Water Absorption Capacity and Coating Adhesion on Thermally Modified and Not-Modified Spruce Wood(Blue Stained or Free of Blue Stained)

This study aimed to investigate the water absorption capacity of thermally modified and non-modified spruce and blue-stained spruce wood.The wettability of wood depends on various factors,including its type,density,porosity,and surface treatment.Wood can swell and become distorted when exposed to water or humidity,impacting its structural integrity.Hence,it is crucial to consider the water and water vapour uptake in the wood when choosing materials for applications that are likely to be exposed to moisture.Various moisture absorption tests were conducted to assess water absorption capacity,including short-term and long-term water absorption and water vapour absorption.The results showed a significant difference in the long-term exposure to water,which was related to the density of the wood.The study examined the influence of thermal treatment on the physical properties of wood and observed significant variations in mass change due to coating,indicating differences in adhesion among different wood types.Vacuum-treated blue-stained Norway spruce demonstrated higher adhesion(5%–15%)compared to air-treated samples.Furthermore,cohesion tests revealed lower cohesion force in blue-stained Norway spruce(approximately 20%–30%)compared to Norway spruce.The study also used industry-standard tests to investigate the adhesion and cohesion of nano-coatings on wood surfaces.The results provided valuable information on the properties of coatings applied to wood,which is vital in protecting and decorating wood while also providing preventive protection against wood pests,weathering,and mechanical influences.Wood modification in vacuum involves subjecting the wood to a low-pressure environment to remove air and moisture,allowing for deeper and more uniform penetration of treatment chemicals.In contrast,wood modification in air relies on the natural circulation of air to facilitate the absorption of chemical treatments,without the need for a vacuum chamber.

Optimal setting and placement of FACTS devices using strength Pareto multi-objective evolutionary algorithm

This work proposes a novel approach for multi-type optimal placement of flexible AC transmission system(FACTS) devices so as to optimize multi-objective voltage stability problem. The current study discusses a way for locating and setting of thyristor controlled series capacitor(TCSC) and static var compensator(SVC) using the multi-objective optimization approach named strength pareto multi-objective evolutionary algorithm(SPMOEA). Maximization of the static voltage stability margin(SVSM) and minimizations of real power losses(RPL) and load voltage deviation(LVD) are taken as the goals or three objective functions, when optimally locating multi-type FACTS devices. The performance and effectiveness of the proposed approach has been validated by the simulation results of the IEEE 30-bus and IEEE 118-bus test systems. The proposed approach is compared with non-dominated sorting particle swarm optimization(NSPSO) algorithm. This comparison confirms the usefulness of the multi-objective proposed technique that makes it promising for determination of combinatorial problems of FACTS devices location and setting in large scale power systems.

Design of hybrid damping controller based on multi-target gravitational search optimization algorithm in a multi-machine power system with high penetration of PV park

A mathematical approach was proposed to investigate the impact of high penetration of large-scale photovoltaic park(LPP) on small-signal stability of a power network and design of hybrid controller for these units.A systematic procedure was performed to obtain the complete model of a multi-machine power network including LPP.For damping of oscillations focusing on inter-area oscillatory modes,a hybrid controller for LPP was proposed.The performance of the suggested controller was tested using a 16-machine 5-area network.The results indicate that the proposed hybrid controller for LPP provides sufficient damping to the low-frequency modes of power system for a wide range of operating conditions.The method presented in this work effectively indentifies the impact of increased PV penetration and its controller on dynamic performance of multi-machine power network containing LPP.Simulation results demonstrate that the model presented can be used in designing of essential controllers for LPP.

Hyperparameter Tuning Bidirectional Gated Recurrent Unit Model for Oral Cancer Classification

Oral Squamous Cell Carcinoma(OSCC)is a type of Head and Neck Squamous Cell Carcinoma(HNSCC)and it should be diagnosed at early stages to accomplish efficient treatment,increase the survival rate,and reduce death rate.Histopathological imaging is a wide-spread standard used for OSCC detection.However,it is a cumbersome process and demands expert’s knowledge.So,there is a need exists for automated detection ofOSCC using Artificial Intelligence(AI)and Computer Vision(CV)technologies.In this background,the current research article introduces Improved Slime Mould Algorithm with Artificial Intelligence Driven Oral Cancer Classification(ISMA-AIOCC)model on Histopathological images(HIs).The presented ISMA-AIOCC model is aimed at identification and categorization of oral cancer using HIs.At the initial stage,linear smoothing filter is applied to eradicate the noise from images.Besides,MobileNet model is employed to generate a useful set of feature vectors.Then,Bidirectional Gated Recurrent Unit(BGRU)model is exploited for classification process.At the end,ISMA algorithm is utilized to fine tune the parameters involved in BGRU model.Moreover,ISMA algorithm is created by integrating traditional SMA and ChaoticOppositional Based Learning(COBL).The proposed ISMA-AIOCC model was validated for performance using benchmark dataset and the results pointed out the supremacy of ISMA-AIOCC model over other recent approaches.

Ensemble of Handcrafted and Deep Learning Model for Histopathological Image Classification

Histopathology is the investigation of tissues to identify the symptom of abnormality.The histopathological procedure comprises gathering samples of cells/tissues,setting them on the microscopic slides,and staining them.The investigation of the histopathological image is a problematic and laborious process that necessitates the expert’s knowledge.At the same time,deep learning(DL)techniques are able to derive features,extract data,and learn advanced abstract data representation.With this view,this paper presents an ensemble of handcrafted with deep learning enabled histopathological image classification(EHCDL-HIC)model.The proposed EHCDLHIC technique initially performs Weiner filtering based noise removal technique.Once the images get smoothened,an ensemble of deep features and local binary pattern(LBP)features are extracted.For the classification process,the bidirectional gated recurrent unit(BGRU)model can be employed.At the final stage,the bacterial foraging optimization(BFO)algorithm is utilized for optimal hyperparameter tuning process which leads to improved classification performance,shows the novelty of the work.For validating the enhanced execution of the proposed EHCDL-HIC method,a set of simulations is performed.The experimentation outcomes highlighted the betterment of the EHCDL-HIC approach over the existing techniques with maximum accuracy of 94.78%.Therefore,the EHCDL-HIC model can be applied as an effective approach for histopathological image classification.

Detection of butt weld of laser-MIG hybrid welding of thin-walled profile for high-speed train

Purpose–This study aims to solve the problem of weld quality inspection,for the aluminum alloy profile welding structure of high-speed train body has complex internal shape and thin plate thickness(2–4 mm),the conventional nondestructive testing method of weld quality is difficult to implement.Design/methodology/approach–In order to solve this problem,the ultrasonic creeping wave detection technology was proposed.The impact of the profile structure on the creeping wave detection was studied by designing profile structural test blocks and artificial simulation defect test blocks.The detection technology was used to test the actual welded test blocks,and compared with the results of X-ray test and destructive test(tensile test)to verify the accuracy of the ultrasonic creeping wave test results.Findings–It is indicated that that X-ray has better effect on the inspection of porosities and incomplete penetration defects.However,due to special detection method and protection,the detection speed is slow,which cannot meet the requirements of field inspection of the welding structure of aluminum alloy thin-walled profile for high-speed train body.It can be used as an auxiliary detection method for a small number of sampling inspection.The ultrasonic creeping wave can be used to detect the incomplete penetration welds with the equivalent of 0.25 mm or more,the results of creeping wave detection correspond well with the actual incomplete penetration defects.Originality/value–The results show that creeping wave detection results correspond well with the actual non-penetration defects and can be used for welding quality inspection of aluminum alloy thin-wall profile composite welding joints.It is recommended to use the echo amplitude of the 10 mm 30.2 mm 30.5 mm notch as the criterion for weld qualification.

Modelling and analysis of parameters of vacuum tube solar collector with U-shaped tube for different climates

In this study,based on the energy balance for different components of a double-layered vacuum-tube solar collector with a U-tube,the thermal performance of the collector unit is investigated separately using an analytical and quasi-dynamic method.The model used in this study determines the temperature distribution in longitudinal and radial directions.In this research,the effects of physical parameters and heat transfer including the size of the collector,thermal-loss coefficient,absorption coefficient,mass flow and thermal resistance of the air layer under different climate conditions have been evaluated on the performance of the vacuum-tube collector.The results showed that by increasing the diameter of the tube with constant length,the annual thermal efficiency of the collector increased.Also,in a fixed-diameter tube,with increasing tube length,the annual efficiency increases,but this increase is meagre for lengths of>1.5 m.The optimal mass flow rate for maximum efficiency has been obtained for cities with different climates.According to the results,the optimal flow for different climates has different values that can be optimized as a relationship between the average solar radiation annually as a symbol of temperature and flow.

Modelling and optimization of combined heat and power system in microgrid based on renewable energy

Due to the short distance between the sources of production and consumption,microgrids(MGs)have received considerable attention because these systems involve fewer losses and waste less energy.And another advantage of MGs is that renewable energy sources can be widely used because these resources are not fully available and can provide a part of the required power.The purpose of this research is to model the MG considering the production sources of microturbines,gas turbines and internal combustion engines.Renewable energies such as wind turbines(WTs)and photovoltaic(PV)cells have been used to provide part of the required power and,because of the lack of access to renewable energy sources at all times,energy reserves such as batteries and fuel cells(FCs)have been considered.The power of the microturbine,gas turbine,internal combustion engine,FC and battery in this system is 162,150,90,100 and 225 kW,respectively.After modelling the studied system,optimization was done using the imperialist competitive algorithm to minimize production costs and provide maximum thermal and electrical loads.The maximum production power for PVs is equal to 0.6860 MWh and at this time this value for WTs is equal to 0.3812 MWh,in which case the excess electricity produced will be sold to the grid.

Thermo-economic analysis of the performance of the combined system with evacuated tube collectors

Using combined cooling,heat and power systems can be an appropriate substitute for preventing emissions of pollutants and excessive consumption of fossil fuels.Utilizing renewable energy in these systems as a source of power generation can be an appropriate substitute for fossil-fuel-based systems.Therefore,in this paper,cogeneration cooling,heat and power systems based on gas-fired internal combustion engines with a solar-thermal system with evacuated tube collectors have been modelled and thermo-economic analysis has been done to compare fossil-fuel-based systems.The required rate of heat to supply the hot water is 50 kW.In the studied system,the internal combustion engine produces electrical energy.Then,the solar-thermal system with evacuated tube collectors and the gas-burning generator provide the thermal energy required by the studied building and the primary stimulus of the absorption chiller for cooling.In this study,two different scenarios are conducted in states considering simultaneous production systems and regardless of this environmental and thermo-economic analysis system.The results showed that the efficiency of the studied system was 60% in summer and 56% in winter.

An efficient hybrid evolutionary optimization algorithm based on PSO and SA for clustering

The K-means algorithm is one of the most popular techniques in clustering. Nevertheless, the performance of the Kmeans algorithm depends highly on initial cluster centers and converges to local minima. This paper proposes a hybrid evolutionary programming based clustering algorithm, called PSO-SA, by combining particle swarm optimization (PSO) and simulated annealing (SA). The basic idea is to search around the global solution by SA and to increase the information exchange among particles using a mutation operator to escape local optima. Three datasets, Iris, Wisconsin Breast Cancer, and Ripley's Glass, have been considered to show the effectiveness of the proposed clustering algorithm in providing optimal clusters. The simulation results show that the PSO-SA clustering algorithm not only has a better response but also converges more quickly than the K-means, PSO, and SA algorithms.

Attuned design of demand response program and M-FACTS for relieving congestion in a restructured market environment

This paper addresses the attuned use of multi- converter flexible alternative current transmission systems （M-FACTS） devices and demand response （DR） to perform congestion management （CM） in the deregulated environment. The strong control capability of the M- FACTS offers a great potential in solving many of the problems facing electric utilities. Besides, DR is a novel procedure that can be an effective tool for reduction of congestion. A market clearing procedure is conducted based on maximizing social welfare （SW） and congestion as network constraint is paid by using concurrently the DR and M-FACTS. A multi-objective problem （MOP） based on the sum of the payments received by the generators for changing their output, the total payment received by DR participants to reduce their load and M-FACTS cost is systematized. For the solution of this problem a nonlinear time-varying evolution （NTVE） based multi-objective particle swarm optimization （MOPSO） style is formed. Fuzzy decision-making （FDM） and technique for order preference by similarity to ideal solution （TOPSIS） approaches are employed for finding the best compromise solution from the set of Pareto-solutions obtained through multi-objective particle swarm optimization-nonlinear time-varying evolution （MOPSO-NTVE）. In a real power system, Azarbaijan regional power system of Iran, comparative analysis of the results obtained from the application of the DR ＆ unified power flow controller （UPFC） and the DR ＆ M-FACTS are presented.

Impact of partial slip condition on mixed convection of nanofluid within lid-driven wavy cavity and solid inner body

In thermofluid systems,the lid-driven square chamber plays an imperative role in analyzing thermodynamics’first and second laws in limited volume cases executed by sheer effects with a prominent role in many industrial applications including electronic cooling,heat exchangers,microfluidic components,solar collectors,and renewable energies.Furthermore,nanofluids as working fluids have demonstrated potential for heat transfer enhancement systems,however there are some concerns about irreversibility problems in the systems.Due to this problem and in line with the applications of partial slip on fluid flow modification and irreversibilities,the present study considers laminar mixed convection and entropy generation analysis of aluminum oxide nanofluid inside a lid-driven wavy cavity having an internal conductive solid body in the presence of a partial slip on the upper surface,which to the best of our knowledge,has not been investigated so far.The fundamental equations of the current work with the appropriate boundary conditions are first made dimensionless and then solved numerically using the Galerkin weighted residual FEM.The main parameters of the flow and heat transfer,entropy generation,and Bejan number are presented and explained in details.The outcomes indicate that the partial slip is more effective when friction irreversibilities govern the cavity.In the presence of slip condition,the flow circulation changes the trend in the middle of the cavity around the solid block leading to a decrease in the isentropic lines at the dense sections with almost 30%less than the case of no-slip condition.It is concluded that partial slip shows different trends on the local Nusselt number interface along the wavy wall improving the average Nusselt number where high friction irreversibilities dominate.

Parametric investigation of thermal behaviour of salt-gradient solar pool for climatic conditions

The use of solar energy is highly welcomed due to its availability everywhere.Among the types of solar energy technologies,the use of this type of energy to produce heat from different aspects is much more common,so in this research we have tried to examine different aspects of producing thermal energy from solar energy to supply the heat required by the pool.For this purpose,numerical modelling of the solar pool has been done by considering the heat-transfer characteristics and validation has been done to ensure the obtained results.In this paper,according to the physical realities facing solar systems in two scenarios,an analysis with shadow and without shadow has been done.One of the important results is that as the surface of the pool increases,the amount of heat absorption by the pool fluid will increase,but the effect of the shadow will decrease.