A new synthetic metamodel methodology for liquid‐propellant engine's cooling system optimization

The present paper strives for optimization of the cooling system of a liquid‐propellant engine (LPE). To this end, the new synthetic metamodel methodology utilizing the design of experiment method and the response surface method was developed and implemented as two effective means of designing, analyzing, and optimizing. The input variables, constraints, objective functions, and their surfaces were identified. Hence, the design and development strategy of combustion chamber and nozzle was clarified, and 64 different experiments were carried out on the RD‐161 propulsion system, of which 47 experiments were approved and compatible with the problem constraints. This engine used all three modes of cooling: the radiation cooling, the regenerative cooling, and the film cooling. The response surface curves were drawn and the related objective function equations were obtained. The analysis of variance results indicate that the developed synthetic model is capable to predict the responses adequately within the limits of input parameters. The three‐dimensional response surface curves and contour plots have been developed to find out the combined effects of input parameters on responses. In addition, the precision of the models was assessed and the output was interpreted and analyzed, which showed high accuracy. Therefore, the desirability function analysis has been applied to LPE's cooling system for multiobjective optimization to maximize the total heat transfer and minimize the cooling system pressure loss simultaneously. Finally, confirmatory tests have been conducted with the optimum parametric conditions to validate the optimization techniques. In conclusion, this methodology optimizes the LPE's cooling system, a 2% increase in the total heat transfer, and a 38% decrease in the pressure loss of the cooling system. These values are considerably large for the LPE design.     

Silicene Nanoribbons on an Insulating Thin Film

Silicene, a new 2D material has attracted intense research because of the ubiquitous use of silicon in modern technology. However, producing free-standing silicene has proved to be a huge challenge. Until now, silicene could be synthesized only on metal surfaces where it naturally forms strong interactions with the metal substrate that modify its electronic properties. Here, the authors report the first experimental evidence of silicene nanoribbons on an insulating NaCl thin film. This work represents a major breakthrough, for the study of the intrinsic properties of silicene, and by extension to other 2D materials that have so far only been grown on metal surfaces.     

Development and comparison of loop-mediated isothermal amplification and quantitative polymerase chain reaction assays for the detection of Mycoplasma bovis in milk

Bovine mastitis is an economic burden for dairies worldwide. Mycoplasma species, and especially Mycoplasma bovis, are among the most important causative agents, and rapid, precise, and low-cost methods for Mycoplasma detection are urgently needed. For this purpose, loop-mediated isothermal amplification (LAMP) and quantitative PCR (qPCR) assays were developed and compared. The LAMP assay was designed and primer concentrations optimized to M. bovis oppD, encoding oligopeptide permease D. For qPCR, a Taqman assay (Applied Biosystems, Carlsbad, CA) targeting M. bovis gltX, encoding glutamate transfer RNA ligase, was optimized for primer concentration, annealing temperature, and DNA polymerase. Both assays were similarly sensitive, with a detection limit of approximately 10⁴ to 10⁵ M. bovis cells/mL. Both assays were also successful in confirming M. bovis identity in laboratory culture suspensions and in bovine milk. The LAMP and qPCR assays combined with the MoBio DNA extraction kit (MoBio Laboratories Inc., Carlsbad, CA) resulted in the correct detection of 13 out of 13 M. bovis isolates and 14 out of 16 M. bovis-positive milk samples collected from commercial dairies in California. When combined with the PrepMan Ultra reagent (Applied Biosystems), the qPCR assay resulted in confirming 21 out of 21 M. bovis-positive milk samples. Comparison of the assays to milk containing either Mycoplasma arginini, Mycoplasma bovigenitalium, Mycoplasma californicum, M. alkalescens, or Acholeplasma laidlawii or milk lacking any detectable Mycoplasma species or relatives resulted in 3 out of 17 (LAMP with MoBio), 1 out of 17 (qPCR with MoBio), and 2 out of 36 (qPCR with PrepMan Ultra) false positives. Overall, the qPCR assay was more robust than LAMP and could be used on DNA recovered from milk prepared with the PrepMan Ultra reagent, a method that does not include a DNA purification step. The use of this qPCR method enables M. bovis detection in bovine milk in 40 to 55 min, and therefore provides new opportunities to accelerate and simplify M. bovis detection in unpasteurized milk to reduce the incidence of M. bovis mastitis outbreaks.     

Telesurgery QoS improvement over SDN based on a Type‐2 fuzzy system and enhanced cuckoo optimization algorithm

Telemedicine is a new area based on the information and communication technology for collecting, storing, organizing, retrieving and exchanging medical information. One of the most important applications of telemedicine is indeed telesurgery in which an efficient telecommunication infrastructure between the surgery room and remote surgeons need to be established. One of the most important issues to be tackled in telesurgery is to find favorable links for routing as well as providing high Quality of Service (QoS). In this paper, an efficient model based on the hybridization of Type‐2 Fuzzy System (T2FS) and Cuckoo Optimization Algorithm (COA) over the Software Defined Networks (SDN) is proposed in order to achieve optimal and reliable routes for telesurgery application. Using T2FS, the fitness of the links is determined; then, a COA is conducted over the Constraint Shortest Path (CSP) problem to find the best routes. Delay is considered as a CSP problem which is satisfied by trying to find the paths with minimum cost. Due to the NP‐completeness of the CSP problem, an Enhanced COA (so‐called E‐COA) is proposed and utilized as a metaheuristic solver. To the best of our knowledge, this paper is the first SDN‐based communication model that applies both T2FS and E‐COA for assigning proper costs to the network's links, and solves the consequence CSP problem according to the QoS requirement for telesurgery. The model also recognizes and preserves the second‐best routes in order to keep the reliability for such a critical application. In addition to the simulations, the performance evaluation is also conducted on a real experimental scenario. Many comparisons are carried out between the proposed model and other conventional methods, and the evaluation study shows the superiority of the proposed model on all the three QoS‐related metrics, i.e. average end‐to‐end delay, packet loss ratio and PSNR.     

Adaptive robust control-based energy management of hybrid PV-Battery systems with improved transient performance

Energy management of hybrid photovoltaic (PV)-battery systems still serve as a challenging task owing to their complex and nonlinear characteristics, multicomponent structures, and the extensive range of environmental factors disturbing their nominal performance. The hybrid energy system developed in this study encompasses PV arrays, a battery component, one boost converter, and one bidirectional boost converter. In this paper, we propose a novel adaptive robust control framework for the optimal energy management of the PV-battery systems under many operating conditions and subject to unmodelled dynamics. An improved exponential-like adaptive integral sliding mode (EISM) control coupled to neural network approximator is introduced using a multi-rate convergence tweaking mechanism for the sliding surface to improve the transient performance of the closed-loop system. Furthermore, the entire dynamics of the hybrid energy system is considered unknown, unlike the previous studies that only assumed the parametric uncertainties. The global asymptotic stability of the system is guaranteed, and the effectiveness of this novel framework is compared to benchmark studies.     

Castor oil-based polyurethane coatings containing benzyl triethanol ammonium chloride: synthesis,characterization, and biological properties

In the present work, benzyl triethanol ammonium chloride (BTEAC) was employed as a reactive bactericidal additive for preparing of polyurethane coatings. In this regard, castor oil as a renewable resource-based polyol, polyethylene glycol (PEG1000), and BTEAC were reacted with toluene diisocyanate. Physical, mechanical, and thermal characteristics as well as biocompatibility and antibacterial properties of polyurethanes were evaluated. The prepared polyurethanes showed two-phase structure with soft and hard segments glass transition temperature transitions in the range of 18–70 and 85–153 °C, respectively. Initial modulus and tensile strength were improved for coatings with higher BTEAC content, while elongation at break and thermal stability were decreased. Hydrophilicity of coatings was increased for polyurethanes based on higher content of BTEAC and PEG1000. Polyurethanes with higher BTEAC content showed better cytocompatibility for mouse L929 fibroblast cells. Moreover, coatings with higher hydrophilicity and BTEAC content displayed superior antibacterial activity against both Escherichia coli and Staphylococcus aureus bacteria.     

Numerical simulation and optimization of steam-assisted gravity drainage with temperature,rate, and well distance control using an efficient hybrid optimization technique

Steam-assisted gravity drainage (SAGD) is a thermal enhanced oil recovery technique through drilling of two horizontal wells. Effects of steam injection temperature, well rates, and their distance on oil recovery were analyzed and optimized. Steam temperature and well distances remarkably affect SAGD performance. Four metaheuristic algorithms (particle swarm optimization (PSO), imperialist competitive algorithm, cultural algorithm, and Bees algorithm) and pattern search optimization algorithm (PSA) are used for optimization. PSO performs better than other metaheuristics and PSA is the fastest one, while it is probable to be trapped in local optimums. Hybrid PSO-PS is proposed that starts with PSO and proceeds with PSA, and tested in an SAGD project and showed excellence over other techniques.     

The structural variability of quarters and residential areas in the historical texture of the city of Yazd based on Islamic rules and jurisprudence: a case study of Golchinan quarter

According to many researchers and scholars, religious beliefs can be considered as the most influential factor in forming Muslim urban spaces and their architectural elements. In fact, historical cities reflect the culture and beliefs of their residences. Among all historical places in Iranian cities, the historical texture of the city of Yazd, especially the quarters since the age of Qajar dynasty, are well preserved. The present study aims at identifying the Islamic principles and values influencing the formation of architectural spaces and the extent of their applications in one of the historical quarters known as Golchinan. The results of the conformation of the theoretical findings with the data acquired from field studies revealed that almost 90% of the urban and architectural spaces (e.g. residential areas, mosques, bazaars, and pathways) in Yazd are directly influenced by Islamic principles. In other words, there is a strong conformity between the accepted Islamic values of the society and what actually was applied to urban constructions during Qajar dynasty.