the cost analysis for their access to the electrical grid providing AS, in combination with their operating cost analysis. The calculations on fuel consumption cost show that DSGA are comparable with the most expensive gas turbines of the Cretan power system. Finally, considering the capital cost for their required configurations and their fuel consumption cost, a proposal for their remuneration prices is made. The prices that arise are lower than the actual remuneration prices of other similar services such as Genset rentals for the case of the Cretan power system. Full article

This study analyzes transient turbulent modeling of three-dimensional multiple dimpled fin array using large eddy simulation (LES). The Navier–Stokes equations as well as the energy equation were constructed by the finite volume method and then discretized to form algebraic equations, which were solved by semi-implicit method for pressure-linked equation (SIMPLE). The solutions of temperature and velocity were obtained by iterating computation until it converged within each step. This simulation places nine fins on the bottom surface of a channel and changes the height of the dimple (0.4, 0.8, and 1.2 mm) with three different levels of Reynolds number (Re) (3500, 5000, and 6500) to investigate the temperature and flow field without gravity in forced convection. The results indicate that the dimpled fin array can generate vortices between the convex/concave dimples and the fin base and increase the influences of the height of the dimple on the flow field around the fin array. The averaged time-mean of the Nusselt number (Nu) for the dimple height of 0.8 mm is higher than that of the no-dimple case up to 14.4%, while the averaged time-mean Nu for the dimple height of 1.2 mm is lower than that of the no-dimple case up to 11.6%. Full article

This concept paper describes a device consisting of a disinfectant wristband for the hands of the wearer and objects that the wearer intends to touch. This wristband can be powered automatically by the movement of the user’s hand or by solar cells or, if necessary, by a power outlet. It disinfects the surface of the hands and the objects in front of them using an ultraviolet (UV) lamp. Control and monitoring can be carried out automatically or manually, which guarantees complete and effective disinfection. The electronic control system, which is fully integrated into the UV emitter head, regulates the intensity and duration of the UV radiation and also manages the electrical energy. In addition, the wristband can be fitted with an optional watch to improve its decoration and ergonomics. The device in question has a compact, elegant, and practical shape. This hand sanitizing wristband can be an effective tool in the fight against the current COVID-19 pandemic and, in general, help to address the health challenges related to hygiene and disease prevention. Full article

This paper presents a topology of a multi-port phase shift converter for integration with a photovoltaic (PV) system, a wind turbine generator, and a battery to supply a grid-connected domestic load. The main advantage of the topology is using a multi-winding high-frequency transformer (MWHFT) to integrate the input and outputs of the system. In contrast with the case of using a common electrical bus, using MWHFT presents several advantages, such as isolating the converter ports, the easier matching of different voltage levels of the converter ports by adjusting turns ratio, simpler power flow control between the converter ports by applying leading or lagging phase shift angles, and eliminating the leakage current flow through the PV panels from the utility grid. A detailed analysis of the proposed topology and the control system is presented. A numerical simulation of the proposed system is carried out to confirm the system operation and control technique. The experimental tests have been conducted on a prototype converter to approve the proposed system performance. Full article

In this work, a structured design method, the Stylistic Design Engineering (SDE), is applied for the construction of a new minivan car, in particular a new city car, which we will call FIAT 600 Omega. The SDE, or Stylistic Design Engineering, is a structured engineering method for carrying out automotive design projects. The SDE method consists of six different phases: (1) Analysis of stylistic trends; (2) Sketches; (3) 2D Computer Aided Design (CAD) drawings; (4) 3D CAD models; (5) Rendering; (6) Solid stylistic model (also called style maquette). This project deals with the external redesign of the Fiat 600 multiple, a small minivan which was very successful in the 1950s and 1960s. SDE is a methodology consisting of various technologies and design methodologies that will be further explained in detail, such as the Pininfarina method, the Quality Function Deployment (QFD) method, Benchmarking (BM), and Top Flop Analysis (TPA). The work was organized according to the different phases. Initially, the Fiat style was studied, in particular the style of the FIAT 600 MULTI PURPOUSE VEHICLE (MPV). This step is essential to better understand the characteristics of the brand and also the main characteristics carried out over the decades. Then we moved on to the freehand sketching phase, based on what we learned in the previous phase of the study. When a satisfactory shape was found for the new car, by analyzing and discarding the different proposals of the various types of style, we proceeded to the evaluation of the proportions and dimensions through two-dimensional drawings and finally we obtained the three-dimensional shape of the new car thanks to 3D CAD software and rendering software. Many advantages in the industrial world SDE takes together with its development. In fact, until the early 2000s, car design and styling was considered quite a craft activity, not a technical or scientific one, mostly based on the great capability of famous car designers and masters, just like Giugiaro, Zagato, Bertone, Pininfarina, Stephenson, Bangle, etc. Then, thanks to the industrial activity of Eng. Lorenzo Ramacciotti, former CEO of Pininfarina Spa and Mechanical Engineer, and also thanks to the academic studies developed at ALMA MATER STUDIORUM University of Bologna, SDE became the object of attention, because it is able to systematize the car design process and reduce costs. With SDE, a good design research or an industrial product development team can complete a car design project, also without the presence of a mentor. Car Design Process finally becomes with SDE a scientific method; Car Design becomes with SDE an industrial method. Industrial needs are nice products made in a short time; SDE is structured to attend these issues. Industrial challenges follow innovation, in shape and functionality; SDE is able to recognize innovation. Industrial benefits can be reached with SDE, ensuring beautiful aesthetic projects are realized systematically and with low costs. Full article

This paper developed a multi-nozzle pneumatic extrusion-based additive manufacturing (AM) system and applied it to print multi-material polymers and conductive sensing pads. We used pneumatic extrusion nozzles to extrude the liquid material and then cured it by an ultraviolet (UV) light source. The multi-nozzle pneumatic extrusion-based additive manufacturing system mainly integrates both PC-based HMI and CNC controller to operate the three-axis motion and the extrusion flow control. Moreover, the peripheral I/Os include both positive and negative pressure and also the curing light source. A D/A controller is also applied to control the value of the pneumatic pressure. The coding part utilizes the numerical control software along with the PLC planning to operate the AM machine automatically. Our experiment is conducted by using Simplify3D, a commercial 3D printing slicing software. Different requirements were set for extrusion nozzles with different materials, and then we executed the path controlling G-code data by Python Language. Our system successfully prints multi-material polymer structure pads which include the hard and soft material pad fabricated in double-layers, triple-layers and also the grid structure. Finally, we find that the printed pad has conductivity. Full article

Methane, the primary component of natural gas, is a significant contributor to global warming and climate change. It is a harmful greenhouse gas with an impact 28 times greater than carbon dioxide over a 100-year period. Preventing methane leakage from transmission pipelines and other oil and gas production activities is a possible solution to reduce methane emissions. In order to detect and resolve methane leaks, reliable and cost-effective sensors need to be researched and developed. This paper provides a comprehensive review of different types of methane detection sensors, including optical sensors, calorimetric sensors, pyroelectric sensors, semiconducting oxide sensors, and electrochemical sensors. The discussed material includes the definitions, mechanisms and recent developments of these sensors. A comparison between different methods, highlighting the advantages and disadvantages of each, is also presented to help address future research needs. Full article

Fluctuations in fossil fuel prices significantly affect the economies of countries, especially oil-importing countries, hence these countries are thoroughly investigating the increase in the utilization of renewable energy resources as it is abundant and locally available in all the countries despite challenges. Renewable energy systems (RES) such as solar and wind systems offer suitable alternatives for fossil fuels and could ensure the energy security of countries in a feasible way. Zimbabwe is one of the African countries that import a significant portion of its energy needs which endanger the energy security of the country. Several studies in the literature discussed the feasibility of different standalone and hybrid RES either with or without energy storage systems to either maximize the technical feasibility or the economic feasibility; however, none of the studies considered maximizing both feasibilities at the same time. Therefore, we present a techno-economic comparison of standalone wind and solar photovoltaic (PV) in addition to hybrid PV/wind systems based on maximizing the RES fraction with levelized cost of electricity (LCOE) being less than or equal to the local grid tariff where Gwanda, Zimbabwe, is the case study. The methodology suggested in this study could increase the utilization of renewable energy resources feasibly and at the same time increase the energy security of the country by decreasing dependency on imported energy. The results indicate that the PV/wind hybrid system does not only have the best economic benefits represented by the net present value (NPV) and the payback period (PBP), but also the best technical performance; where the maximum feasible size of the hybrid system-2 MW wind and 1 MW PV-has RES fraction of 65.07%, LCOE of 0.1 USD/kWh, PBP of 3.94 years, internal rate of return of 14.04% and NPV of 3.06 × 10⁶ USD. Having similar systems for different cities in Zimbabwe will decrease the energy bill significantly and contribute toward the energy security of the country. Full article

Some of the most promising distributed recycling and additive manufacturing (DRAM) technical systems use fused particle fabrication (FPF) or fused granular fabrication (FGF), where compression screws force post-consumer waste plastic through a heated nozzle for direct 3D printing. To assist the technical evolution of these systems, this study provided the details of an invention for a low-cost, easily replicable open-source grinding machine for compression screw manufacturing. The system itself can be largely fabricated using FPF/FGF following the self-replicating rapid prototyper (RepRap) methodology. This grinding machine can be made from a cordless cut-off grinder and < $155 in parts. The new invention is demonstrated to be able to cut custom screws with variable (i) channel depths, (ii) screw diameters, (iii) screw lengths, (iv) pitches, (v) abrasive disk thicknesses, (vi) handedness of the screws, (vii) and materials (three types of steel tested: 1045 steel, 1144 steel, and 416 stainless steel). The results show that the device is more than capable of replicating commercial screws as well as providing makers with a much greater flexibility to make custom screws. This invention enables the DRAM toolchain to become even more self-sufficient, which assists the goals of the circular economy. Full article

Additive manufacturing (AM) is evolving rapidly and this trend is creating a number of growth opportunities for several industries. Recent studies on AM have focused mainly on developing new machines and materials, with only a limited number of studies on the troubleshooting, maintenance, and problem-solving aspects of AM processes. Deep learning (DL) is an emerging machine learning (ML) type that has widely been used in several research studies. This research team believes that applying DL can help make AM processes smoother and make AM-printed objects more accurate. In this research, a new DL application is developed and implemented to minimize the material consumption of a failed print. The material used in this research is polylactic acid (PLA) and the DL method is the convolutional neural network (CNN). This study reports the nature of this newly developed DL application and the relationships between various algorithm parameters and the accuracy of the algorithm. Full article

In a growing number of battery-driven applications the need of removing any position and speed transducer is taking over due to space, cost and mechanical reliability constraints, further than making the installation easier as requiring less wiring. This paper presents the development of a sensorless algorithm capable of running an Interior Permanent Magnet Synchronous Machine (IPMSM), assuring constant torque production in the whole speed range, form standstill to high speeds. This is achieved with an hybrid method: at standstill and very low speeds the saliency of the IPM is exploited through an High Frequency Signal Injection (HFSI), which assures a robust estimation of the rotor position. At medium to high speeds an advanced V-I estimator is adopted in order to enhance the motor performances. The developed algorithm comes out of being highly scalable as it requires very little tuning, resulting in a multi-purpose application which can be employed with any motor size. Full article