A porous volumetric receiver is the key component in concentrated solar power systems. In this paper, we investigate the effects of volumetric parameter models on the heat collection efficiency of the volumetric receiver by numerical simulations with the combination of local thermal non-equilibrium and discrete ordinate methods. Seven volumetric convective heat transfer coefficient models and three extinction coefficient models were investigated. The efficiencies calculated using these models were compared among each other. The results show that volumetric convective heat transfer coefficient models have significant effects with a maximum difference of 27.7% in receiver efficiency for these models. Extinction coefficient models have less effects on receiver efficiency with a maximum difference of 7.3%.

The Equivalent Consumption Minimization Strategy (ECMS) is a well-known control strategy for the definition of optimal power-split in hybrid-electric vehicles, because of its effectiveness and reduced calibration effort. In this kind of Energy Management Systems (EMS), the correct identification of an equivalence factor (K), which translates electric power in equivalent fuel consumption, is of paramount importance. To guarantee charge sustaining operation, the K factor must be adjusted to different mission profiles. Adaptive ECMS (A-ECMS) techniques have thus been introduced, which automatically determine the optimal equivalence factor based on the vehicle mission. The aim of this research activity is to assess the potential in terms of fuel consumption and charge sustainability of different A-ECMS techniques on a gasoline hybrid-electric passenger car. First, the 0D vehicle and powertrain model was developed in the commercial CAE software GT-SUITE. An ECMS-based EMS was used to contro... [more]

Accurate prediction of an off-normal event in a nuclear reactor is dependent upon the availability of sensory data, reactor core physical condition, and understanding of the underlying phenomenon. This work presents a method to project the data from some discrete sensory locations to the overall reactor domain during conduction cooldown scenarios similar to High Temperature Gas-cooled Reactors (HTGRs). The existing models for conductive cooldown in a heterogeneous multi-body system, such as an assembly of prismatic blocks or pebble beds relies on knowledge of the thermal contact conductance, requiring significant knowledge of local thermal contacts and heat transport possibilities across those contacts. With a priori knowledge of bulk geometry features and some discrete sensors, a machine learning approach was devised. The presented work uses an experimental facility to mimic conduction cooldown with an assembly of 68 cylindrical rods initially heated to 1200 K. High-fidelity temperatu... [more]

In order to study the effect of groove parameters on solid particles’ deposition in mechanical face seal lubrication film, a multi-phase flow calculation model for the sealing micro-gap lubricating film was established based on the Laminar model, mixture multi-phase flow model, Zwart−Gerber−Belamri cavitation model, and DPM model in Fluent, and a numerical simulation of the effect of groove parameters is presented. The results show that, with the increase of groove depth, the circumferential sedimentary zone in the dam area decreases or even disappears, and the groove area becomes the main sedimentary part; the particle deposition rate decreases first and then increases with the increase of groove depth and spiral angle. The influence of groove depth on the deposition rate at low speed is more significant than that at high speed. The increase of deposition rate caused by a spiral angle that is too large is greater than that caused by a spiral angle that is too small. The optimal groove... [more]

Liquefied natural gas (LNG) is regarded as the cleanest among fossil fuels due to its lower environmental impact. In power plants, it emits 50−60% less carbon dioxide into the atmosphere compared to regular oil or coal-fired plants. As the demand for a lower environmental footprint is increasing, fuel cells powered by LNG are starting to appear as a promising technology, especially suitable for off-grid applications, since they can supply both electricity and heating. This article presents a techno-economic assessment for an integrated system consisting of a solid oxide fuel cell (SOFC) stack and a micro gas turbine (MGT) fueled by LNG, that feeds the waste heat to a multi-effect desalination system (MED) on the Greek island of Patmos. The partial or total replacement of the diesel engines on the non-interconnected island of Patmos with SOFC systems is investigated. The optimal system implementation is analyzed through a multi-stage approach that includes dynamic computational analysis... [more]

Addressing the problem of the vibration and noise of a permanent-magnet synchronous motor (PMSM), this paper optimizes the structure of a permanent-magnet motor rotator, introduces the electromagnetic-structure-acoustic coupling calculation model, and optimizes the motor rotator to reduce the vibration and noise of a permanent-magnet motor. Using the theory of Maxwell’s stress equation, the radial electromagnetic force on the stator teeth of the permanent-magnet motor is deduced and analyzed, and the correctness of the analysis calculation is verified by using the finite element multi-physical field coupling method. Based on the deduced analytical expression of the radial electromagnetic force, the sources of the radial electromagnetic force for each order and the frequency of the permanent-magnet motor are summarized. A 12-slot, 8-pole, permanent-magnet motor is taken as an example. A calculation model considering the spatial distribution of the radial electromagnetic force and the el... [more]

Multiple elimination has always been a key, challenge, and hotspot in the field of hydrocarbon exploration. However, each multiple elimination method comes with one or more limitations at present. The efficiency and success of each approach strongly depend on their corresponding prior assumptions, in particular for seismic data acquired from complex geological regions. The multiple elimination approach using deep learning encodes the input seismic data to multiple levels of abstraction and decodes those levels to reconstruct the primaries without multiples. In this study, we employ a classic convolution neural network (CNN) with a U-shaped architecture which uses extremely few seismic data for end-to-end training, strongly increasing the neural network speed. Then, we apply the trained network to predict all seismic data, which solves the problem of difficult elimination of global multiples, avoids the regularization of seismic data, and reduces massive amounts of calculation in tradit... [more]

With a focus on the shock oscillation phenomenon of a supersonic inlet at a high Mach number, the influence of isolator overflow on shock oscillation is studied in this paper. The shock wave dynamic model with overflow was established by the theoretical method, and the integrated numerical model of internal flow and external flow in the inlet was established too. The theoretical analysis of rate of overflow and overflow position on the flow field is carried out, and the changes of flow field parameters are studied by numerical simulation under different overflow positions. The results showed that both increasing the rate of overflow and setting the overflow gap close to the shock front were beneficial to reducing the flow parameters’ oscillation. In the viscous flow field, the overflow gap restricted the forward development of the local separation region of the shock train system, thus constraining the shock wave movement process, which could significantly reduce the parameter oscillat... [more]

Gasification has played an important role in the sustainable use of waste biomass, providing useful combustible gases in the process. Gasification has an important role in waste management and promotes energy independence for many oil-deficit countries. The gasification process has been studied by various researchers, and improvements have been achieved in its sub-processes such as devolatilization, feed input methods, and so on. We examined the influence of gasifier operation parameters, such as oxidizer content, moisture content in the feedstock, and solar flux input inside the gasifier, on the temperature distribution, velocity distribution, and product gas yields of the gasifier. The results indicate that inducing solar energy at different stages of the gasifier leads to different yields of product gas composition (CO and H2).

A series of PFDPP copolymers based on fluorene (F) and diketopyrrolopyrrole (DPP) monomers were synthesized via direct arylation polycondensation using Fagnou conditions which involved palladium acetate as catalyst (a gradual catalyst addition of three different percentages were used), potassium carbonate as the base, and neodecanoic acid in N, N-dimethylacetamide. This synthesis provides a low cost compared with traditional methods of transition-metal-catalyzed polymerization. Among the different amounts of catalyst used in the present work, 12% was optimal because it gave the highest reaction yield (81.5%) and one of the highest molecular weights (Mn = 13.8 KDa). Copolymers’ chemical structures, molecular weight distributions, and optical and thermal properties were analyzed. The linear optical properties of PFDPP copolymers resulted very similarly independently to the catalyst amounts used in the synthesis of the PFDPP copolymers: two absorptions bands distinctive of donor−acceptor... [more]

This paper proposes and demonstrates, in full scale, a novel type of energy geostructure (“the Climate Road”) that combines a ground-source heat pump (GSHP) with a sustainable urban drainage system (SUDS) by utilizing the gravel roadbed simultaneously as an energy source and a rainwater retarding basin. The Climate Road measures 50 m × 8 m × 1 m (length, width, depth, respectively) and has 800 m of geothermal piping embedded in the roadbed, serving as the heat collector for a GSHP that supplies a nearby kindergarten with domestic hot water and space heating. Model analysis of operational data from 2018−2021 indicates sustainable annual heat production levels of around 0.6 MWh per meter road, with a COP of 2.9−3.1. The continued infiltration of rainwater into the roadbed increases the amount of extractable heat by an estimated 17% compared to the case of zero infiltration. Using the developed model for scenario analysis, we find that draining rainwater from three single-family houses an... [more]

Nowadays, there are significant issues in the classification of lithofacies and the identification of rock types in particular. Zamzama gas field demonstrates the complex nature of lithofacies due to the heterogeneous nature of the reservoir formation, while it is quite challenging to identify the lithofacies. Using our machine learning approach and cluster analysis, we can not only resolve these difficulties, but also minimize their time-consuming aspects and provide an accurate result even when the user is inexperienced. To constrain accurate reservoir models, rock type identification is a critical step in reservoir characterization. Many empirical and statistical methodologies have been established based on the effect of rock type on reservoir performance. Only well-logged data are provided, and no cores are sampled. Given these circumstances, and the fact that traditional methods such as regression are intractable, we have chosen to apply three strategies: (1) using a self-organizi... [more]

Digital twins (DTs) and building information modelling (BIM) are proving to be valuable tools for managing the entire life cycle of a building (LCB), from the early design stages to management and maintenance over time. On the other hand, BIM platforms cannot manage the geometric complexities of existing buildings and the large amount of information that sensors can collect. For this reason, this research proposes a scan-to-BIM process capable of managing high levels of detail (LODs) and information (LOIs) during the design, construction site management, and construction phases. Specific grades of generation (GOGs) were applied to create as-found, as-designed, and as-built models that interact with and support the rehabilitation project of a multi-level residential building. Furthermore, thanks to the sharing of specific APIs (Revit and Autodesk Forge APIs), it was possible to switch from static representations to novel levels of interoperability and interactivity for the user and more... [more]

This paper provides computer analysis and experiential investigation of the permanent magnet machines with neodymium and ferrite permanent magnets to discuss the feasibility of utilizing induction machines-oriented equipment for PM machine production. For this purpose, the machines are obtained by replacing the squirrel-cage rotor of the induction motor with the flux-focusing (tangential) and surface-mounted (radial) permanent magnet rotors. Electromechanical parameters of the machines as electromagnetic torque and output power are discussed and compared. The temperatures of the neodymium and ferrite magnets are also calculated at rated current, and short circuit scenarios and the performance of two different cooling systems in minimizing the temperature effect on the machines are investigated. Furthermore, the demagnetization of permanent magnets at various load conditions is also studied. Finally, the results of the computer modeling are validated by the physical prototypes of the ma... [more]

The aim of the article is to present a new idea of limiting the bearing voltage in electric machines with permanent magnets through the use of a shielding winding placed in stator slot wedges. The first part of the article is dedicated to the mechanisms of generating bearing voltages when the machine is supplied from the mains and from a power electronic converter. Additionally, some methods of counteracting these phenomena were described. Next, multivariant simulation tests were carried out based on the two-dimensional field model of a synchronous machine with permanent magnets. The tests were run in order to determine the internal capacitances of the machine, on which the level of bearing voltages depends. Based on these results, the optimal variant of the design solution ensuring the limitation of the bearing voltage to a safe level was selected. Using the model of a two-level converter and based on the equivalent diagram of the internal capacitances of the machine, the influence of... [more]

The internal heat transfer performance and flow structures of a sweeping jet and film composite cooling on a flat plate were numerically studied. Sweeping jet and film composite cooling consists of a fluidic oscillator and 20 cylindrical film holes; the direct jet is formed by removing the feedback from the fluidic oscillator, which is different from the traditional cylindrical nozzle. Four different mass flow rates of coolant were considered, and the inclination angle of the film hole was 30°. The Conjugate Heat Transfer method (CHT) and Unsteady Reynolds Averaged Navier Stokes equation (URANS) were employed. The results indicated that the flow resistance coefficients of the sweeping jet were larger than those of the direct jet, and the Nusselt number monotonously increased with the increase in the mass flow rate. Compared to the direct jet, the sweeping jet had a more spatially uniform heat removal rate, and the area-averaged Nusselt number was slightly lower. Therefore, the sweeping... [more]

This study examines the heat and mass transfer coefficient, thermal effusivity, and other thermal properties of solar-dried cocoyam chips, as well as the drying kinetics. The research also assessed the economics of the solar dryer. For these reasons, a solar dryer with a partitioned collector was developed that creates a double airflow travel distance to delay the airflow inside the collector. The partitioning of the collector delays the airflow and helps to create more turbulence for the airflow with increased energy. The solar dryer was locally developed at the Michael Okpara University of Agriculture and tested during the humid crop harvesting period of September for the worst-case scenario. The obtained drying curves and kinetics for cocoyam drying are subjected to the vagaries of weather conditions. The drying rate showed declining sinusoidal characteristics and took about 25 h to attain equilibrium. Analysis of the airflow velocity showed gravitation between laminar and turbulent... [more]

A constant worldwide growing load stress over a power system compelled the practice of a reactive power injection to ensure an efficient power network. For this purpose, multiple technologies exist in the knowledge market out of which this paper emphasizes the usage of the flexible alternating current transmission system (FACTS) and presents a comparative study of the static var compensator (SVC) with the static synchronous compensator (STATCOM), inducted in a real electric substation. The aim is to improve the power factor (PF) and power quality and to encounter reliably extreme conditions. A 220 kV electric substation was opted for the analysis, and both the static and dynamic conditions were observed with the help of a power system analysis tool termed PowerFactory-DIgSILENT. Multiple aspects were investigated via software simulations to assess the performance of the aforementioned FACTS devices, such as the voltage profile evaluation via the load flow analysis method (LFA), the har... [more]

Hyper compressors are key facilities for producing the low-density polyethylene with discharge pressure up to 350 MPa. Such high pressure brings great challenges to the design of the hyper compressor in many aspects. In this paper, a 3D transient computational fluid dynamics (CFD) model with inlet and outlet pipelines is built to investigate the thermodynamic performance of a hyper compressor. To realize the interaction between the thermodynamic processes and the pressure pulsation through valve dynamics, the pressures across the valve surfaces were monitored to the dynamic equation of the poppet valve. Then, structured grids were generated for the flow domain inside the valve, and the entire numerical model was solved by a commercial code: ANSYS Fluent. Consequently, the p-V diagram, the valve motion and pressure pulsation could be acquired simultaneously. The results of the numerical model showed that the exponents of the expansion and compression processes were 5.12 and 13.22, which... [more]

Since the DC-link of the dual-inverter two-stage matrix converter (TSMC) has no energy storage element, its grid-side current waveform is closely related to the load-side condition. The conventional modulation strategy of the dual-inverter TSMC is only the stack of the double inverters, without considering the cooperation between both modulation strategies. Thus, the fluctuations in the grid-side currents synthesized by both load-side currents will be obvious. To solve this problem, this paper analyzes the effect of the current pulse position on the grid-side current waveform quality, and relevant relationship between the pulse position and current harmonics is obtained according to Fourier transform. On this basis, the harmonic attenuation strategy for the dual-inverter TSMC is proposed. In the proposed strategy, the grid-side current harmonic is reduced based on the optimal duty-cycle combination, obtained from the harmonic optimization problem. The simulation and experimental result... [more]

Graphene oxide, as a new two-dimensional material, has a large specific surface area, high thermal stability, excellent mechanical stability and exhibits hydrophilic properties. By combining the carboxyl groups on the surface of graphene oxide with hydrophilic groups, surfactant-like polymers can be obtained. In this paper, based on the molecular dynamics method combined with the first nature principle, we first determine the magnitude of the binding energy of three different coupling agents—alkylamines, silane coupling agents, and haloalkanes—and analytically obtain the characteristics of the soft reaction. The high stability of alkylamines and graphene oxide modified by cetylamine, oil, and water models was also established. Then, three different chain lengths of simulated oil, modified graphene oxide−water solution, and oil-modified graphene oxide−water systems were established, and finally, the self-aggregation phenomenon and molecular morphology changes in modified graphene oxide... [more]

This paper proposes a modelling technique for Synchronous Reluctance Motors (SynRMs) based on a generalized Magnetic Equivalent Circuit (MEC). The proposed model can be used in the design of any number of stator teeth, rotor poles, and rotor barrier combinations. This technique allows elimination of infeasible machine solutions during the initial machine sizing stage, resulting in a lower cohort of feasible machine solutions that can be further optimized using finite element methods. Therefore, saturation effects, however, are not considered in the modelling. This paper focuses on modelling a generic structure of the SynRM in modular form and is then extended to a full SynRM model. The proposed model can be iteratively used for any symmetrical rotor pole and stator teeth combination. The developed technique is applied to model a 4-pole, 36 slot SynRM as an example, and the implemented model is executed following a time stepping strategy. The motor characteristics such as flux distribut... [more]

In recent years, machine learning, especially deep learning, has developed rapidly and has shown remarkable performance in many tasks of the smart grid field. The representation ability of machine learning algorithms is greatly improved, but with the increase of model complexity, the interpretability of machine learning algorithms is worse. The smart grid is a critical infrastructure area, so machine learning models involving it must be interpretable in order to increase user trust and improve system reliability. Unfortunately, the black-box nature of most machine learning models remains unresolved, and many decisions of intelligent systems still lack explanation. In this paper, we elaborate on the definition, motivations, properties, and classification of interpretability. In addition, we review the relevant literature addressing interpretability for smart grid applications. Finally, we discuss the future research directions of interpretable machine learning in the smart grid.

The present work mainly developed a mathematical model based on the plug flow model and coarse fly ash particles’ fragmentation model to describe the behavior and evolution of ash formation and the influence of the biomass feeding rate and flue gas cooling rate on ash properties, which is validated by literature data. The model considers homogeneous nucleation of alkali vapors, heterogeneous condensation of vapors on newly formed particles and fly ash particles, and collision-coagulation between aerosol particles, which is also applied to numerically study and analyze the ash formation characteristics in the cases of practical boiler pulverized fuel combustion and SO2 sulfation. The results show that the mathematical model can reasonably describe the ash formation and the influence of the biomass feeding rate and the flue gas cooling rate on the mass PSDs of PM10 and its elements. The initial nucleation temperature and initial nucleation particle size increase with the biomass feeding... [more]

The combustion of waste biomass is becoming a key challenge for the energy sector, especially in times of growing energy demand and increasing environmental awareness of society. Processing such fuels is usually demanding. Mathematical modeling makes it possible to adapt the course of the process. The best option is to use appropriate fuel mixtures. The aim of this work was to develop a simple model that would allow the pre-selection of the mixture of two types of digestate. Residues from methane fermentation of maize and apple pomace were used in the study. The paper presents both a mathematical model and laboratory tests. The practical part was to check the validity of the model estimates. The model works on the basic data from physicochemical analysis. Laboratory tests included combustion of the samples of different mixtures. We used image analysis of thermograms to determine changes during combustion, which allowed us to determine when and where the main combustion occurs. Results... [more]