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The paper aims to throw light on the interactions taking place between the different chemical compositions at various temperatures. P-methylacetophenone is a polar dissolvable, which is positively related by dipole–dipole co-operations and is exceptionally compelling a direct result of the shortfall of any critical primary impacts because of the absence of hydrogen bonds; hence, it might work an enormous dipole moment (μ = 3.62 D). Alcohols additionally assume a significant part in industries and research facilities as reagents and pull in incredible consideration as helpful solvents in the green innovation. They are utilized as pressure-driven liquids in drugs, beauty care products, aromas, paints removers, flavors, dye stuffs and as a germ-free specialist.

Mixtures were prepared by mass in airtight ground stopper bottles. The mass measurements were performed on a digital electronic balance (Mettler Toledo AB135, Switzerland) with an uncertainty of ±0.0001 g. The uncertainty in mole fraction was thus estimated to be less than ±0.0001. The densities of pure liquids and their mixtures were determined using a density meter (DDH-2911, Rudolph Research Analytical). The instrument was calibrated frequently using deionized doubly distilled water and dry air. The estimated uncertainty associated with density measurements is ±0.0003 g.cm⁻³. Viscosities of the pure liquids and their mixtures were determined by using Ostwald’s viscometer. The viscometer was calibrated at each required temperature using doubly distilled water. The viscometer was cleaned, dried and is filled with the sample liquid in a bulb having capacity of 10 ml. The viscometer was then kept in a transparent walled water bath with a thermal stability of ±0.01K for about 20 min to obtain thermal equilibrium. An electronic digital stop watch with an uncertainty of ±0.01 s was used for the flow time measurements for each sample at least four readings were taken and then the average of these was taken.

Negative values of excess molar volume, excess isentropic compressibility and positive values of deviation in viscosity including excess Gibbs energy of activation of viscous flow at different temperatures (303.15, 308.15 and 313.15 K) may be attribution to the specific intermolecular interactions through the hetero-association interaction between the components of the mixtures, resulting in the formation of associated complexes through hydrogen bond interactions.

The excess molar volume (V^E) values were analyzed with the Prigogine–Flory–Patterson theory, which demonstrated that the free volume contribution is the one of the factors influencing negative values of excess molar quantities. The Jouyban–Acree model was used to correlate the experimental values of density, speed of sound and viscosity.

It is of great significance to study the influence of subgrade filling on permafrost temperature field in permafrost area for the smooth construction and safe operation of railway.

The paper builds up the model for the hydrothermal coupling calculation of permafrost using finite element software COMSOL to study how permafrost temperature field changes in the short term after subgrade filling, on which basis it proposes the method of calculation for the concave distortion of freezing front in the subgrade-covered area.

The results show that the freezing front below the subgrade center sinks due to the thermal effect of subgrade filling, which will trigger hydrothermal erosion in case of sufficient moisture inflows, leading to the thawing settlement or the cracking of the subgrade, etc. The heat output of soil will be hindered the most in case of July filling, in which case the sinking and the distortion of the freezing front is found to be the most severe, which the recovery of the permafrost temperature field, the slowest, constituting the most unfavorable working condition. The concave distortion of the freezing front in the subgrade area increases with the increase in temperature difference between the filler and ground surface, the subgrade height, the subgrade width and the volumetric thermal capacity of filler, while decreases with the increase of the thermal conductivity of filler. Therefore, the filler chose for engineering project shall be of small volumetric thermal capacity, low initial temperature and high thermal conductivity whenever possible.

The concave distortion of the freezing front under different working conditions at different times after filling can be calculated using the method proposed.

This paper aims to comprehensively clarify the research status of thermal transport of supercritical aviation kerosene, with particular interests in the effect of cracking on heat transfer.

A brief review of current research on supercritical aviation kerosene is presented in views of the surrogate model of hydrocarbon fuels, chemical cracking mechanism of hydrocarbon fuels, thermo-physical properties of hydrocarbon fuels, turbulence models, flow characteristics and thermal performances, which indicates that more efforts need to be directed into these topics. Therefore, supercritical thermal transport of n-decane is then computationally investigated in the condition of thermal pyrolysis, while the ASPEN HYSYS gives the properties of n-decane and pyrolysis products. In addition, the one-step chemical cracking mechanism and SST k-ω turbulence model are applied with relatively high precision.

The existing surrogate models of aviation kerosene are limited to a specific scope of application and their thermo-physical properties deviate from the experimental data. The turbulence models used to implement numerical simulation should be studied to further improve the prediction accuracy. The thermal-induced acceleration is driven by the drastic density change, which is caused by the production of small molecules. The wall temperature of the combustion chamber can be effectively reduced by this behavior, i.e. the phenomenon of heat transfer deterioration can be attenuated or suppressed by thermal pyrolysis.

The issues in numerical studies of supercritical aviation kerosene are clearly revealed, and the conjugation mechanism between thermal pyrolysis and convective heat transfer is initially presented.

Nearly 75% of EU buildings are not energy-efficient enough to meet the international climate goals, which triggers the need to develop sustainable construction techniques with high degree of resilience against climate change. In this context, a promising construction technique is represented by ventilated façades (VFs). This paper aims to propose three different VFs and the authors define a novel machine learning-based approach to evaluate and predict their energy performance under different boundary conditions, without the need for expensive on-site experimentations

The approach is based on the use of machine learning algorithms for the evaluation of different VF configurations and allows for the prediction of the temperatures in the cavities and of the heat fluxes. The authors trained different regression algorithms and obtained low prediction errors, in particular for temperatures. The authors used such models to simulate the thermo-physical behavior of the VFs and determined the most energy-efficient design variant.

The authors found that regression trees allow for an accurate simulation of the thermal behavior of VFs. The authors also studied feature weights to determine the most relevant thermo-physical parameters. Finally, the authors determined the best design variant and the optimal air velocity in the cavity.

This study is unique in four main aspects: the thermo-dynamic analysis is performed under different thermal masses, positions of the cavity and geometries; the VFs are mated with a controlled ventilation system, used to parameterize the thermodynamic behavior under stepwise variations of the air inflow; temperatures and heat fluxes are predicted through machine learning models; the best configuration is determined through simulations, with no onerous in situ experimentations needed.

The goal of this work is to create a computational finite element model to perform thermoelastic stress analysis (TSA) with the usage of a non-ideal load frequency, containing the effects of the material thermal properties.

Throughout this document, the methodology of the model is presented first, followed by the procedure and results. The last part is reserved to results, discussion and conclusions.

This work had the main goal to create a model to perform TSA with the usage of non-ideal loading frequencies, considering the materials’ thermal properties. Loading frequencies out of the ideal range were applied and the model showed capable of good results. The created model reproduced acceptably the TSA, with the desired conditions.

This work creates a model to perform TSA with the usage of non-ideal loading frequencies, considering the materials’ thermal properties.

The purpose of the paper is to propose an effective approach of artificial intelligence (AI) addressing social-humanitarian reality comprising non-formalizable representation. The new task is to describe processes of integration of AI and humans in the hybrid systems framework.

Social-humanitarian dynamics contradict traditional characteristics of AI. Suggested methodology embraces formalized and non-formalized parts as a whole. Holonic and special convergent approaches are combined to ensure purposefulness and sustainability of collective decision-making. Inverse problem solving on topology spaces, control thermodynamics and non-formalizable (considering quantum and relativistic) semantics include observers of eigenforms of reality.

Collective decision-making cannot be represented only by formal means. Thus, this paper suggests the equation of hybrid reality (HyR), which integrates formalizable and non-formalizable parts conveying and coalescing holonic approaches, thermodynamic theory, cognitive modeling and inverse problem solving. The special convergent approach makes the solution of this equation purposeful and sustainable.

The suggested approach is far reaching with respect of current state-of-the-art technology; medium-term limitations are expected in the creation of cognitive semantics.

Social-humanitarian events embrace all phenomena connected with individual and collective human behavior and decision-making. The paper will impact deeply networked experts, groups of crowds, rescue teams, researchers, professional communities, society and environment.

New possibilities for advanced AI to enable purposeful and sustainable social-humanitarian subjects. The special convergent information structuring during collective decision-making creates necessary conditions toward the goals.

In further conceptualizing a novel generative knowledge management system (KM/KMS), this paper aims to focus on identifying and mitigating the risks related to its envisaged scaling from a prototype to an application with a rapidly growing user base.

It follows up on prior publications using design science research (DSR) methodologies in compliance with theory effectiveness, a principle expecting system designs to be purposeful in terms of utility and communication. The KMS perspective taken prioritizes a decentralizing agenda benefiting knowledge workers while also aiming to foster a fruitful co-evolution with conventional organizational KM approaches.

The utilization and further extension of the CKDT and a “scalable innovation” heuristic are assisting the detecting of potential scaling risks related to the logics and logistics, generative interoperability, technological capacitating, knowledge dynamics and value chain which further validates the viability of the proposed KM concept and system.

Although the prototype development is still in progress, the paper conforms to the DSR practice to report on early visions of technology impact on users, organizations and society but also reflects on expectations of viability, desirability and commitment, as well as the system’s prospect as a general-purpose-technology or disruptive innovation.

In addition to the novel KM-related perspectives, the paper’s practical emphasis on the scaling of more complex systems is rarely dealt with in the literature due to the respective projects’ often large-scale collaborative nature, broad methodological scope and diverse stakeholders’ interests. In this case, the task is eased as prior DSR outputs can be referred to.

In this study, AlCoCrFeNi–Cu (Cu-based) and AlCoCrFeNi–Ti (Ti-based) high entropy alloys (HEAs) were fabricated using a direct blown powder technique via laser additive manufacturing on an A301 steel baseplate for aerospace applications. The purpose of this research is to investigate the electrical resistivity and oxidation behavior of the as-built copper (Cu)- and titanium (Ti)-based alloys and to understand the alloying effect, the HEAs core effects and the influence of laser parameters on the physical properties of the alloys.

The as-received AlCoCrFeNiCu and AlCoCrFeNiTi powders were used to fabricate HEA clads on an A301 steel baseplate preheated at 400°C using a 3 kW Rofin Sinar dY044 continuous-wave laser-deposition system fitted with a KUKA robotic arm. The deposits were sectioned using an electric cutting machine and prepared by standard metallographic methods to investigate the electrical and oxidation properties of the alloys.

The results showed that the laser power had the most influence on the physical properties of the alloys. The Ti-based alloy had better resistivity than the Cu-based alloy, whereas the Cu-based alloy had better oxidation residence than the Ti-based alloy which attributed to the compositional alloying effect (Cu, aluminum and nickel) and the orderliness of the lattice, which is significantly associated with the electron transportation; consequently, the more distorted the lattice, the easier the transportation of electrons and the better the properties of the HEAs.

It is evident from the studies that the composition of HEAs and the laser processing parameters are two significant factors that influence the physical properties of laser deposited HEAs for aerospace applications.

Apart from the basic material properties of liquid lubricants, such as, e.g., the viscosity and density of the hydraulic fluid, it is also important to have information regarding the electrical properties of the fluid used. The latter is closely related to the purpose, type, structure, and conditions of use of a hydraulic system, especially the powertrain design and fluid condition monitoring. The insulating capacity of the hydraulic fluid is important in cases where the electric motor of the pump is immersed in the fluid. In other cases, on the basis of changing the electrical conductive properties of the hydraulic fluid, we can refer its condition, and, on this basis, the degree of degradation.

The paper first highlights the importance of knowing the electrical properties of hydraulic fluids and then aims to compare these properties, such as the breakdown voltage of commonly used hydraulic mineral oils and newer ionic fluids suitable for use as hydraulic fluids.

Knowledge of this property is crucial for the design approach of modern hydraulic compact power packs. In the following, the emphasis is on the more advanced use of known electrical quantities, such as electrical conductivity and the dielectric constant of a liquid.

Based on the changes in these quantities, we have the possibility of real-time monitoring the hydraulic fluid condition, on the basis of which we judge the degree of fluid degradation and its suitability for further use.