Technologies

12 pages, 12160 KiB

Open AccessArticle

Tool Wear Characteristics and Strengthening Method of the Disc Cutter for Nomex Honeycomb Composites Machining with Ultrasonic Assistance

by Huiting Zha, Wenjun Shang, Jie Xu, Feng Feng, Hongyun Kong, Enlai Jiang, Yuan Ma, Chao Xu and Pingfa Feng

Technologies 2022, 10(6), 132; https://doi.org/10.3390/technologies10060132 - 16 Dec 2022

Cited by 5 | Viewed by 1994

Abstract

Nomex honeycomb composites are used extensively in aerospace, automotive, and other industries due to their superior material properties. However, the tool wear during their machining can compromise the processing accuracy and the stability of the whole machining process, thus studies on the tool [...] Read more.

Nomex honeycomb composites are used extensively in aerospace, automotive, and other industries due to their superior material properties. However, the tool wear during their machining can compromise the processing accuracy and the stability of the whole machining process, thus studies on the tool wear and strengthening method are urgently needed. This study presents a radial difference calculation method (RDC) to evaluate the tool wear of the disc cutter quantitatively in both conventional cutting and ultrasonic assisted cutting. The morphology of the tool wear process and its characteristics were analyzed. Two different heat treatments (salt bath quenching and vacuum quenching) were carried out to strengthen the tool performance. The research results demonstrated that ultrasonic vibration could significantly reduce the tool wear of the disc cutter, by up to 36%, after the same machining time. Salt bath quenching and vacuum quenching can both strengthen the tool performance. Particularly, after vacuum quenching treatment, the disc cutter’s metallographic grains were refined, and the tool wear could be reduced by 64%, compared to the as-received disc cutter. The findings in this study could be instructive to obtain further understanding of the machining mechanism and to improve methods in ultrasonic assisted cutting of Nomex honeycomb composites. Full article

(This article belongs to the Section Manufacturing Technology)

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19 pages, 4723 KiB

Open AccessArticle

Benchmarking Analysis of the Panorama of Grid-Connected PV Installations in Spain

by F. J. Gómez-Uceda, M. Varo-Martínez, J. C. Ramírez-Faz, R. López-Luque and L. M. Fernández-Ahumada

Technologies 2022, 10(6), 131; https://doi.org/10.3390/technologies10060131 - 13 Dec 2022

Cited by 2 | Viewed by 1848

Abstract

Renewable energies play an important role as a solution to the challenge of satisfying the growing global energy demand without jeopardizing the achievements in the fight against climate change. Given this panorama, different countries, including Spain, have developed policies to promote renewable energies. [...] Read more.

Renewable energies play an important role as a solution to the challenge of satisfying the growing global energy demand without jeopardizing the achievements in the fight against climate change. Given this panorama, different countries, including Spain, have developed policies to promote renewable energies. One of the technologies that benefit from these policies is photovoltaics. In Spain, the number of grid-connected photovoltaic installations has increased significantly in recent years. It is interesting to analyze the panorama of these facilities and identify the trends in their design criteria. In this line, in this work, the projects of 70 grid-connected photovoltaic installations distributed across Spain were analyzed. For that purpose, benchmarking techniques were applied, facilitating the systematization of information, the intercomparison of plants and the identification of trends and efficient solutions. A set of characteristic indicators of each installation was defined, and a statistical analysis of them was developed. Likewise, a tool was developed that allows the designers of this type of photovoltaic plant to compare the design parameters chosen for their installations with those of the surrounding area. Therefore, this work provides knowledge about the current panorama of photovoltaic implementation applicable to its future advance. Full article

(This article belongs to the Section Environmental Technology)

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14 pages, 3108 KiB

Open AccessArticle

Combined Treatment of Parts Produced by Additive Manufacturing Methods for Improving the Surface Quality

by Sergey Grigoriev, Alexander Metel, Marina Volosova, Yury Melnik and Enver Mustafaev

Technologies 2022, 10(6), 130; https://doi.org/10.3390/technologies10060130 - 11 Dec 2022

Cited by 1 | Viewed by 2303

Abstract

To improve the quality of a part manufactured by the additive method, it is necessary to eliminate the porosity and high roughness of its surface, as well as to deposit a coating on it. For this purpose, in the present work, we studied [...] Read more.

To improve the quality of a part manufactured by the additive method, it is necessary to eliminate the porosity and high roughness of its surface, as well as to deposit a coating on it. For this purpose, in the present work, we studied the combined processing in a gas discharge plasma of complex shape parts obtained by the additive manufacturing method, which includes explosive ablation of surface protrusions when voltage pulses are applied to the part immersed in the plasma; polishing with a concentrated beam of fast neutral argon atoms at a large angle of incidence on the surface of the part, and magnetron deposition of a coating on it with assistance by fast argon atoms. Combined processing made it possible to completely get rid of porosity and reduce the surface roughness from Ra ~ 5 µm to Ra ~ 0.05 µm. Full article

(This article belongs to the Special Issue 3D Printing Technologies II)

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10 pages, 1007 KiB

Open AccessCase Report

Dynamic Storage Location Assignment in Warehouses Using Deep Reinforcement Learning

by Constantin Waubert de Puiseau, Dimitri Tegomo Nanfack, Hasan Tercan, Johannes Löbbert-Plattfaut and Tobias Meisen

Technologies 2022, 10(6), 129; https://doi.org/10.3390/technologies10060129 - 11 Dec 2022

Cited by 7 | Viewed by 4279

Abstract

The warehousing industry is faced with increasing customer demands and growing global competition. A major factor in the efficient operation of warehouses is the strategic storage location assignment of arriving goods, termed the dynamic storage location assignment problem (DSLAP). This paper presents a [...] Read more.

The warehousing industry is faced with increasing customer demands and growing global competition. A major factor in the efficient operation of warehouses is the strategic storage location assignment of arriving goods, termed the dynamic storage location assignment problem (DSLAP). This paper presents a real-world use case of the DSLAP, in which deep reinforcement learning (DRL) is used to derive a suitable storage location assignment strategy to decrease transportation costs within the warehouse. The DRL agent is trained on historic data of storage and retrieval operations gathered over one year of operation. The evaluation of the agent on new data of two months shows a 6.3% decrease in incurring costs compared to the currently utilized storage location assignment strategy which is based on manual ABC-classifications. Hence, DRL proves to be a competitive solution alternative for the DSLAP and related problems in the warehousing industry. Full article

(This article belongs to the Special Issue Data Science and Big Data in Biology, Physical Science and Engineering)

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12 pages, 3276 KiB

Open AccessArticle

Research on the Effect of Road Height Profile on Fuel Consumption during Vehicle Acceleration

by Jiří Hanzl, Jan Pečman, Ladislav Bartuška, Ondrej Stopka and Branislav Šarkan

Technologies 2022, 10(6), 128; https://doi.org/10.3390/technologies10060128 - 9 Dec 2022

Cited by 2 | Viewed by 2148

Abstract

The presented article deals with research on the dependence between road vehicle fuel consumption and the longitudinal height profile of the road. The main research goal is to investigate the difference in fuel consumption during acceleration on different longitudinal profiles of the road [...] Read more.

The presented article deals with research on the dependence between road vehicle fuel consumption and the longitudinal height profile of the road. The main research goal is to investigate the difference in fuel consumption during acceleration on different longitudinal profiles of the road (i.e., flat surface, downhill) based on the actual investigation. In the first part of the article, important factors influencing fuel consumption during vehicle acceleration are summarized and a review of literature dealing with this issue is carried out. The next part focuses on the very real-world measurement. In addition to fuel consumption, other parameters were recorded that could be detected by a professional measuring laboratory. In the final part of the article, all the recorded data are evaluated, compared with research question and an actual example is given. Based on the evaluation, it could be concluded that approx. 100 L of fuel can be saved in one week thanks to the implemented measures. Thereafter, recommended possibilities for further use of these findings in technical practice are outlined in the conclusion. Full article

(This article belongs to the Section Environmental Technology)

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10 pages, 4586 KiB

Open AccessArticle

Influence of Operating Conditions on a Cast-Iron Manhole Cover

by Martin Mikelj, Marko Nagode, Jernej Klemenc and Domen Šeruga

Technologies 2022, 10(6), 127; https://doi.org/10.3390/technologies10060127 - 6 Dec 2022

Viewed by 2759

Abstract

Manhole covers must provide adequate strength and durability over the intended service life. In addition to operating loads, the lifespan of cast-iron manhole covers is strongly influenced by the conditions of installation and cover placement after opening or closing. These can include a [...] Read more.

Manhole covers must provide adequate strength and durability over the intended service life. In addition to operating loads, the lifespan of cast-iron manhole covers is strongly influenced by the conditions of installation and cover placement after opening or closing. These can include a vertical displacement from the plane of the carriageway during installation or the settlement of the terrain around the cover afterwards. After opening and closing the cover, the lid often only partially touches the support surface due to stones or other impurities caught on the surface or under the cover. These events can significantly affect the lifespan of the cover. In this study, an improved geometry of the cast-iron cover is proposed and analysed from an operational strength point of view. Initially, the geometry and potential critical points were scrutinized, and typical loads on the cover were determined. A numerical model was then set to simulate the behaviour during typical operation. In the simulations, the impact of the critical scenarios was analysed by dividing the impact parameters into individual levels. The simulation results reveal the suitability of the improved cover geometry. Full article

(This article belongs to the Section Manufacturing Technology)

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20 pages, 646 KiB

Open AccessArticle

RETRACTED: Policy Framework Enabling Flexibility Markets—Bulgarian Case

by Valeri Mladenov, Vesselin Chobanov and Verzhinia Ivanova

Technologies 2022, 10(6), 126; https://doi.org/10.3390/technologies10060126 - 2 Dec 2022

Cited by 2 | Viewed by 2416 | Retraction

Abstract

The legislation at the EU level is decisive in developing the local flexibility market. At the current stage, there are far-from-sufficient regulations on the local flexibility market, which can be perceived as a major barrier. The scope of this article is to explore [...] Read more.

The legislation at the EU level is decisive in developing the local flexibility market. At the current stage, there are far-from-sufficient regulations on the local flexibility market, which can be perceived as a major barrier. The scope of this article is to explore the operational principles of the European local flexibility market and to assess the regulation of emerging flexible markets in order to help a new policy framework that facilitates the integration of flexible assets in the distribution grid. Although the evaluation primarily focuses on current regulations, numerous modifications are still being made to them, such as those brought about by the implementation of the Clean Energy Package. The possibility of the research material quickly becoming outdated makes this difficult. To reduce this risk, we also examine current debates over potential restrictions; nonetheless, the core of the report mainly applies to laws and policies that were in force prior to the second half of 2022. An examination and analysis of potential flexibility providers’ motives to offer flexibility on a local flexibility market were conducted concurrently with the regulatory assessment. The inquiry was initiated by identifying resources that may be used to improve the flexibility of the electrical system but are underutilized. Underutilized resources refer to assets that are already part of society, such as efficient energy use, support for behavioral changes, heating systems (such as district heating, heat pumps, and thermal inertia), as well as underutilized energy storage capacities that are underutilized in terms of supplying flexibility to the electric grid. Resources were found via conducting interviews and studying scientific literature. The rules and guidelines for the emerging local flexibility markets are examined in this study. The regulations need to be continually improved because they are far from complete. Full article

13 pages, 460 KiB

Open AccessArticle

Privacy and Explainability: The Effects of Data Protection on Shapley Values

by Aso Bozorgpanah, Vicenç Torra and Laya Aliahmadipour

Technologies 2022, 10(6), 125; https://doi.org/10.3390/technologies10060125 - 1 Dec 2022

Cited by 7 | Viewed by 2397

Abstract

There is an increasing need to provide explainability for machine learning models. There are different alternatives to provide explainability, for example, local and global methods. One of the approaches is based on Shapley values. Privacy is another critical requirement when dealing with sensitive [...] Read more.

There is an increasing need to provide explainability for machine learning models. There are different alternatives to provide explainability, for example, local and global methods. One of the approaches is based on Shapley values. Privacy is another critical requirement when dealing with sensitive data. Data-driven machine learning models may lead to disclosure. Data privacy provides several methods for ensuring privacy. In this paper, we study how methods for explainability based on Shapley values are affected by privacy methods. We show that some degree of protection still permits to maintain the information of Shapley values for the four machine learning models studied. Experiments seem to indicate that among the four models, Shapley values of linear models are the most affected ones. Full article

(This article belongs to the Special Issue 10th Anniversary of Technologies—Recent Advances and Perspectives)

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19 pages, 7207 KiB

Open AccessPerspective

Methods of Material and Surface Analysis for the Evaluation of Failure Modes for Electrical Connectors

by Philipp Kolmer, Abhay Shukla and Jian Song

Technologies 2022, 10(6), 124; https://doi.org/10.3390/technologies10060124 - 29 Nov 2022

Cited by 2 | Viewed by 2588

Abstract

The development of autonomous vehicles and the integration of new information and communication technologies are making the reliability of electrical systems and components in modern vehicles increasingly important. Electrical connectors are a crucial component in an electrical on-board system. They are exposed to [...] Read more.

The development of autonomous vehicles and the integration of new information and communication technologies are making the reliability of electrical systems and components in modern vehicles increasingly important. Electrical connectors are a crucial component in an electrical on-board system. They are exposed to a wide variety of influences by the environment and operating conditions. Thus, the degradation of electrical connectors can occur. Material and surface analysis methods are the tools used to analyze the degradation mechanisms in connectors after lifetime tests, as well as in field operations. Within the framework of this study, a wide variety of methods from the analytical scope are presented and discussed. The connector surfaces degraded by different failure mechanisms are analyzed using various material and surface analysis methods. The quality and the nature of the analyses results obtained from various analysis methods are compared. Also, this study deals with the benefits and limitations, as well as the effort and the specific challenges of different material and surface analytical methods for the evaluation of failure mechanisms from the point of view of a material and surface analyst. Full article

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18 pages, 631 KiB

Open AccessEditor’s ChoiceArticle

HADD: High-Accuracy Detection of Depressed Mood

by Yu Liu, Kyoung-Don Kang and Mi Jin Doe

Technologies 2022, 10(6), 123; https://doi.org/10.3390/technologies10060123 - 29 Nov 2022

Cited by 6 | Viewed by 2225

Abstract

Depression is a serious mood disorder that is under-recognized and under-treated. Recent advances in mobile/wearable technology and ML (machine learning) have provided opportunities to detect the depressed moods of participants in their daily lives with their consent. To support high-accuracy, ubiquitous detection of [...] Read more.

Depression is a serious mood disorder that is under-recognized and under-treated. Recent advances in mobile/wearable technology and ML (machine learning) have provided opportunities to detect the depressed moods of participants in their daily lives with their consent. To support high-accuracy, ubiquitous detection of depressed mood, we propose HADD, which provides new capabilities. First, HADD supports multimodal data analysis in order to enhance the accuracy of ubiquitous depressed mood detection by analyzing not only objective sensor data, but also subjective EMA (ecological momentary assessment) data collected by using mobile devices. In addition, HADD improves upon the accuracy of state-of-the-art ML algorithms for depressed mood detection via effective feature selection, data augmentation, and two-stage outlier detection. In our evaluation, HADD significantly enhanced the accuracy of a comprehensive set of ML models for depressed mood detection. Full article

(This article belongs to the Section Assistive Technologies)

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12 pages, 831 KiB

Open AccessArticle

Comparison of the Predictive Performance of Medical Coding Diagnosis Classification Systems

by Dimitrios Zikos and Nailya DeLellis

Technologies 2022, 10(6), 122; https://doi.org/10.3390/technologies10060122 - 28 Nov 2022

Viewed by 2828

Abstract

Health analytics frequently involve tasks to predict outcomes of care. A foundational predictor of clinical outcomes is the medical diagnosis (Dx). The most used expression of medical Dx is the International Classification of Diseases (ICD-10-CM). Since ICD-10-CM includes >70,000 codes, it is computationally [...] Read more.

Health analytics frequently involve tasks to predict outcomes of care. A foundational predictor of clinical outcomes is the medical diagnosis (Dx). The most used expression of medical Dx is the International Classification of Diseases (ICD-10-CM). Since ICD-10-CM includes >70,000 codes, it is computationally expensive and slow to train models with. Alternative lower-dimensionality alternatives include clinical classification software (CCS) and diagnosis-related groups (MS-DRGs). This study compared the predictive power of these alternatives against ICD-10-CM for two outcomes of hospital care: inpatient mortality and length of stay (LOS). Naïve Bayes (NB) and Random Forests models were created for each Dx system to examine their predictive performance for inpatient mortality, and Multiple Linear Regression models for the continuous LOS variable. The MS-DRGs performed highest for both outcomes, even outperforming ICD-10-CM. The admitting ICD-10-CM codes were, surprisingly, not underperformed by the primary ICD-10-CM Dxs. The CCS system, although having a much lower dimensionality than ICD-10-CM, has only slightly lower performance while the refined version of CCS only slightly outperformed the old CCS. Random Forests outperformed NB for MS-DRG, and ICD-10-CM, by a large margin. Results can provide insights to understand the compromise from using lower-dimensionality representations in clinical outcome studies. Full article

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20 pages, 2143 KiB

Open AccessEditor’s ChoiceArticle

Simulation Analysis of Signal Conditioning Circuits for Plants’ Electrical Signals

by Mirella Carneiro, Victor Oliveira, Fernanda Oliveira, Marco Teixeira and Milena Pinto

Technologies 2022, 10(6), 121; https://doi.org/10.3390/technologies10060121 - 25 Nov 2022

Cited by 1 | Viewed by 2253

Abstract

Electrical signals are generated and transmitted through plants in response to stimuli caused by external environment factors, such as touching, luminosity, and leaf burning. By analyzing a specific plant’s electrical responses, it is possible to interpret the impact of external aspects in the [...] Read more.

Electrical signals are generated and transmitted through plants in response to stimuli caused by external environment factors, such as touching, luminosity, and leaf burning. By analyzing a specific plant’s electrical responses, it is possible to interpret the impact of external aspects in the plasma membrane potential and, thus, determine the cause of the electrical signal. Moreover, these signals permit the whole plant structure to be informed almost instantaneously. This work presents a brief discussion of plants electrophysiology theory and low-cost signal conditioning circuits, which are necessary for the acquisition of plants’ electrical signals. Two signal conditioning circuits, which must be chosen depending on the signal to be measured, are explained in detail and electrical simulation results, performed in OrCAD Capture Software are presented. Furthermore, Monte Carlo simulations were performed to evaluate the impact of components variations on the accuracy and efficiency of the signal conditioning circuits. Those simulations showed that, even after possible component variations, the filters’ cut-off frequencies had at most 4% variation from the mean. Full article

(This article belongs to the Special Issue 10th Anniversary of Technologies—Recent Advances and Perspectives)

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21 pages, 580 KiB

Open AccessArticle

Human-in-Loop Decision-Making and Autonomy: Lessons Learnt from the Aviation Industry Transferred to Cyber-Physical Systems

by Chara Makri, Didem Gürdür Broo and Andy Neely

Technologies 2022, 10(6), 120; https://doi.org/10.3390/technologies10060120 - 24 Nov 2022

Viewed by 2649

Abstract

In this study, we reviewed aircraft accidents in order to understand how autonomy and safety has been managed in the aviation industry, with the aim of transferring our findings to autonomous cyber-physical systems (CPSs) in general. Through the qualitative analysis of 26 reports [...] Read more.

In this study, we reviewed aircraft accidents in order to understand how autonomy and safety has been managed in the aviation industry, with the aim of transferring our findings to autonomous cyber-physical systems (CPSs) in general. Through the qualitative analysis of 26 reports of aircraft accidents that took place from 2016 to 2022, we identified the most common contributing factors and the actors involved in aircraft accidents. We found that accidents were rarely the result of a single event or actor, with the most common contributing factor being non-adherence to standard operating procedures (SOPs). Considering that the aviation industry has had decades to perfect their SOPs, it is important for CPSs not only to consider the actors and causes that may contribute to safety-related issues, but also to consider well-defined reporting practices, as well as the different levels of mechanisms checked by diverse stakeholders, in order to minimise the cascading nature of such events to improve safety. In addition to proposing a new definition of safety, in this study we suggest reviewing high-reliability organisations to offer further insights as part of future research on CPS safety. Full article

(This article belongs to the Special Issue Human-Centered Cyber-Physical Systems)

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18 pages, 2498 KiB

Open AccessEditor’s ChoiceArticle

Infrared Thermal Imaging and Artificial Neural Networks to Screen for Wrist Fractures in Pediatrics

by Olamilekan Shobayo, Reza Saatchi and Shammi Ramlakhan

Technologies 2022, 10(6), 119; https://doi.org/10.3390/technologies10060119 - 22 Nov 2022

Cited by 4 | Viewed by 2163

Abstract

Paediatric wrist fractures are commonly seen injuries at emergency departments. Around 50% of the X-rays taken to identify these injuries indicate no fracture. The aim of this study was to develop a model using infrared thermal imaging (IRTI) data and multilayer perceptron (MLP) [...] Read more.

Paediatric wrist fractures are commonly seen injuries at emergency departments. Around 50% of the X-rays taken to identify these injuries indicate no fracture. The aim of this study was to develop a model using infrared thermal imaging (IRTI) data and multilayer perceptron (MLP) neural networks as a screening tool to assist clinicians in deciding which patients require X-ray imaging to diagnose a fracture. Forty participants with wrist injury (19 with a fracture, 21 without, X-ray confirmed), mean age 10.50 years, were included. IRTI of both wrists was performed with the contralateral as reference. The injured wrist region of interest (ROI) was segmented and represented by the means of cells of 10 × 10 pixels. The fifty largest means were selected, the mean temperature of the contralateral ROI was subtracted, and they were expressed by their standard deviation, kurtosis, and interquartile range for MLP processing. Training and test files were created, consisting of randomly split 2/3 and 1/3 of the participants, respectively. To avoid bias of participant inclusion in the two files, the experiments were repeated 100 times, and the MLP outputs were averaged. The model’s sensitivity and specificity were 84.2% and 71.4%, respectively. Further work involves a larger sample size, adults, and other bone fractures. Full article

(This article belongs to the Special Issue Medical Imaging & Image Processing III)

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15 pages, 9713 KiB

Open AccessEditor’s ChoiceArticle

Friction Stir Welding of Ti-6Al-4V Using a Liquid-Cooled Nickel Superalloy Tool

by Sergei Tarasov, Alihan Amirov, Andrey Chumaevskiy, Nikolay Savchenko, Valery E. Rubtsov, Aleksey Ivanov, Evgeniy Moskvichev and Evgeny Kolubaev

Technologies 2022, 10(6), 118; https://doi.org/10.3390/technologies10060118 - 18 Nov 2022

Cited by 6 | Viewed by 2278

Abstract

Friction stir welding (FSW) of titanium alloy was carried out using liquid cooling of the FSW tool made of heat-resistant nickel superalloy. Cooling of the nickel superalloy tool was performed by means of circulating water inside the tool. The FSW joints were characterized [...] Read more.

Friction stir welding (FSW) of titanium alloy was carried out using liquid cooling of the FSW tool made of heat-resistant nickel superalloy. Cooling of the nickel superalloy tool was performed by means of circulating water inside the tool. The FSW joints were characterized by microstructures and mechanical strength. The mechanical strength of the joints was higher than that of the base metal. Full article

(This article belongs to the Special Issue 10th Anniversary of Technologies—Recent Advances and Perspectives)

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26 pages, 2625 KiB

Open AccessEditor’s ChoiceArticle

Towards a Modern Learning Organization: Human-Centered Digitalization of Lessons Learned Management for Complex Systems Development Projects

by YangYang Zhao and Henrik Jensen

Technologies 2022, 10(6), 117; https://doi.org/10.3390/technologies10060117 - 16 Nov 2022

Viewed by 2744

Abstract

The importance of learning from experience is incontrovertible; however, little is studied regarding the digitalization of in- and inter-project lessons learned in modern organizational practices. As a critical part of organizational knowledge, lessons learned are known to help organizations adapt to the ever-changing [...] Read more.

The importance of learning from experience is incontrovertible; however, little is studied regarding the digitalization of in- and inter-project lessons learned in modern organizational practices. As a critical part of organizational knowledge, lessons learned are known to help organizations adapt to the ever-changing world via the complex systems development projects they use to capitalize on and to develop their competitive advantage. In this paper, we introduce the concept of human-centered digitalization for this unique type of organizational knowledge and explain why this approach to managing lessons learned for complex systems development projects is necessary. Drawing from design thinking and systems thinking theories, we further outline the design principles for guiding actions and provide a case study of their implementation in automated systems projects for maritime industries. Full article

(This article belongs to the Special Issue Human-Centered Cyber-Physical Systems)

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20 pages, 8521 KiB

Open AccessEditor’s ChoiceArticle

Electrical Discharge Machining of Al₂O₃ Using Copper Tape and TiO₂ Powder-Mixed Water Medium

by Sergey N. Grigoriev, Anna A. Okunkova, Marina A. Volosova, Khaled Hamdy and Alexander S. Metel

Technologies 2022, 10(6), 116; https://doi.org/10.3390/technologies10060116 - 11 Nov 2022

Cited by 6 | Viewed by 3069

Abstract

Aluminum-based ceramics are used in industry to produce cutting tools that resist extreme mechanical and thermal load conditions during the machining of Ni-based and high-entropy alloys. There is wide field of application also in the aerospace industry. Microtexturing of cutting ceramics reduces contact [...] Read more.

Aluminum-based ceramics are used in industry to produce cutting tools that resist extreme mechanical and thermal load conditions during the machining of Ni-based and high-entropy alloys. There is wide field of application also in the aerospace industry. Microtexturing of cutting ceramics reduces contact loads and wear of cutting tools. However, most of the published works are related to the electrical discharge machining of alumina in hydrocarbons, which creates risks for the personnel and equipment due to the formation of chemically unstable dielectric carbides (methanide Al₃C₄ and acetylenide Al₂(C₂)₃). An alternative approach for wire electrical discharge machining Al₂O₃ in the water-based dielectric medium using copper tape of 40 µm thickness and TiO₂ powder suspension was proposed for the first time. The performance was evaluated by calculating the material removal rate for various combinations of pulse frequency and TiO₂ powder concentration. The obtained kerf of 54.16 ± 0.05 µm in depth demonstrated an increasing efficiency of more than 1.5 times with the closest analogs for the workpiece thickness up to 5 mm in height. The comparison of the performance (0.0083–0.0084 mm³/s) with the closest analogs shows that the results may correlate with the electrical properties of the assisting materials. Full article

(This article belongs to the Section Innovations in Materials Processing)

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21 pages, 15427 KiB

Open AccessEditor’s ChoiceArticle

Modelling the Trust Value for Human Agents Based on Real-Time Human States in Human-Autonomous Teaming Systems

by Chin-Teng Lin, Hsiu-Yu Fan, Yu-Cheng Chang, Liang Ou, Jia Liu, Yu-Kai Wang and Tzyy-Ping Jung

Technologies 2022, 10(6), 115; https://doi.org/10.3390/technologies10060115 - 8 Nov 2022

Cited by 1 | Viewed by 2687

Abstract

The modelling of trust values on agents is broadly considered fundamental for decision-making in human-autonomous teaming (HAT) systems. Compared to the evaluation of trust values for robotic agents, estimating human trust is more challenging due to trust miscalibration issues, including undertrust and overtrust [...] Read more.

The modelling of trust values on agents is broadly considered fundamental for decision-making in human-autonomous teaming (HAT) systems. Compared to the evaluation of trust values for robotic agents, estimating human trust is more challenging due to trust miscalibration issues, including undertrust and overtrust problems. From a subjective perception, human trust could be altered along with dynamic human cognitive states, which makes trust values hard to calibrate properly. Thus, in an attempt to capture the dynamics of human trust, the present study evaluated the dynamic nature of trust for human agents through real-time multievidence measures, including human states of attention, stress and perception abilities. The proposed multievidence human trust model applied an adaptive fusion method based on fuzzy reinforcement learning to fuse multievidence from eye trackers, heart rate monitors and human awareness. In addition, fuzzy reinforcement learning was applied to generate rewards via a fuzzy logic inference process that has tolerance for uncertainty in human physiological signals. The results of robot simulation suggest that the proposed trust model can generate reliable human trust values based on real-time cognitive states in the process of ongoing tasks. Moreover, the human-autonomous team with the proposed trust model improved the system efficiency by over

50 %

compared to the team with only autonomous agents. These results may demonstrate that the proposed model could provide insight into the real-time adaptation of HAT systems based on human states and, thus, might help develop new ways to enhance future HAT systems better. Full article

(This article belongs to the Special Issue 10th Anniversary of Technologies—Recent Advances and Perspectives)

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34 pages, 11931 KiB

Open AccessEditor’s ChoiceArticle

Open-Source Photovoltaic—Electrical Vehicle Carport Designs

by Nicholas Vandewetering, Koami Soulemane Hayibo and Joshua M. Pearce

Technologies 2022, 10(6), 114; https://doi.org/10.3390/technologies10060114 - 7 Nov 2022

Cited by 9 | Viewed by 7072

Abstract

Solar powering the increasing fleet of electrical vehicles (EV) demands more surface area than may be available for photovoltaic (PV)-powered buildings. Parking lot solar canopies can provide the needed area to charge EVs but are substantially costlier than roof- or ground-mounted PV systems. [...] Read more.

Solar powering the increasing fleet of electrical vehicles (EV) demands more surface area than may be available for photovoltaic (PV)-powered buildings. Parking lot solar canopies can provide the needed area to charge EVs but are substantially costlier than roof- or ground-mounted PV systems. To provide a low-cost PV parking lot canopy to supply EV charging, in this study, we provide a full mechanical and economic analysis of three novel PV canopy systems: (1) an exclusively wood, single-parking-spot spanning system, (2) a wood and aluminum double-parking-spot spanning system, and (3) a wood and aluminum cantilevered system for curbside parking. All three systems can be scaled to any amount of EV parking spots. The complete designs and bill of materials (BOM) of the canopies are provided, along with basic instructions, and are released with an open-source license that will enable anyone to fabricate them. Analysis results indicate that single-span systems provide cost savings of 82–85%, double-span systems save 43–50%, and cantilevered systems save 31–40%. In the first year of operation, PV canopies can provide 157% of the energy needed to charge the least efficient EV currently on the market if it is driven the average driving distance in London, ON, Canada. Full article

(This article belongs to the Topic Emerging Technologies for Grid-Interactive Efficient Buildings and Communities)

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24 pages, 10290 KiB

Open AccessEditor’s ChoiceArticle

Modular Multi-Input DC/DC Converter for EV Fast Charging

by Hossam A. Gabbar and Abdalrahman Elshora

Technologies 2022, 10(6), 113; https://doi.org/10.3390/technologies10060113 - 7 Nov 2022

Cited by 1 | Viewed by 2806

Abstract

In this paper, a modular multi-input, single output DC/DC converter is proposed to enhance the energy management of a fast-charging station for electric vehicles (EVs). The proposed bidirectional converter can work in different modes of operation with fewer components and a modular design [...] Read more.

In this paper, a modular multi-input, single output DC/DC converter is proposed to enhance the energy management of a fast-charging station for electric vehicles (EVs). The proposed bidirectional converter can work in different modes of operation with fewer components and a modular design to extend the input power sources and increase the charging power rate. The converter has several merits compared to the conventional converters, such as centralizing the control, reducing power devices, and reducing power conversion stages. By using MATLAB/Simulink, the converter was tested in many operation modes and was used to charge a Nissan Leaf EV’s battery (350 V, 60 Ah) from hybrid sources simultaneously and individually in power up to (17 kW). In addition, it was tested on a hardware scale at a low power rate (100 W) for the validation of the simulation work and the topology concept. In addition, its different losses and efficiency were calculated during the different operation modes. Full article

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12 pages, 4446 KiB

Open AccessArticle

Fabrication and Characterization of SnCl₂- and CuBr-Added Perovskite Photovoltaic Devices

by Yugo Asakawa, Takeo Oku, Masashi Kido, Atsushi Suzuki, Riku Okumura, Masanobu Okita, Sakiko Fukunishi, Tomoharu Tachikawa and Tomoya Hasegawa

Technologies 2022, 10(6), 112; https://doi.org/10.3390/technologies10060112 - 28 Oct 2022

Cited by 11 | Viewed by 2088

Abstract

Perovskite photovoltaic devices added with tin (Sn) dichloride and copper (Cu) bromide were fabricated and characterized. The thin film devices were prepared by an ordinary spin-coating technique using an air blowing method in ambient air. A decaphenylcyclopentasilane layer was coated at the surface [...] Read more.

Perovskite photovoltaic devices added with tin (Sn) dichloride and copper (Cu) bromide were fabricated and characterized. The thin film devices were prepared by an ordinary spin-coating technique using an air blowing method in ambient air. A decaphenylcyclopentasilane layer was coated at the surface of perovskite layer and annealed at a high temperature of 190 °C. Conversion efficiencies and short-circuit current densities were improved for devices added with Sn and Cu compared with the standard devices. The energy gap of the perovskite crystal decreased through the Sn addition, which was also confirmed by first-principles calculations. Full article

(This article belongs to the Section Innovations in Materials Processing)

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8 pages, 362 KiB

Open AccessEditor’s ChoiceCommunication

Variance-Based Sensitivity Analysis of Fitting Parameters to Impact on Cycling Durability of Polymer Electrolyte Fuel Cells

by Victor A. Kovtunenko

Technologies 2022, 10(6), 111; https://doi.org/10.3390/technologies10060111 - 28 Oct 2022

Cited by 3 | Viewed by 1695

Abstract

Degradation of a catalyst layer in polymer electrolyte membrane fuel cells is considered, which is caused by electrochemical reactions of the platinum ion dissolution and oxide coverage. An accelerated stress test is applied, where the electric potential cycling is given by a non-symmetric [...] Read more.

Degradation of a catalyst layer in polymer electrolyte membrane fuel cells is considered, which is caused by electrochemical reactions of the platinum ion dissolution and oxide coverage. An accelerated stress test is applied, where the electric potential cycling is given by a non-symmetric square profile. Computer simulations of the underlying one-dimensional Holby–Morgan model predict durability of the fuel cell operating. A sensitivity analysis based on the variance quantifies how loss of the platinum mass subjected to the degradation is impacted by the variation of fitting parameters in the model. Full article

(This article belongs to the Section Environmental Technology)

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17 pages, 1944 KiB

Open AccessArticle

The Impossible, the Unlikely, and the Probable Nudges: A Classification for the Design of Your Next Nudge

by Randi Karlsen and Anders Andersen

Technologies 2022, 10(6), 110; https://doi.org/10.3390/technologies10060110 - 22 Oct 2022

Cited by 2 | Viewed by 3246

Abstract

Nudging provides a way to gently influence people to change behavior towards a desired goal, e.g., by moving towards a healthier or more environmentally friendly lifestyle. Personalized and context-aware digital nudging (named smart nudging) can be a powerful tool for efficient nudging by [...] Read more.

Nudging provides a way to gently influence people to change behavior towards a desired goal, e.g., by moving towards a healthier or more environmentally friendly lifestyle. Personalized and context-aware digital nudging (named smart nudging) can be a powerful tool for efficient nudging by tailoring nudges to the current situation of each individual user. However, designing smart nudges is challenging, as different users may need different supports to improve their behavior. Determining the next nudge for a specific user must be done based on the user’s current situation, abilities, and potential for improvement. In this paper, we focus on the challenge of designing the next nudge by presenting a novel classification of nudges that distinguishes between (i) nudges that are impossible for the user to follow, (ii) nudges that are unlikely to be followed, and (iii) probable nudges that the user can follow. The classification is tailored to individual users based on user profiles, current situations, and knowledge of previous behaviors. This paper describes steps in the nudge design process and a novel set of principles for designing smart nudges. Full article

(This article belongs to the Section Information and Communication Technologies)

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Technologies, Volume 10, Issue 6 (December 2022) – 23 articles

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