Vilnius Gediminas Technical University
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Repeatability of High-Pressure Measurement in a Diesel Engine Test Bed
No full textThis paper addresses the issue of metrological accuracy of instantaneous in-cylinder pressure measurement in a diesel engine test bed. In studies, the central unit has been the single-cylinder AVL 5402 engine. The pressure measurement was performed with a sensor designed for thermodynamic analysis, and the results were related to the crank angle, where two rotations corresponding to the four-stroke working cycle were denoted as angles between −360° and +360°. The novelty of this paper is the proposition of how to perform a type A uncertainty estimation of the in-cylinder pressure measurement and to assess its repeatability. It was demonstrated that repeatability of the measurement during the ignition process was difficult to estimate because of the phenomena that cannot ensure the repeatability conditions. To solve the problem, two methods were proposed. In one method, the pressure was measured in the subsequent cycles immediately after the ignition was turned off, and in another method, the engine was driven by a starter. The latter method provided maximal pressure values much lower than during usual tests. The obtained repeatability of measured pressure was %EV = 0.4%, which proved high capability of the evaluated measurement system.This article belongs to the Special Issue Sensors in Experimental MechanicsThe research was supported by the Cultural and Educational Grant Agency of the Ministry of Education,
Science, Research and Sport of the Slovak Republic under the project no. KEGA 044ŽU-4/2019 “Implementation of
Innovative Elements in the Education Process within the Study Program Maintenance of Means of Transport”,
and co-funded from the ’Excellent science’ program of the Polish Ministry of Science and Higher Education as part
of the contract no. DNK/SP/465641/2020 “The role of the agricultural engineering and environmental engineering
in the sustainable agriculture development”
Feasibility Evaluation of Local Laser Treatment for Strengthening of Thin-Walled Structures from Low-Carbon Steel Subjected to Bending
No full textThis paper is devoted to investigating numerically, by finite element analysis (FEA), and analytically the influences and effects of laser processing of the surface of thin-plate, low-carbon structural steel. The plate mechanical properties—axial and flexural stiffnesses, force-deflection behavior and cross-section force-strain behavior—are investigated after different laser treatments. An analytical methodology of the estimation of the cross-section area of the laser-processed metal is also proposed in the present article, that can be applied to choosing the reasonable distance between the centers of the laser-processed tracks. The methodology takes into account the width of the laser-processed tracks and the distances between these tracks. The experimental, finite element numerical and analytical analyses showed that the laser treatments of the surface of the steel plate increase the yield point of the laser-processed metal and the axial and flexural stiffnesses of the plate.This article belongs to the Special Issue Development of Laser Welding and Surface Treatment of Metal
Nanocatalysts Containing Direct Electron Transfer-Capable Oxidoreductases: Recent Advances and Applications
Get PDFDirect electron transfer (DET)-capable oxidoreductases are enzymes that have the ability to transfer/receive electrons directly to/from solid surfaces or nanomaterials, bypassing the need for an additional electron mediator. More than 100 enzymes are known to be capable of working in DET conditions; however, to this day, DET-capable enzymes have been mainly used in designing biofuel cells and biosensors. The rapid advance in (semi) conductive nanomaterial development provided new possibilities to create enzyme-nanoparticle catalysts utilizing properties of DET-capable enzymes and demonstrating catalytic processes never observed before. Briefly, such nanocatalysts combine several cathodic and anodic catalysis performing oxidoreductases into a single nanoparticle surface. Hereby, to the best of our knowledge, we present the first review concerning such nanocatalytic systems involving DET-capable oxidoreductases. We outlook the contemporary applications of DET-capable enzymes, present a principle of operation of nanocatalysts based on DET-capable oxidoreductases, provide a review of state-of-the-art (nano) catalytic systems that have been demonstrated using DET-capable oxidoreductases, and highlight common strategies and challenges that are usually associated with those type catalytic systems. Finally, we end this paper with the concluding discussion, where we present future perspectives and possible research directions.This article belongs to the Special Issue State of the Art and Future Trends in Nanostructured Biocatalysi
A Group Decision Framework for Renewable Energy Source Selection under Interval-Valued Probabilistic linguistic Term Set
No full textIn recent years, the assessment of desirable renewable energy alternative has been an extremely important concern that could change the environment and economic growth. To tackle the circumstances, some authors have paid attention to selecting the desirable renewable energy option by employing the decision-making assessment and linguistic term sets. With a fast-growing interest in multi-criteria group decision-making (MCGDM) problems, researchers are tirelessly working towards new techniques for better decision-making. Decision makers (DMs) generally rate alternatives linguistically with different probabilities occurring for each term. Previous studies on linguistic decision-making have either ignored this idea or have used an only a single value for representing the weight of the linguistic term. Since expression of the complete probability distribution is hard and implicit hesitation exists, representation of weights of the linguistic terms using a single value becomes imprecise and unreasonable. To avoid this challenge, an interval-valued probabilistic linguistic term set (IVPLTS) is used, which is a generalization of (probabilistic linguistic term set) PLTS. Inspired by the usefulness of IVPLTS concept, we develop a decision framework for rational decision making. Initially, some operational laws and axioms are presented. Further, a novel aggregation operator known as interval-valued probabilistic linguistic simple weighted geometry (IVPLSWG) is developed for aggregating DMs’ preferences. Also, criteria weights are determined using the newly developed interval-valued probabilistic linguistic standard variance (IVPLSV) approach and alternatives are ranked using the extended VIKOR (VlseKriterijumskaOptimizacijaKompromisnoResenje) method under IVPLTS environment. Finally, a numerical example of renewable energy assessment is demonstrated to show the practicality of the developed decision framework. Also, the strengths and weaknesses of the developed decision framework are illustrated by comparison with existing ones.This article belongs to the Special Issue Uncertain Decision Making Methods in Energy Policies for Sustainable Developmen
Force and Sound Pressure Sensors Used for Modeling the Impact of the Firearm with a Suppressor
No full textIn this paper, a mathematical model for projectiles shooting in any direction based on sensors distributed stereoscopically is put forward. It is based on the characteristics of a shock wave around a supersonic projectile and acoustical localization. Wave equations for an acoustic monopole point source of a directed effect used for physical interpretation of pressure as an acoustic phenomenon. Simulation and measurements of novel versatile mechanical and acoustical damping system (silencer), which has both a muzzle break and silencer properties studied in this paper. The use of the proposed damping system can have great influence on the acoustic pressure field intensity from the shooter. A silencer regarded as an acoustic transducer and multi-holes waveguide with a chamber. Wave equations for an acoustic monopole point source of a directed effect used for the physical interpretation of pressure as an acoustic phenomenon. The numerical simulation results of the silencer with different configurations presented allow trends to be established. A measurement chain was used to compare the simulation results with the experimental ones. The modeling and experimental results showed an increase in silencer chamber volume results in a reduction of recorded pressure within the silencer chamber.This article belongs to the Special Issue Modelling, Simulation and Data Analysis in Acoustical Problems
Distributed Optical Fiber Sensing Bonding Techniques Performance for Embedment inside Reinforced Concrete Structures
No full textDistributed optical fiber sensors (DOFS) are modern-day cutting-edge monitoring tools that are quickly acquiring relevance in structural health monitoring engineering. Their most ambitious use is embedded inside plain or reinforced concrete (RC) structures with the scope of comprehending their inner-workings and the functioning of the concrete-reinforcement interaction. Yet, multiple studies have shown that the bonding technique with which the DOFS are bonded to the reinforcement bars has a significant role on the quality of the extracted strain data. Whilst this influence has been studied for externally bonded DOFS, it has not been done for embedded ones. The present article is set on performing such study by monitoring the strain measurement quality as sampled by DOFS bonded to multiple rebars with different techniques and adhesives. These instrumented rebars are used to produce differently sized RC ties later tested in tension. The discussion of the test outputs highlights the quasi-optimal performance of a DOFS/rebar bonding technique consisting of incising a groove in the rebar, positioning the DOFS inside it, bonding it with cyanoacrylate and later adding a protective layer of silicone. The resulting data is mostly noise-free and anomalies-free, yet still presents a newly diagnosed hitch that needs addressing in future research.This article belongs to the Special Issue Structural Health Monitoring for Smart StructuresThe study was performed within project No 09.3.3-LMT-K-712-01-0145 that has received funding from
European Social Fund under grant agreement with the Research Council of Lithuania (LMTLT). Furthermore,
this work was supported by the Swedish Transportation Administration (Trafikverket) under the grant TRV/BBT
2017-028. The authors are also indebted to the Secretaria d’ Universitats i Recerca de la Generalitat de Catalunya
for the funding provided through Agaur (2017 SGR 1481)
Polyethylene-Carbon Composite (Velostat®) Based Tactile Sensor
No full textThe progress observed in ‘soft robotics’ brought some promising research in flexible tactile, pressure and force sensors, which can be based on polymeric composite materials. Therefore, in this paper, we intend to evaluate the characteristics of a force-sensitive material—polyethylene-carbon composite (Velostat®) by implementing this material into the design of the flexible tactile sensor. We have explored several possibilities to measure the electrical signal and assessed the mechanical and time-dependent properties of this tactile sensor. The response of the sensor was evaluated by performing tests in static, long-term load and cyclic modes. Experimental results of loading cycle measurements revealed the hysteresis and nonlinear properties of the sensor. The transverse resolution of the sensor was defined by measuring the response of the sensor at different distances from the loaded point. Obtained dependencies of the sensor’s sensitivity, hysteresis, response time, transversal resolution and deformation on applied compressive force promise a practical possibility to use the polyethylene-carbon composite as a sensitive material for sensors with a single electrode pair or its matrix. The results received from experimental research have defined the area of the possible implementation of the sensor based on a composite material—Velostat®.This article belongs to the Special Issue High-Performance Polymeric SensorsThis project has received funding from European Social Fund (project No 09.3.3-LMT-K-712-19-0153) under grant agreement with the Research Council of Lithuania (LMTLT)
A New Decision-Making Approach Based on Fermatean Fuzzy Sets and WASPAS for Green Construction Supplier Evaluation
No full textThe construction industry is an important industry because of its effects on different aspects of human life experiences and circumstances. Environmental concerns have been considered in designing and planning processes of construction supply chains in the recent past. One of the most crucial problems in managing supply chains is the process of evaluation and selection of green suppliers. This process can be categorized as a multi-criteria decision-making (MCDM) problem. The aim of this study is to propose a novel and efficient methodology for evaluation of green construction suppliers with uncertain information. The framework of the proposed methodology is based on weighted aggregated sum product assessment (WASPAS) and the simple multi-attribute rating technique (SMART), and Fermatean fuzzy sets (FFSs) are used to deal with uncertainty of information. The methodology was applied to a green supplier evaluation and selection in the construction industry. Fifteen suppliers were chosen to be evaluated with respect to seven criteria including “estimated cost”, “delivery efficiency”, “product flexibility”, “reputation and management level”, “eco-design”, and “green image pollution”. Sensitivity and comparative analyses were also conducted to assess the efficiency and validity of the proposed methodology. The analyses showed that the results of the proposed methodology were stable and also congruent with those of some existing methods.This article belongs to the Special Issue Fuzzy Applications in Industrial EngineeringThe research was funded by European Regional Development Fund under a grant agreement No
01.2.2-LMT-K-718-01-0073 with the Research Council of Lithuania (LMTLT)
Gated Bow-Tie Diode for Microwave to Sub-Terahertz Detection
No full textWe propose a new design microwave radiation sensor based on a selectively doped semiconductor structure of asymmetrical shape (so-called bow-tie diode). The novelty of the design comes down to the gating of the active layer of the diode above different regions of the two-dimensional electron channel. The gate influences the sensing properties of the bow-tie diode depending on the nature of voltage detected across the ungated one as well as on the location of the gate in regard to the diode contacts. When the gate is located by the wide contact, the voltage sensitivity increases ten times as compared to the case of the ungated diode, and the detected voltage holds the same polarity of the thermoelectric electromotive force of hot electrons in an asymmetrically shaped n-n+ junction. Another remarkable effect of the gate placed by the wide contact is weak dependence of the detected voltage on frequency which makes such a microwave diode to be a proper candidate for the detection of electromagnetic radiation in the microwave and sub-terahertz frequency range. When the gate is situated beside the narrow contact, the two orders of sensitivity magnitude increase are valid in the microwaves but the voltage sensitivity is strongly frequency-dependent for higher frequencies.This article belongs to the Special Issue Sensors Based on RF Circuits and Microwave CircuitsThis work was in part supported by the Research Council of Lithuania (grant No. LAT-03/2016) in the
frame of National Science Program “Towards Future Technologies”
Unsupervised Pre-Training for Voice Activation
Get PDFThe problem of voice activation is to find a pre-defined word in the audio stream. Solutions such as keyword spotter “Ok, Google” for Android devices or keyword spotter “Alexa” for Amazon devices use tens of thousands to millions of keyword examples in training. In this paper, we explore the possibility of using pre-trained audio features to build voice activation with a small number of keyword examples. The contribution of this article consists of two parts. First, we investigate the dependence of the quality of the voice activation system on the number of examples in training for English and Russian and show that the use of pre-trained audio features, such as wav2vec, increases the accuracy of the system by up to 10% if only seven examples are available for each keyword during training. At the same time, the benefits of such features become less and disappear as the dataset size increases. Secondly, we prepare and provide for general use a dataset for training and testing voice activation for the Lithuanian language. We also provide training results on this dataset.This article belongs to the Section Computing and Artificial Intelligenc