Veneer drying is the manufacturing process in the plywood industry that most affects energy consumption and panel properties such as bonding and bending. Therefore, the veneer drying temperature and ...moisture content should be accurately adjusted. Moreover, the determination of veneer thermal conductivity is as important as these two parameters and the thermal conductivity values should also be specifi ed when forming the drying programs. This study aimed to predict the optimum values of the veneer drying temperatures, moisture content and thermal conductivity, which gave the best mechanical properties, by artifi cial neural network (ANN) analysis. Poplar (Populus deltoidesI-77/51) and spruce (Picea orientalis L.) veneers and urea formaldehyde (UF) resin were used in the production of plywood. The thermal conductivity of veneer and the bonding, bending strength and elasticity modulus of the panels were tested by the relevant standards. The most accurate and reliable prediction models were obtained by analyzing the experimental data with ANN. The optimum veneer drying temperature, moisture content and thermal conductivity values that gave the best values for all three mechanical properties were 149 °C, 6.2 % and 0.02668 W/mK for poplar and 116 °C, 4.4 % and 0.02534 W/mK for spruce.
Sušenje furnira proizvodni je proces u industriji furnirskih ploča koji najviše utječe na potrošnju energije i svojstva ploče kao što su čvrstoća lijepljenja i savijanja. Stoga je potrebno točno prilagoditi temperaturu sušenja i sadržaj vode u furniru. Nadalje, određivanje toplinske vodljivosti furnira jednako je važno kao temperatura sušenja i sadržaj vode, pa je pri izradi programa sušenja potrebno specificirati i vrijednosti toplinske vodljivosti. Cilj ovog istraživanja bio je primjenom umjetne neuronske mreže (ANN) predvidjeti vrijednosti optimalne temperature sušenja, sadržaja vode i toplinske vodljivosti furnira koje će rezultirati najboljim mehaničkim svojstvima ploče. Za potrebe ispitivanja furnirske su ploče proizvedene od furnira topolovine (Populus deltoidesI-77/51) i furnira smrekovine (Picea orientalis L.) te su slijepljeni urea formaldehidnom smolom (UF). Prema odgovarajućim standardima ispitani su toplinska vodljivost i čvrstoća lijepljenja furnira te čvrstoća na savijanje i modul elastičnosti ploča. Najtočniji i najpouzdaniji modeli predviđanja dobiveni su analizom eksperimentalnih podataka uz pomoć umjetne neuronske mreže. Optimalne vrijednosti temperature sušenja, sadržaja vode i toplinske vodljivosti uz koje se postižu najbolja mehanička svojstva za furnirske ploče od topolovine iznosile su 149 °C, 6,2 % i 0,02668 W/mK, a za furnirske ploče od smrekovine 116 °C, 4,4 % i 0,02534 W/mK.
•Pedotransfer function (PTF) was developed to estimate the soil water retention curve.•The extended evaporation method (HYPROP system) was used to generate high resolution water retention data.•The ...pseudo continuous PTFs were developed using artificial neural networks.
HYPROP (Hydraulic Property Analyzer) system works based on the simplified evaporation method, which determines soil hydraulic properties in the laboratory. This system simultaneously monitors the changes in weight of soil samples as well as the soil matric potential at two depths throughout a drying process governed by evaporation from the soil surface. In this study, we examined the performance of the pseudo continuous pedotranfer function (PC-PTF) to estimate the soil water retention curve (SWRC) using high resolution data measured by HYPROP system. The dataset consisted of 7963 measured water retention data points obtained from 81 Turkish soil samples from which 60%, 20% and 20% were randomly selected for training, cross-validation and test subsets, respectively. The best PC-PTF developed in this study with a mean absolute error of 0.023 m3 m−3 (a root mean square error of 0.033 m3 m−3) and a correlation coefficient of 0.96 showed promising performance considering the typical performance range (RMSE = 0.034–0.085 m3 m−3) for parametric PTFs estimating SWRC. The best PC-PTF used soil textural information, soil bulk density, the percentage of stable aggregates, soil organic matter content and the initial water content as the input attributes. PTFs developed in this study also ranked high among previously developed PC-PTFs (with RMSE ranging from 0.027 to 0.056 m3 m−3) using sparse datasets collected via the traditional equilibrium approach (i.e. sandbox apparatus /pressure plates extractor). We, therefore, recommend further application of the PC-PTF approach for development of PTFs using high resolution data obtained by HYPROP system.
The fundamental objective of engineering is to design a structural system at minimum cost. Moreover, it is crucial that the algorithms used to achieve this objective be stable and fast. In a ...comparative study of optimization algorithms, the simulation environments should be standardized, sufficient competitors should be used, and algorithms should be examined in terms of stability and computational complexity. The goal of this research is to achieve the optimum design of reinforced concrete continuous beams at the lowest cost, which has been the topic of numerous studies, and to thoroughly evaluate the performance of selected metaheuristic algorithms for this problem. To achieve this goal, a benchmark suite of problems with various numbers of spans was created, and a two-phase research process was followed. The simulation environment was created in a fair and standardized manner. In the first phase, the ability of the twenty-five metaheuristic algorithms to determine optimal designs was examined, feasible solutions were identified, and the top five competitive algorithms were determined. In the second phase, the stability and computational complexity of competitive algorithms were evaluated. This is the first extensive investigation of continuous beam problems (CBPs). The statistical analysis revealed that COA, SOS, SFS, GSK, and TS were the five competitive algorithms. According to the stability analysis results, COA was found to be the most stable algorithm for one- and two-span CBPs, whereas SFS was the most stable algorithm for three-span CBP. The SOS algorithm achieved a feasible solution for all problems within the shortest time based on the computation duration. According to the success-duration distance (SDD) metric introduced for the first time in this study, the COA algorithm is recommended for use in the optimal design of CBPs.
Click here for the simulation environment containing the problem tools of the CBP benchmark suite:https://www.mathworks.com/matlabcentral/fileexchange/160641-rc-continuous-beam-problems-cbps-benchmark-suite
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•Parameters affecting Marsh-funnel flow time and mini-slump of paste mixtures were determined.•The study was carried out with two different approaches as experimental and ...modeling.•214 paste mixtures containing different cement/HRWR were prepared.•Admixture content and cement fineness were found to be the most important parameters.
In this study, the parameters affecting Marsh-funnel flow time and mini-slump of the paste mixtures were determined through experimental and modelling studies. Marsh-funnel flow times were modelled through artificial intelligence and regression methods. A novel model was used to train the coefficients of artificial neural networks (ANN) with the Teaching-Learning Based Artificial Bee Colony (TLABC) Algorithm. Accuracy of this method was investigated through ANN-Back Propagation, ANN-Teaching Learning Based Optimization Algorithm, ANN-Artificial Bee Colony, Multivariate Adaptive Regression Splines and Classical Regression Analysis methods. ANN-TLABC method showed the best results among the applied models. The admixture content, cement fineness, solid material content of admixture and C3A content of cement were found to be the most important parameters affecting the flowability of the paste. However, C2S, equivalent alkali, C4AF and C3S contents of the cement were observed to have no considerable effect on the Marsh-funnel flowability of paste.
•Four grasses were compared as bioenergy crops under different managements.•The highest dry biomass and net energy yields were achieved by giant reed.•The highest energy ratio was achieved by bulbous ...canary grass.•Winter harvest improved biomass quality of miscanthus, switchgrass and giant reed.•Crop biomass and energy yields were optimized with none or low nitrogen input.
Perennial grasses have received particular attention as bioenergy crops in recent years due to their high biomass productivity and environmental benefits. The objective of the present study was to compare four perennial grasses: miscanthus (Miscanthus x giganteus Keng), switchgrass (Panicum virgatum L.), giant reed (Arundo donax L.), and bulbous canary grass (Phalaris aquatica L.) in terms of biomass yield, energy balance, and biomass quality under four nitrogen fertilization rates (0, 100, 150, 200 kg ha–1y–1) and 2 harvest times (autumn, winter) over three growing seasons in the Mediterranean environment of Turkey. The crop biomass and net energy yields were optimized with none or 100 kg ha–1 y–1 N input in the study. Although the winter harvest resulted in significant yield reductions in all of the grass species, it improved the biomass quality of miscanthus, switchgrass, and giant reed due to reduced moisture and ash contents. On the contrary, the autumn harvest resulted in a considerably lower moisture and ash contents in bulbous canary grass, mainly because of leaf defoliation the during summer dormancy period. Giant reed produced the highest average biomass yield (between 12.86 and 36.78 t ha–1) over the three years, followed by miscanthus (between 12.75 and 23.54 t ha–1), switchgrass (between 11.88 and 18.91 t ha–1), and bulbous canary grass (between 5.21 and 10.83 t ha–1). On the other hand, bulbous canary grass provided the highest average energy ratio (19.7–64.5) over the three years, due mainly to a lack of energy input for irrigation. These results suggest that satisfactory biomass production can be achievable from miscanthus, switchgrass, and giant reed in the semi-arid Mediterranean environment under adequate moist conditions, but the irrigation requirement increases the energy cost, thus decreasing the energy ratio. In this respect, bulbous canary grass may be evaluated as an alternative bioenergy crop in the dry marginal lands of Mediterranean for sustainable biomass production.
The primary objective of this study was to apply the ANN (artificial neural network) model with the ABC (artificial bee colony) algorithm to estimate annual hydraulic energy production of Turkey. ...GEED (gross electricity energy demand), population, AYT (average yearly temperature), and energy consumption were selected as independent variables in the model. The first part of the study compared ANN-ABC model performance with results of classical ANN models trained with the BP (back propagation) algorithm. Mean square and relative error were applied to evaluate model accuracy. The test set errors emphasized positive differences between the ANN-ABC and classical ANN models. After determining optimal configurations, three different scenarios were developed to predict future hydropower generation values for Turkey. Results showed the ANN-ABC method predicted hydroelectric generation better than the classical ANN trained with the BP algorithm. Furthermore, results indicated future hydroelectric generation in Turkey will range from 69.1 to 76.5 TWh in 2021, and the total annual electricity demand represented by hydropower supply rates will range from 14.8% to 18.0%. However, according to Vision 2023 agenda goals, the country plans to produce 30% of its electricity demand from renewable energy sources by 2023, and use 20% less energy than in 2010. This percentage renewable energy provision cannot be accomplished unless changes in energy policy and investments are not addressed and implemented. In order to achieve this goal, the Turkish government must reconsider and raise its own investments in hydropower, wind, solar, and geothermal energy, particularly hydropower.
•This study is associated with predicting hydropower generation in Turkey.•Sensitivity analysis was performed to determine predictor variables.•GEED, population, energy consumption and AYT were used as predictor variables.•ANN-ABC predicted the hydropower generation more accurately than classical ANN.•Using the ANN-ABC model, the hydropower generation was forecasted until 2021.
We propose an automated camera setup for photogrammetric roughness analysis in the laboratory environment. The developed fast and low-cost automation setup can be very useful for tedious and ...laborsome manual field logging practices. The photographs are processed in MATLAB to obtain disparity maps. Coding routines for stereo photogrammetry and digital measurements are written in MATLAB. Secondly, 6 effecting factors (projecting an image onto core face, depth of field, brightness, camera-to-object to baseline distance ratio, projected image size, and occlusion) influencing noise in roughness depth maps computed by employing stereo photogrammetry are investigated. After deciding the best values that allow the lowest amount of noise, depth maps of 6 core faces are computed. Using the 3D point cloud generated, roughness profile measurements are made. Then, 8 profile measurements are made for each core face, both manually and digitally. The accuracy of the disparity maps has been verified by comparing 48 joint roughness coefficient (JRC) measurements made manually using a profile gauge. It was proved that surface roughness can be measured very fast in millimetric accuracy with an average root mean square error (RMSE) of 3.50 and mean absolute error (MAE) of 3.02 by the help of the proposed set-up and calibration.
In this study, a robust adaptive controller is designed to be used in an active tuned mass damper system that can be used to damp undesired vibrations that occurred on the multistory buildings during ...the earthquake. To realize the controller design, all of the system parameters are assumed to be unknown, and the adaptive structure of the designed controller is obtained by designing adaptive compensation rules for system parameters. A backstepping control design approach is utilized for the control design by considering the appropriateness of the system’s structure of multistory buildings having an active tuned mass damper system at the top of the structure. The proposed control design is supported with a Lyapunov-based stability analysis where it is proven that the designed controller is able to protect the overall system’s stability while reaching the main control purpose. In addition to these, in the simulation studies realized for a nine-story building under the effect of a major earthquake, it is shown that the designed controller can be used to reach the main control purpose efficiently.
The high-speed railways require more viaduct than a conventional railway. When the viaduct is subjected to high-amplitude vibrations for a long time, the fatigue-induced crack formation can occur . ...The presence of a crack changes the stiffness of the structure. Depending on the location of the crack, the reduction effect in stiffness varies. In this study, the presence of a single crack in a multi-storey frame structure, which is considered as a viaduct model, has been investigated. Effects of crack location on the dynamic response are investigated via 3D velocity-crack location-dynamic magnification factor (or maximum displacement) graphs. The train is modelled as a four-axle two-bogie multi-body system with 10 DOF and moving at a constant speed. The finite element method, based on Euler–Bernoulli beam theory, is used to simulate the vibrations of the coupled vehicle-structure system. Wilson-theta time integration scheme is used to solve the equation of motion. It has been determined that when the crack is located at the midpoint of the top beam, the highest effect on the dynamic response is observed.
Active tuned mass damper (ATMD) devices are recommended in various structures to reduce vibrations. The performance of the ATMD system is closely tied to the control design utilized, according to ...research in the literature. The designed control input will take into account as much system dynamics as possible, making it possible to use it as a generalized controller in all similar systems. Nonlinear behavior is the natural behavior of engineering structures, and in order to obtain a more realistic and high-performance ATMD system, it can be considered as an appropriate approach to design the controller by considering the structural nonlinearities. In addition, unexpected external influences and parameter uncertainties must be taken into account during control design to ensure that control systems perform successfully in similar systems in all conditions. Therefore, in this study, the nonlinear model of the multi-story building was reconstructed by adding nonlinear disturbance to represent unknown external effects. Band-limited white noise is used as a disturbance function and Gaussian white noise is added to measured states in this study. To obtain a robust controller, unknown structural parameters are compensated for by using adaptive compensation terms. With the controller design supported by the Lyapunov-based stability analysis, the stability of the vibrating structure featuring an ATMD is theoretically guaranteed while achieving the main control goal. Performance analyses of the designed controllers are carried out with simulation studies. The efficiency of the developed Lyapunov-based controller in dampening the unwanted vibrations that occurred on the building is seen in simulation results.
