Thermally reused solar energy harvesting using current mirror cells

This paper implements a simultaneous solar and thermal energy harvesting system, as a hybrid energy harvesting (HEH) system, to convert ambient light into electrical energy through photovoltaic (PV) cells and heat absorbed in the body of PV cells. Indeed, a solar panel equipped with serially connected thermoelectric generators not only converts the incoming light into electricity but also takes advantage of heat emanating from the light. In a conventional HEH system, the diode block is used to provide the path for the input source with the highest value. In this scheme, at each time, only one source can be handled to generate its output, while other sources are blocked. To handle this challenge of combining resources in HEH systems, this paper proposes a method for collecting all incoming energies and conveying its summation to the load via the current mirror cells in an approach similar to the maximum power point tracking. This technique is implemented using off-the-shelf components. The measurement results show that the proposed method is a realistic approach for supplying electrical energy to wireless sensor nodes and low-power electronics.     

The effect of heat transfer characteristics of macromolecule fouling on heat exchanger surface: A dynamic simulation study

At the city gate gas pressure reduction stations (CGSs), to prevent natural gas from forming a hydrate in the throttle valve, the natural gas is heated by the heater before reaching the pressure relief valve. Heat exchangers are an essential component of industrial processes that contribute significantly to total system energy. Since the element impacting heat exchanger performance is the fouling process, all fouling processes and models were dynamically simulated in this study. Through coding in the C++ language and simultaneous use of fluent functions, or, in other words, user-defined function (UDF), fouling-related models were defined for this software. The dynamic simulation was performed, and parameters such as fouling strength and layer thickness were calculated. The effects of changing operating conditions, such as gas inlet velocity, surface temperature, and fouling species concentration on fouling growth, were also evaluated. As the concentration of fouling species increased, the fouling rate also increased. The amount of supersaturation and fouling rate increased as the surface temperature increased. Due to the operational limitations of the system, to reduce the fouling rate, the gas inlet velocity should be as high as possible, and the fluid inlet temperature, surface temperature, and concentration of fouling species should be as low as possible. In this study, the required time to reach the efficiency of 70% of the heat exchanger was calculated using the modelling of this chamber, which was equivalent to 190 days. Additionally, the critical thickness of the fouling layer at this time was 3.5 cm.     

Realization of diversity in physical properties of Zr2Se(B1-xSex) MAX phases through DFT approach

The discovery of a series of MAX phases, Zr₂Se(B_1-xSe_x), with Se at both A- and X-sites, drives a new chemical diversity to the MAX family. Here, we employed the density functional theory (DFT) approach to realize the diversity in physical properties of Zr₂Se(B_1-xSe_x). All compositions of Zr₂Se(B_1-xSe_x) are mechanically stable and the dynamical stability of the end member Zr₂SeSe is confirmed. The elastic constant C₃₃ and bulk moduli B show a decrease almost monotonically with Se-content x while other constants and moduli change irregularly. All elastic constants and moduli except C₁₂ and C₁₃ are highest for the end member Zr₂SeB. Additionally, the Vickers hardness, Debye temperature, minimum thermal conductivity, and lattice thermal conductivity are highest for Zr₂SeB. The increase of Se-content x at X-site reduces most of the properties of Zr₂Se(B_1-xSe_x). The electronic band structures change drastically with increasing Se-content x. This diversity in electronic band structures is mainly the reason for the diversity in physical properties of Zr₂Se(B_1-xSe_x). All compositions of Zr₂Se(B_1-xSe_x) have the potential to be thermal barrier coating materials, and Zr₂SeB has the potential to be etched into 2D MXene, Zr₂B.     

Tailoring Additively Manufactured Titanium Implants for Short-Time Pediatric Implantations with Enhanced Bactericidal Activity

Paediatric titanium (Ti) implants are used for the short-term fixation of fractures, after which they are removed. However, bone overgrowth on the implant surface can complicate their removal. The current Ti implants research focuses on improving their osseointegration and antibacterial properties for long-term use while overlooking the requirements of temporary implants. This paper presents the engineering of additively manufactured Ti implants with antibacterial properties and prevention of bone cell overgrowth. 3D-printed implants were fabricated followed by electrochemical anodization to generate vertically aligned titania nanotubes (TNTs) on the surface with specific diameters (∼100 nm) to reduce cell attachment and proliferation. To achieve enhanced antibacterial performance, TNTs were coated with gallium nitrate as antibacterial agent. The physicochemical characteristics of these implants assessed by the attachment, growth and viability of osteoblastic MG-63 cells showed significantly reduced cell attachment and proliferation, confirming the ability of TNTs surface to avoid cell overgrowth. Gallium coated TNTs showed strong antibacterial activity against S. aureus and P. aeruginosa with reduced bacterial attachment and high rates of bacterial death. Thus a new approach for the engineering of temporary Ti implants with enhanced bactericidal properties with reduced bone cell attachment is demonstrated as a new strategy toward a new generation of short-term implants in paediatrics.     

Facile Fabrication and Developing the Structural,Optical and Electrical Properties of SiC/Y2O3 Nanostructures Doped PMMA for Optics and Potential Nanodevices

Silicon - This work aims to improve the structural, optical and electrical characteristics of silicon carbide(SiC) yttrium oxide(Y2O3) nanostructures doped poly-methyl methacrylate(PMMA) to utilize...     

Imbalance factor: a simple new scale for measuring inter-class imbalance extent in classification problems

Knowledge and Information Systems - Learning from datasets that suffer from differences in absolute frequency of classes is one of the most challenging tasks in the machine learning field. Efforts...     

Thermodynamic and economic evaluation and optimization of the applicability of integrating an innovative multi-heat recovery with a dual-flash binary geothermal power plant

Clean Technologies and Environmental Policy - Generally, a stand-alone flash-binary geothermal power plant loses most of its input energy, so its efficiency declines accordingly. Its overall...     

Seismic damage identification of moment frames based on random forest algorithm and enhanced gray wolf optimization

The present study aims to identify damage in two-dimensional (2-D) moment frames using seismic responses by combining the random forest (RF) machine classifier and the enhanced gray wolf optimizer (EGWO) metaheuristic algorithm. First, a 2-D moment frame for the dynamic analysis is simulated using the finite element method (FEM). Then, the placement of sensors is optimized using a proposed optimal sensor placement (POSP) method, which is a combination of the iterated improved reduced system (IIRS) and the binary differential evolution (BDE) optimization algorithm. The acceleration responses of the moment frame having damaged elements under 1995 Kobe earthquake are measured at the optimal sensor placement. Then, the natural frequencies and mode shapes of the structure are extracted using the auto-regressive model with exogenous input method (ARX) as a system identification method. The natural frequencies are exploited to train an RF machine learning network that can find the damaged story of the moment frame. Then, EGWO is employed to accurately locate and quantify the damaged elements of the structure. The efficiency of the proposed method is assessed through considering a six-story frame with 18 elements, a seven-story frame with 49 elements, and the experimental data of an eight-story frame for various conditions. The results show that the RF algorithm has an outstanding performance to correctly find a damaged story. Furthermore, the location and severity of damaged elements are precisely determined by EGWO algorithm. As a final outcome, it is demonstrated that the two-step proposed method is very effective in seismically identifying damage to such structures.     

Skill Optimization Algorithm: A New Human-Based Metaheuristic Technique

Metaheuristic algorithms are widely used in solving optimization problems. In this paper, a new metaheuristic algorithm called Skill Optimization Algorithm (SOA) is proposed to solve optimization problems. The fundamental inspiration in designing SOA is human efforts to acquire and improve skills. Various stages of SOA are mathematically modeled in two phases, including: (i) exploration, skill acquisition from experts and (ii) exploitation, skill improvement based on practice and individual effort. The efficiency of SOA in optimization applications is analyzed through testing this algorithm on a set of twenty-three standard benchmark functions of a variety of unimodal, high-dimensional multimodal, and fixed-dimensional multimodal types. The optimization results show that SOA, by balancing exploration and exploitation, is able to provide good performance and appropriate solutions for optimization problems. In addition, the performance of SOA in optimization is compared with ten metaheuristic algorithms to evaluate the quality of the results obtained by the proposed approach. Analysis and comparison of the obtained simulation results show that the proposed SOA has a superior performance over the considered algorithms and achieves much more competitive results.     

Influence of Curing Agents Molecular Structures on Interfacial Characteristics of Graphene/Epoxy Nanocomposites: A Molecular Dynamics Framework

This paper presents a comprehensive molecular dynamics study on the effects of the stoichiometric ratio of epoxy:hardener, hardener's linear and cyclic structure, and number of aromatic rings on the interfacial characteristics of graphene/epoxy nanocomposite. The van der Waals gap and polymer peak density as a function of the type of the hardener is calculated by analyzing the local mass density profile. Additionally, steered molecular dynamics are used to conduct normal pull-out of graphene to study the effect of the mentioned features of hardeners on the interfacial mechanical properties of nanocomposites, including traction force, separation distance, and distribution quality of reacted epoxide rings in the epoxy. Influence of the hardeners on the damage mechanism and its initiation point are also studied by analyzing the evolution of local mass density profile during the normal pull-out simulation. It is seen that stoichiometric ratio and geometrical structure of the hardeners affect the interfacial strength. It is also revealed that the hardener type can change the epoxy damage initiation point. The damage occurs in the interphase region for a higher stoichiometric ratio or cyclic structure of hardener. In comparison, for hardener's lower stoichiometric ratio and non-cyclic structure, failure begins in the epoxy near graphene layers.