bluuebunny/crossref_metadata_2025_split huggingface dataset:
Experimental study of epoxy based graphite coating on parabolic trough solar collector
Authors: Nagaraj Abhijeeth 
Published: February 2022

Abstract
Parabolic Trough Solar Collector is a line concentration method employed to harness solar energy for high-temperature applications. Attempts are made to improve the heat transfer of PTSC by reducing convectional losses of the absorber tube by using covering on the absorber tube. The study attempts to improve the Parabolic Trough Solar Collector performance using epoxy-based graphite coating through experimentation. The experiment is attempted for varied flow rates of 0.3, 0.7 and 1.1 litres per minute. The study highlighted that the coating method improved the rise in thermal fluid temperature over the absorber tube covering method by 24%. The improvement in heat transfer due to the graphite coating can be accounted for by the improvement in absorptivity and insulation, leading to better heat transfer to the thermal fluid utilized in the absorber tube.
Photovoltaic acai (Euterpe oleracea Mart.) berry juice extractor machine
Authors: Feijão A T , Almeida A M G , Brito A U 
Published: February 2022

Abstract
This project is about the development of a product called the photovoltaic acai (Euterpe oleracea Mart.) berry juice extractor machine, which comes as a technological alternative to solve one of the problems resulting from the lack of commercial supply of electricity in remote areas of the Amazon. It is a utility model patent, which employs equipment available in the local market, designated initially to operate in conventional electrical supply however operationally configured for photovoltaic solar power systems. This machine configuration consists of an “acai mixer”, a three-phase induction motor, a three-phase variable-speed drive and a photovoltaic generator. The photovoltaic acai (Euterpe oleracea Mart.) berry juice extractor machine is characterized as a photovoltaic system isolated from the conventional power grid and it is of the type of direct coupling. The results of the tests performed in the lab revealed that the prototype could produce up to 126 L/day of acai berry juice in a single day. However, the production of only 28 L/day is able to amortize the investment within two years.
Grid-connected photovoltaic system with power smoothing
Authors: Pantaleon E , Sal y Rosas D 
Published: February 2022

Abstract
This paper analyzes the power smoothing of grid-connected photovoltaic (PV) systems under fast irradiance changes. The analyzed converter is composed of a triple active bridge series-resonant (TABSR) DC-DC converter cascaded with a voltage source inverter (VSI). Two controlled variables are considered: battery current and the PV voltage. The TABSR DC-DC converter is modeled as controlled current sources for the battery and the PV ports. The ramp rate (RR) control algorithm is used to smooth the PV output power profile enhancing the power delivered to the grid. Four ramp rates (10%, 5%, 2% and 1%) are used to evaluate the RR control algorithm and the battery state of charge (SOC) response. Therefore, the battery can be sized appropriately. Real data for irradiance and temperature in an overcast day is used to verify the effectiveness of the proposed system.
Soiling accumulation impact on PV modules installed at different tilted angles in São Paulo, Brazil
Authors: Misquita Í da S , Zilles R 
Published: February 2022

Abstract
The present study was carried out at the University of São Paulo (USP), in the capital campus, in Butantã, São Paulo. On the rooftop of the Photovoltaic Systems Laboratory (LSF). This study used twenty photovoltaic modules with a unit power of 20 Wp. Before the beginning of the study, the modules were exposed to natural light so that they would suffer the LID effect. Subsequently, all modules were calibrated to measure the solar irradiance, using IEC 60904-2 using a pyranometer as a secondary reference sensor. After calibration, the modules were arranged in pairs, with angles ranging from 0 to 45° as reference to the surface, with a difference between pairs of 5°. To evaluate the influence of rainfall, which is the main responsible for the natural cleaning of the modules. The pluviometric values were obtained from the meteorological station of the Institute of Astronomy, Geophysics and Atmospheric Sciences of the USP. The module allocated at 0°, “Dirty” was used as reference and all the results obtained were calculated in relation to it. The results for the 18 months of experiment showed the non-linear influence of soiling, acting in a stronger way for the less inclined angles, and after 10°, this influence, became less relevant, in comparison to the previous angle. The largest losses were found for 0° and 5°, the losses exclusively to soiling were 8.16 % and 6.82 % respectively. For angles greater than 10°, the soiling effect was attenuated, which resulted in less significant losses, for 15° the difference between the impact of dirt compared to 10° was only 0.1%. Rainfall also had a very relevant impact on the experiment. This study concluded that the optimal angle, where dirt accumulation was reduced, the rainfall cleaning and relative gains were optimized is in the range between 20° and 30°.
Design and thermo-energetic evaluation of a solar building heating system
Authors: González S M , Hernández A L 
Published: February 2022

Abstract
This paper presents the design, construction and thermo-energetic evaluation of a solar building heating system consisting of a double-pass counter-current solar air heating collector with porous matrix and a water-bed heat storage unit connected to a prototype building located at the National University of Salta, Argentina. The experimental study determined that the solar collector has an average daily efficiency of 37 % while the storage unit has an average daily efficiency of 38 %. The overall daily efficiency of the complete system is 18 %. During the test period, the night-time discharge of the storage unit ensured that the temperature of the room to be heated was always above 20 °C when the outside temperature was between 10 and 15 °C.
A general study of designing an electromagnetic induction cooking device prototype for microgrids in rural areas
Authors: Carbajal X , Sal y Rosas D 
Published: February 2022

Abstract
This paper presents a general study of designing an electromagnetic induction cooking device connected to batteries that operates in remote rural zones microgrids. For this work, the analytical and simulation modeling is carried out to obtain parameters of the equivalent impedance. Therefore, a full-bridge series-resonant (FBSR) DC/AC converter is designed at a specified operating frequency. The results obtained analytically are compared with the experimental data to verify the output power load and temperature measurement of the prototype.
Application of a bioclimatic tool for the hygrothermal analysis of a historic building in Lima-Peru
Authors: Alvarez S , Lefebvre G 
Published: February 2022

Abstract
The main objective of this paper is to know and analyze the bioclimatic strategies that would be present in colonial residential architecture in Lima. The knowledge and use of systems to achieve certain climate conditions in ancient buildings made of sun-dried bricks and thatch, both in open and closed spaces. We consider that through trial-and-error approaches, techniques would have been developed to obtain indoor comfort considering local climate conditions, available materials and other cultural conditions. Temperature, humidity and air speed measurements were taken three times a day during four days in some places of the building. Givoni’s building bioclimatic chart is used to analyze the performance of the places measured. On the one hand, different climate conditions were recorded in each patio and would be the result of its physical characteristics. In addition, differences between the performance of social spaces and private rooms were observed due to different ventilation strategies.
Modeling the effect of roof coatings materials on the building thermal temperature variations based on an artificial intelligence
Authors: May Tzuc O. , Hernandez-Pérez I. , Castro Karla M Aguilar , Jiménez Torres M. , Castillo-Téllez M , Demesa López N 
Published: February 2022

Abstract
This paper presents the benefits of applying the artificial neural networks technique to model the building indoor temperature variations caused by implementing roof coatings. Four of the most common roof coating used in Mexican constructions were considered. The study evaluated test cells at outdoors and instrumented them to measure the indoor temperature variation. The environmental parameters solar radiation, wind speed, ambient temperature, and relative humidity were also monitored. The results showed the viability of modeling the thermal behavior generated by the roof coatings with an accuracy greater than 90%. It implies the ability to predict internal temperatures based on the physical properties of the material and environmental variables, being a feasible tool in the search for thermal comfort for buildings in the region. In addition, the results of the sensitivity analysis identified to what extent to improve the optical properties of the material impact on the heat transferred to the interior.
Energy analysis of a nZEB standard residential building: case study in Rio de Janeiro
Authors: Vitória V H , Meiriño M J , Figueiredo G 
Published: February 2022

Abstract
This research aims to identify the technical feasibility of the concept of Nearly Zero Energy Building according to Brazilian standards and climatic conditions. The analysis was performed under the most up-to-date normative references and through computational energy simulation via EnergyPlus software, focusing on the building envelope model of a residential building in Rio de Janeiro. A reference model and five other construction models common in the national market were analyzed in two scenarios: firstly, in terms of natural ventilation only, and then using natural ventilation alternating with artificial cooling. Although those models were shown to be in the scope of international benchmarks about energy consumption in warm climate areas, some models stood out. In this case, the model with the lowest energy consumption presented results 22% lower than the reference model. This model was then associated with a supply of solar photovoltaic energy in order to apply one of the fundamental requirements of nZEB: the use of renewable energy sources. The results show the potential for nZEB implementation in Brazil.
Is the information provided by free satellite sources suitable for predicting or evaluating the performance of photovoltaic systems in Peru? (In memoriam to Heinrich Berg)
Authors: Espinosa-González C A , Angulo J R , Conde L A , Carhuavilca A M , Alfaro E F , Espinoza R , Töfflinger J A , Muñoz-Cerón E , de la Casa J 
Published: February 2022

Abstract
At present, there are free access online platforms that offer, free of charge, meteorological data on Peru; however, there is no study that validates the goodness of its use in the country. These types of tools are of the utmost interest, both in the design phase of photovoltaic systems PV and in the subsequent process of analysis and evaluation of their operation if it is intended to implement monitoring systems with Class B or C precision defined in the IEC 61724: 2017 standard. In this work, the consistency of the data offered by any of these platforms and their usefulness will be analysed when they are contrasted with experimental data on the operation of real systems.
Remaining Useful Life Prediction of Turbofan Engine Based on Temporal Convolutional Networks Optimized by Genetic Algorithm
Authors: Chen Zhengkun , Chen Baojia , Chen Xueliang 
Published: February 2022

Abstract
It is tough to select the parameters of the deep neural network and enhance the accuracy in the field of remaining useful life (RUL) prediction. To address the problem, one RUL prediction model optimized by a genetic algorithm, based on temporal convolutional networks (TCN), was proposed. Firstly, forward-filling sliding sampling is used to add the samples’ time step. Then the genetic algorithm is used to search the hyperparameters of the residual block of TCN. Finally, the performance of the proposed method is verified by the C-MAPSS dataset. The results show that in the two evaluation metrics of root mean square error (RMSE) and score function (SF), the proposed GA-TCN reduces them by 8.2% ∼ 27.56% and 28.24% ∼ 79.35%, respectively, when compared with other studies. The RMSE and SF metrics of the proposed method are on average 17.10% and 54.10% lower than that of other methods in four sub-datasets of the turbofan engine.
A reinforcement learning algorithm for the 2D-rectangular strip packing problem
Authors: Zhao Xusheng , Rao Yunqing , Fang Jie 
Published: February 2022

Abstract
The 2D packing problem is categorized as one branch of the cutting and packing problems, which is widely spread in the manufacturing industries. Over the years many meta­heuristics have been proposed and applied on the packing problem. Recently, the approach combined with machine learning serves as a novel paradigm for solving the combinatorial optimization problem. However, the machine learning approaches have very limited literature reports on the appliance of the packing problem. We propose a reinforcement learning method for the 2D-rectangular strip packing problem. The solution is represented by the sequence of the items and the layout is constructed piece by piece. We use the lowest centroid placement rule for the piece placement, then a Q-learning based sequence optimization is applied. Three groups of conditions are set for the testing, the computational results show the Q-learning approach has good effect on the compaction of the layout.
A new algorithm for location parameter estimation in DTV ground broadcast network
Authors: Bao Songjian 
Published: February 2022

Abstract
In the city, terrestrial digital TV network is the most perfect TV network, so the location of terrestrial broadcast signal based on digital TV has become one of the research hots-pots in recent years. Because multi-path in DTV wireless channel will cause serious signal fading, it becomes more difficult to detect DTV signal in the process of positioning, which directly affects the accuracy of positioning. Therefore, how to improve the detection accuracy of DTV signal through parameter estimation has become the focus of this paper. Based on the detailed study of DTV system based on wireless transmission channel characteristics and system structure, through the analysis based on linear least square (LS) channel estimation algorithm, the advantages and disadvantages of interference elimination is given based on the data, a new method of channel estimation, the simulation results verify the algorithm presented in this paper can well improve the channel estimation performance.
Target Detection Based on Deep Learning
Authors: Zhu Yuchen 
Published: February 2022

Abstract
As an important research direction of computer vision, target detection has been widely used in face recognition, intelligent driving, robot navigation and other fields. In recent years, with the deepening research on deep learning, great progress has been made in the field of computer vision, such as image acquisition, image processing and target detection. Compared with the traditional target detection algorithm based on candidate regions, it has the problems of poor timeliness and slow detection speed. Recently, the popular target detection algorithm based on regression realizes the real sense of end-to-end detection and greatly improves the detection efficiency. However, the accuracy of small target detection and dense target detection has not been solved. In the future, we still need to improve the efficiency and accuracy of recognition on the existing basis, and solve the problem of small target and dense target detection to make it more widely used in practical application scenarios. In this paper, the principle, advantages and disadvantages, accuracy and other aspects of the above algorithms are introduced in detail, the problems existing in the target detection algorithm are summarized, and the future development direction has been prospected. In short, both algorithms have advantages and disadvantages, but the regression-based target detection algorithm has better practicality and development prospects.
Phase-locked subdivision method of digital signal based on FPGA
Authors: Hou Han , Cao Guohua , Ding Hongchang , Li Kun , Wang Aijia 
Published: February 2022

Abstract
In order to improve the accuracy and real-time performance of the subdivision signal expression result of the photoelectric encoder in the signal dynamic measurement process, a phase-locked subdivision method of digital signal based on FPGA is proposed. The open-loop structure is used to realize the large-range detection of the grating measurement system, and the fractional frequency division method is used to realize the subdivision function of the grating moiré signal. In order to verify the effectiveness of the design, we compare the analog signal subdivision with the traditional digital phase-locked subdivision method. The experimental results show that the digital phase-locked subdivision algorithm designed in this paper can be used in the high-frequency moiré signal frequency and rate of change. The subdivision function is realized under the following conditions, which can be better applied to dynamic measurement occasions.
Research on the Distribution Strategy of Longitudinal Driving Force of Vehicle Driven by 8×8 In-wheel Motors
Authors: Yao Yifan , Li Erkang , Peng Chunlei 
Published: February 2022

Abstract
In order to meet the driving requirements of 8×8 in-wheel motor-driven vehicles, and to improve the adhesion performance of the vehicle at the same time, using the characteristics that each wheel can be controlled independently, a driving force distribution algorithm based on the optimal load of adhesion performance is designed. The mathematical model of the vehicle dynamics and the driving force distribution algorithm are built in Matlab/Simulink, and the effectiveness of the algorithm is verified through simulation tests, that is, it can meet the driver’s longitudinal dynamics requirements, take into account the limitations of the road and the motor, and reduce the load of the adhesion.
Optimization of composite cylinder shell via a data-driven intelligent optimization algorithm
Authors: Chen Ming , Zhang Xinhu , Shen Kechun , Pan Guang 
Published: February 2022

Abstract
While composite material provides huge flexibility for design, the design optimization of composite structure is time consuming with low efficiency. This work combines finite element analysis for composite cylinder shell with a data-driven intelligent optimization algorithm (Bayesian optimization algorithm) and is aimed at maximizing eigenvalue buckling load. Through minimizing number of iterations as a derivative-free global optimization algorithm, Bayesian optimization is versatile and can be further applied to design advanced composite structure with more complicated scenarios, such as complex geometries and load conditions.
The Concept of early monitoring and warning of thermal runaway of lithium-ion power battery using parameter analysis
Authors: Gao Ao , Xu Fang , Dong Wenhui 
Published: February 2022

Abstract
Considering the key factors affecting the fire rescue of lithium-ion power battery, such as timely early warning, monitoring, delaying the runaway process and sharing the causes of safety accidents, this paper analyses the thermal runaway mechanism of lithium-ion power battery. In addition, this paper puts forward the intelligent fire safety design of lithium-ion power battery, from the real-time monitoring technology of lithium-ion power battery safety, to bring the fire safety of lithium-ion power battery into the urban intelligent fire protection system.
Development of Parametric Modeling and Finite Element Analysis System for Cylindrical Spiral Tension Spring
Authors: Pan Yunping , Ming Yili , Wan Wenzhe 
Published: February 2022

Abstract
The survey shows that there are few researches on automatic modelling and finite element analysis by changing the relevant parameters of cylindrical spiral tension springs. This paper discusses the method of combining parametric technology with finite element analysis, using Visual Studio 2010 as the system development platform and Visual Basic (VB) as the program development language to establish a VB window operation interface. Automated modelling is carried out through the input feature size, and the VB event-driven feature is used to link automated modelling and automated finite element analysis to establish a parametric design and finite element analysis system for cylindrical spiral tension springs.
Modelling and Simulation of a 3DOF End Effector for Material Handling with a Delta Robot
Authors: Musa Muhizi , Li JinLiang 
Published: February 2022

Abstract
In order to improve workspace and material handling system of the delta robot, This paper describes a design of an End-effector with 3 degrees of freedom (3DOF) which makes the End-effector more flexible and having sufficient range of working space. This End-effector will be mounted on a delta parallel robot to perform the desired task in handling materials accordingly. The robot is able to pick and place a given material to the right place and positioning as it is desired by the user. The methodology used to design this robot was based on 3 major components which are: Sliding rails which deals with translational motion along horizontal axis, this motion carries the whole system from side to side and is going to play a role of increasing workspace in either assembling line or picking and placing system. Delta robot is in charge of manipulating its end effector in 3 dimensions along (x, y, z - axis) according to the object tracking localization as a human’s arm manipulate the hand. The end effector’s purpose is to perform rotational motion then pick the object and place as the system requires, this performance has advantage of handling materials and positioning respectively. It showed that the proposed system is safe and is feasible for application. The proposed material handling system can minimize the disadvantages of utilizing a delta robot by attachment of the presented end-effector to the delta robot.
Path Planning Method of Mobile Robot Based on Q-learning
Authors: Jiang Qi 
Published: February 2022

Abstract
With the progress of science and technology, mobile robots gradually play an increasingly important role in the industry, military, science and technology and other fields. Aiming at the core problem of path planning in the path planning of mobile robots, this paper studies and designs a path planning method based on a Q-learning algorithm. Q-learning is widely used in robot path planning, as it only needs the interaction between the current state and the environment to make rewards and punishments for robot actions, to make decisions on the next action. Aiming at the problems of low efficiency and slow convergence in the original Q-learning algorithm, this paper improved the algorithm to enable the robot to quickly complete the planning and get the optimal and shortest path. The grid method was used to establish the environment running program to visualize the convergence process and obtain data. Finally, software simulation is used to establish the environment and code the robot to simulate the real environment, which proves the practical value of the algorithm.