Numerical treatment of thermal nanofluid flow for energy enhancement over a porous stretching sheet impact of slip and buoyancy force.

The advancement of nanofluid innovation is a crucial area of research for physicists, mathematicians, manufacturers, and materials scientists. In engineering and industries, the fluid velocity caused by stretching sheets and nanofluids has a lot of applications such as refrigerators, chips, heat exchangers, hybrid mechanical motors, food development, and so on. The originality of the current study is the analysis of the thermal nanofluid in the existence of a porous matrix, and buoyancy force over the stretched sheet, so in limiting cases, the existing work is equated with the available effort, and excellent correspondence is originated. The governing equations in terms of PDEs are changed to the convection differential by utilizing the appropriate transformation and then solved by the ND-solved method along with bvph2. The thermal boundary layer thickness upsurges as the radiation and temperature factors are improved. It is observed that with the growing amount of volume fraction factor the velocity profile declines. When the velocity slip factors and permeability are enhanced the velocity profile augments. It is examined as the values of permeability factor, Biot number, and velocity slip factor are increased the inner temperature of the fluid improves. For the increasing values of θ_r, ϕ, and Nr, the temperature is increasing. In the future, the present model can be extended by using the hybrid nanofluid for the activation of thermal conductivity and heat enhancement analysis.

Techno-economic optimization of a new waste-to-energy plant for electricity, cooling, and desalinated water using various biomass for emission reduction.

A newly developed waste-to-energy system using a biomass combined energy system designed and taken into account for electricity generation, cooling, and freshwater production has been investigated and modeled in this project. The investigated system incorporates several different cycles, such as a biomass waste integrated gasifier-gas turbine cycle, a high-temperature fuel cell, a Rankine cycle, an absorption refrigeration system, and a flash distillation system for seawater desalination. The EES software is employed to perform a basic analysis of the system. They are then transferred to MATLAB software to optimize and evaluate the impact of operational factors. Artificial intelligence is employed to evaluate and model the EES software's analysis output for this purpose. By enhancing the flow rate of fuel from 4 to 6.5 kg/s, the cost rate and energy efficiency are reduced by 51% and increased by 6.5%, respectively. Furthermore, the maximum increment in exergetic efficiency takes place whenever the inlet temperature of the gas turbine rises. According to an analysis of three types of biomasses, Solid Waste possesses the maximum efficiency rate, work output, and expense. Rice Husk, in contrast, has the minimum efficiency, work output, and expense. Additionally, with the change in fuel discharge and gas turbine inlet temperature, the system behavior for all three types of biomasses will be nearly identical. The Pareto front optimization findings demonstrate that the best mode for system performance is an output power of 53,512 kW, a cost of 0.643 dollars per second, and a first law efficiency of 42%. This optimal value occurs for fuel discharge of 5.125 and the maximum inlet temperature for a gas turbine. The rates of water desalination and cooling in this condition are 18.818 kg/s and 2356 kW, respectively.

Deep learning-based framework for real-time upper limb motion intention classification using combined bio-signals.

This research study proposes a unique framework that takes input from a surface electromyogram (sEMG) and functional near-infrared spectroscopy (fNIRS) bio-signals. These signals are trained using convolutional neural networks (CNN). The framework entails a real-time neuro-machine interface to decode the human intention of upper limb motions. The bio-signals from the two modalities are recorded for eight movements simultaneously for prosthetic arm functions focusing on trans-humeral amputees. The fNIRS signals are acquired from the human motor cortex, while sEMG is recorded from the human bicep muscles. The selected classification and command generation features are the peak, minimum, and mean ΔHbO and ΔHbR values within a 2-s moving window. In the case of sEMG, wavelength, peak, and mean were extracted with a 150-ms moving window. It was found that this scheme generates eight motions with an enhanced average accuracy of 94.5%. The obtained results validate the adopted research methodology and potential for future real-time neural-machine interfaces to control prosthetic arms.

An innovative biomass-driven energy systems for green energy and freshwater production with less CO2 emission: Environmental and technical approaches.

Considering the current crisis of fossil energies, the exploitation of renewables and green technologies is necessary and unavoidable. Additionally, the design and development of integrated energy systems with two or more output products and the maximum usage of thermal losses in order to improve efficiency can boost the yield and acceptability of the energy system. In this regard, this paper develops a comprehensive multi-aspect assessment of the operation of a new solar and biomass energies-driven multigeneration system (MGS). The main units installed in MGS are three electric energy generation units based on a gas turbine process, a solid oxide fuel cell unit (SOFCU) and an organic Rankine cycle unit (ORCU), a biomass energy conversion unit to useful thermal energy, a seawater conversion unit into useable freshwater, a unit for converting water and electricity into hydrogen energy and oxygen gas, a unit for converting solar energy into useful thermal energy (based on Fresnel collector), and a cooling load generation unit. The planned MGS has a novel configuration and layout that has not been considered by researchers recently. The current article is based on presenting a multi-aspect evaluation to study thermodynamic-conceptual, environmental and exergoeconomic analyzes. The outcomes indicated that the planned MGS can produce about 6.31 MW of electrical power and 0.49 MW of thermal power. Furthermore, MGS is able to produce various products such as potable water (∼0.977 kg/s), cooling load (∼0.16 MW), hydrogen energy (∼1.578 g/s) and sanitary water (∼0.957 kg/s). The total thermodynamic indexes were calculated as 78.13% and 47.72%, respectively. Also, the total investment and unit exergy costs were 47.16 USD per hour and 11.07 USD per GJ, respectively. Further, the content of CO2 emitted from the desgined system was equal to 10.59 kmol per MWh. A parametric study has been also developed to identify influencing parameters.

Techno-economic analysis and optimization of near-zero energy and emission neighborhoods using biomass waste.

The present study aims to simulate and design a near-Zero Energy neighborhood in one of the most significant industrial cities for reducing greenhouse gas emissions. For this building, biomass wastes are used for energy production, and also energy storage is provided using a battery pack system. Additionally, the Fanger model is used to assess the passengers' thermal comfort, and information on hot water usage is given. The transient performance of the aforementioned building is tested for one year using TRNSYS software, which was employed for this simulation. Wind turbines are considered electricity generators for this building, and any extra energy generated is stored in a battery pack for usage when the wind speed is insufficient and electricity is needed. Hot water is created using a biomass waste system and is kept in a hot water tank after being burned using a burner. A humidifier is utilized to ventilate the building, and a heat pump provides both the building's heating and cooling needs. The produced hot water is used to supply the residents' hot water. In addition, The Fanger model is considered and used for the assessment of occupants' thermal comfort. Matlab software is a powerful software used for this task. According to the findings, a wind turbine with a 6 kW generation capacity may supply the building's power needs while also charging the batteries beyond their initial capacity, and the building will have zero energy. Additionally, biomass fuel is used to give the building the required water which should be hot. On average, 200 g of biomass and biofuel are used per hour to maintain this temperature.

Parametric Investigation and Optimization to Study the Effect of Process Parameters on the Dimensional Deviation of Fused Deposition Modeling of 3D Printed Parts.

Fused deposition modeling (FDM) is the most economical additive manufacturing (AM) technology available for fabricating complex part geometries. However, the involvement of numerous control process parameters and dimensional instabilities are challenges of FDM. Therefore, this study investigated the effect of 3D printing parameters on dimensional deviations, including the length, width, height, and angle of polylactic acid (PLA) printed parts. The selected printing parameters include layer height, number of perimeters, infill density, infill angle, print speed, nozzle temperature, bed temperature, and print orientation. Three-level definitive screening design (DSD) was used to plan experimental runs. The results revealed that infill density is the most consequential parameter for length and width deviation, while layer height is significant for angle and height deviation. The regression models developed for the four responses are non-linear quadratic. The optimal results are obtained considering the integrated approach of desirability and weighted aggregated sum product assessment (WASPAS). The optimal results include a layer height of 0.1 mm, a total of six perimeters, an infill density of 20%, a fill angle of 90°, a print speed of 70 mm/s, a nozzle temperature of 220 °C, a bed temperature of 70 °C, and a print orientation of 90°. The current study provides a guideline to fabricate assistive devices, such as hand and foot orthoses, that require high dimensional accuracies.

Effect of Ranque-Hilsch Vortex Tube Cooling to Enhance the Surface-Topography and Tool-Wear in Sustainable Turning of Al-5.6Zn-2.5Mg-1.6Cu-0.23Cr-T6 Aerospace Alloy.

The aerospace metal cutting industry's search for environmentally friendly practices that do not compromise machining performance is well known. One of the major objectives is the reduction in use of cutting fluids, which play a major role in containing the harsh effects of severe heat generated during machining. Machining performance and product quality can be improved by controlling heat during machining. The purpose of this study was to determine the effectiveness of various environmentally friendly metalworking fluid (MF) strategies for the sustainable turning of aerospace aluminum alloy (Al-5.6Zn-2.5Mg-1.6Cu-0.23Cr-T6) for automotive, marine, and aerospace industrial applications. The SEM images were analyzed for worn tool surfaces and machined surfaces. Under dry conditions, heat does not dissipate well, and will enter the workpiece due to the absence of coolant. This causes extreme damage beneath a turned workpiece. Thus, at 10 µm, a drop in microhardness of approximately 20% can be observed. A similar observation was made in a Ranque-Hilsch vortex tube (RHVT) and in compressed air; however, the drop in hardness was relatively low compared to dry conditions. This evaluation of microhardness indicated a heat-based attention in the turned workpiece, and thus, the heat-based effect was found to be lowest in RHVT and compressed air compared to dry conditions. Results showed that RHVT reduces temperature up to 10%, surface roughness 13%, and tool wear 20% compared to dry turning. Overall, RHVT was identified as more effective environmentally friendly cooling strategy than dry and compressed air for the turning of aluminum alloy 7075-T6.

Experimental and Statistical Analysis of Saw Mill Wood Waste Composite Properties for Practical Applications.

The utilization of composite materials is increasing at a growing rate in almost all types of products, due to their strength-to-stiffness ratio. From this perspective, natural waste composites, i.e., wood waste composites, have also been investigated for their effective and sustainable employment. This paper deals with the application of hard and soft wood waste (i.e., acacia and cedar wood) with epoxy resin polymer to develop high strength and thermally stable wood composites. Mechanical (tensile, flexural, impact, and hardness) and thermal properties of samples are studied using Differential Scanning Calorimeter (DSC) and Thermo Gravimetric Analysis (TGA), respectively. The properties are evaluated by varying the type of wood waste and its percentage by weight. Based on the Taguchi Orthogonal Array Mixture Design, eighteen experiments are investigated. Analysis of variance (ANOVA) results show that wood waste type and wood waste content have a significant effect on all mechanical properties. From the TGA analysis, it is predicted that both types of wood waste composites exhibit similar thermal-induced degradation profiles in terms of the initial and final degradation temperatures. From the DSC results, higher glass transition temperature Tg is detected in 10% of the hardwood waste composite, and a reducing tendency of glass transition temperature Tg is observed with exceeding wood waste content. Moreover, hardwood waste at 10% demonstrated improved decomposition temperature Td, due to strong adhesion between waste and matrix.

Investigating Optimal Confinement Behaviour of Low-Strength Concrete through Quantitative and Analytical Approaches.

Reinforced concrete is used worldwide in the construction industry. In past eras, extensive research has been conducted and has clearly shown the performance of stress-strain behaviour and ductility design for high-, standard-, and normal-strength concrete (NSC) in axial compression. Limited research has been conducted on the experimental and analytical investigation of low-strength concrete (LSC) confinement behaviour under axial compression and relative ductility. Meanwhile, analytical equations are not investigated experimentally for the confinement behaviour of LSC by transverse reinforcement. The current study experimentally investigates the concrete confinement behaviour under axial compression and relative ductility of NSC and LSC using volumetric transverse reinforcement (VTR), and comparison with several analytical models such as Mander, Kent, and Park, and Saatcioglu. In this study, a total of 44 reinforced-column specimens at a length of 18 in with a cross-section of 7 in × 7 in were used for uniaxial monotonic loading of NSC and LSC. Three columns of each set were confined with 2 in, 4 in, 6 in, and 8 in c/c lateral ties spacing. The experimental results show that the central concrete stresses are significantly affected by decreasing the spacing between the transverse steel. In the case of the LSC, the core stresses are double the central stress of NSC. However, increasing the VTR, the capacity and the ductility of NSC and LSC increases. Reducing the spacing between the ties from 8 in to 2 in center to center can affect the concrete column's strength by 60% in LSC, but 25% in the NSC. The VTR and the spacing between the ties greatly affected the LSC compared to NSC. It was found that the relative ductility of the confined column samples was almost twice that of the unrestrained column samples. Regarding different models, the Manders model best represents the performance before the ultimate strength, whereas Kent and Park represents post-peak behaviour.

Numerical Modeling and Analysis of Ti6Al4V Alloy Chip for Biomedical Applications.

The influence of cutting forces during the machining of titanium alloys has attained prime attention in selecting the optimal cutting conditions to improve the surface integrity of medical implants and biomedical devices. So far, it has not been easy to explain the chip morphology of Ti6Al4V and the thermo-mechanical interactions involved during the cutting process. This paper investigates the chip configuration of the Ti6Al4V alloy under dry milling conditions at a macro and micro scale by employing the Johnson-Cook material damage model. 2D modeling, numerical milling simulations, and post-processing were conducted using the Abaqus/Explicit commercial software. The uncut chip geometry was modeled with variable thicknesses to accomplish the macro to micro-scale cutting by adapting a trochoidal path. Numerical results, predicted for the cutting reaction forces and shearing zone temperatures, were found in close approximation to experimental ones with minor deviations. Further analyses evaluated the influence of cutting speeds and contact friction coefficients over the chip flow stress, equivalent plastic strain, and chip morphology. The methodology developed can be implemented in resolving the industrial problems in the biomedical sector for predicting the chip morphology of the Ti6Al4V alloy, fracture mechanisms of hard-to-cut materials, and the effects of different cutting parameters on workpiece integrity.

Multi-Response Optimization of Tensile Creep Behavior of PLA 3D Printed Parts Using Categorical Response Surface Methodology.

Three-dimensional printed plastic products developed through fused deposition modeling (FDM) endure long-term loading in most of the applications. The tensile creep behavior of such products is one of the imperative benchmarks to ensure dimensional stability under cyclic and dynamic loads. This research dealt with the optimization of the tensile creep behavior of 3D printed parts produced through fused deposition modeling (FDM) using polylactic acid (PLA) material. The geometry of creep test specimens follows the American Society for Testing and Materials (ASTM D2990) standards. Three-dimensional printing is performed on an open-source MakerBot desktop 3D printer. The Response Surface Methodology (RSM) is employed to predict the creep rate and rupture time by undertaking the layer height, infill percentage, and infill pattern type (linear, hexagonal, and diamond) as input process parameters. A total of 39 experimental runs were planned by means of a categorical central composite design. The analysis of variance (ANOVA) results revealed that the most influencing factors for creep rate were layer height, infill percentage, and infill patterns, whereas, for rupture time, infill pattern was found significant. The optimized levels obtained for both responses for hexagonal pattern were 0.1 mm layer height and 100% infill percentage. Some verification tests were performed to evaluate the effectiveness of the adopted RSM technique. The implemented research is believed to be a comprehensive guide for the additive manufacturing users to determine the optimum process parameters of FDM which influence the product creep rate and rupture time.

Experimental Investigation and Statistical Evaluation of Optimized Cutting Process Parameters and Cutting Conditions to Minimize Cutting Forces and Shape Deviations in Al6026-T9.

Precise, economical and sustainable cutting operations are highly desirable in the advanced manufacturing environment. For this aim, the present study investigated the influence of cutting parameters (i.e., the cutting speed (c), feed rate (f), depth of cut (d) and positive rake angle (p)) and sustainable cutting conditions (dry and minimum quantity lubricant (MQL)) on cutting forces (i.e., feed force (Ff), tangential forces (Ft), radial force (Fr) and resultant cutting forces (Fc) and shape deviations (i.e., circularity and cylindricity) of a 6026-T9 aluminum alloy. The type of lubricant and insert used are virgin olive oil and uncoated tungsten carbide tool. Turning experiments were performed on a TAKISAWA TC-1 CNC lathe machine and cutting forces were measured with the help of a Kistler 9257B dynamometer. Shape deviations were evaluated by means of a Tesa Micro-Hite 3D DCC 474 coordinate measuring machine (CMM). Experimental runs were planned based on Taguchi mixture orthogonal array design L16. Analysis of variance (ANOVA) was performed to study the statistical significance of cutting parameters. Taguchi based signal to noise (S/N) ratios are applied for optimization of single response, while for optimization of multiple responses Taguchi based signal to noise (S/N) ratios coupled with multi-objective optimization on the basis of ratio analysis (MOORA) and criteria importance through inter-criteria correlation (CRITIC) are employed. ANOVA results revealed that feed rate, followed by a depth of cut, are the most influencing and contributing factors for all components of cutting forces (Ff, Ft, Fr, and Fc) and shape deviations (circularity and cylindricity). The optimized cutting parameters obtained for multi responses are c = 600 m/min, f = 0.1 mm/rev, d = 1 mm and p = 25°, while for cutting conditions, MQL is optimal.