Statistical analysis methods have been widely used in all industries. In well logs analyses, they have been used from the very beginning to predict petrophysical parameters such as permeability and porosity or to generate synthetic curves such as density or sonic logs. Initially, logs were generated as simple functions of other measurements. Then, as a result of the popularisation of algorithms such as the k-nearest neighbours (k-NN) or artificial neural networks (ANN), logs were created based on other logs. In this study, various industry and general scientific programmes were used for statistical data analysis, treating the well logs data as individual data sets, obtaining very convergent results. The methods developed for processing well logs data, such as Multi-Resolution Graph-Based Clustering (MRGBC), as well as algorithms commonly used in statistical analysis such as Kohonen self-organising maps (SOM), k-NN, and ANN were applied. The use of the aforementioned statis-tical method... [more]

The role of a pre-cooler is critical to the sCO2-BC as it not only acts as a sink but also controls the conditions at the main compressor’s inlet that are vital to the cycle’s overall performance. Despite their prime importance, studies on the pre-cooler’s design are hard to find in the literature. This is partly due to the unavailability of data around the complex thermohydraulic characteristics linked with their operation close to the critical point. Henceforth, the current work deals with designing and optimizing pre-cooler by utilizing machine learning (ML), an in-house recuperator and pre-cooler design, an analysis code (RPDAC), and a cycle design point code (CDPC). Initially, data computed using 3D Reynolds averaged Navier-Stokes (RANS) equation is used to train the machine learning (ML) model based on the deep neural network (DNN) to predict Nusselt number (Nu) and friction factor (f). The trained ML model is then used in the pre-cooler design and optimization code (RPDAC) to ge... [more]

In this paper, a novel SIBO (Single-Inductor Bipolar-Output) DC/DC Boost converter is proposed to power OLED (Organic Light-Emitting Diode) microdisplays. The proposed topology merges a conventional SISO (Single-Inductor Single-Output) DC/DC Boost converter and a switched capacitor inverter to produce a SIBO converter without both the cross-regulation effect and the unbalanced output voltages. Moreover, its control circuit and efficiency are almost the same as the conventional SISO Boost converter. Therefore, the novel converter maintains the power density, the small form factor, and the high efficiency of its conventional counterpart. The proposed converter was analyzed under continuous-conduction mode operation using the moving average operator and charge conservation principle. As a result, the authors proposed an equation set with the main averages and ripples of the circuit variables expressed as analytical functions of the circuit components, the input voltage, and the duty cycle... [more]

Electric vehicles (EVs) have gained in popularity over the years. The charging of a high number of EVs harms the distribution system. As a result, increased transformer overloads, power losses, and voltage fluctuations may occur. Thus, management of EVs is required to address these challenges. An EV charging management system based on machine learning (ML) is utilized to route EVs to charging stations to minimize the load variance, power losses, voltage fluctuations, and charging cost whilst considering conventional charging, fast charging, and vehicle-to-grid (V2G) technologies. A number of ML algorithms are contrasted in terms of their performances in optimization since ML has the ability to create accurate future decisions based on historical data, which are Decision Tree (DT), Random Forest (RF), Support Vector Machine (SVM), K-Nearest Neighbours (KNN), Long Short-Term Memory (LSTM) and Deep Neural Networks (DNN). The results verify the reliability of the use of LSTM for the manage... [more]

A new experimental study is presented for a combustor with a double-wall cooling design. The inner wall at the hot gas side features effusion cooling with 7-7-7 laidback fan-shaped holes, and the outer wall at the cold side features an impingement hole pattern with circular holes. Data are acquired to asses the thermal and aerodynamic behavior of the setup, using a new, scaled up, engine similar test rig. Similarity includes Reynolds, Nusselt and Biot numbers for hot gas and coolant flow. Different geometrical setups are studied by varying the cavity height between the two walls and the relative alignment of the two hole patterns at two different impingement Reynolds numbers. This article focuses on the aerodynamic performance of the setup. Instationary flow data are acquired, using a high speed stereo PIV setup. For each geometrical configuration, approximately 20 planes are recorded with a data rate of 1000 Hz by traversing the flow region of interest in the cavity between the two sp... [more]

Estimation and correct determination of vitrinite equivalent reflectance in rock is crucial for the assessment of the source rock in both conventional and unconventional hydrocarbon deposits. These parameters can be determined in laboratories on rock samples. Laboratory measurements provide only point information. However, the use of well logs could overcome discontinuities in the data and provide parameters throughout a study interval. Attention has been paid to the estimation of TOC based on well logs. Vitrinite equivalent reflectance estimation is less well discussed and most papers reported cases with high TOC content in analyzed deposits. In this paper, the estimation of improved Ro is presented using a calculated maturity indicator with well logs. As the organic matter content is not high, additional steps were required for the calculation. To improve the quality of the fit and to find similar intervals, the data were grouped using cluster and neural network analysis. The next st... [more]

Axial slot casing treatment is a common method to extend the stall margin of a compressor. Based on the mechanism of unsteady flow control, this paper redesigns axial slots with large circumferential interval and small opening area. To test the effect of this axial slot structure, unsteady numerical simulations were carried out with different slot areas and circumferential intervals. The results show that this novel axial slot casing treatment can significantly improve compressor stall margin. Meanwhile, compared with the traditional axial slot, the efficiency loss is greatly reduced. The flow field analysis shows that the new axial slot structure proposed in this paper can suppress the development of tip leakage vortex and unsteadiness in the tip region at the near stall condition through decreasing the tip loading periodically. Moreover, we find that the slot area is proportional to the improvement of stability margin. Under the same slot area, an excessive number of slots is not con... [more]

One of the possibilities to achieve energy neutrality of wastewater treatment plants (WWTPs) is the implementation of the anaerobic co-digestion strategy. However, a key factor in its successful implementation on the technical scale is the application of components with complementary composition to sewage sludge (SS). In the 7resent study, the influence of adding various co-substrates on the energy balance of anaerobic digestion was evaluated. The following organic wastes were used as additional components to SS: organic fraction of municipal solid waste (OFMSW) and distillery spent wash (DW) applied in two- and three-component systems. The experiments were performed in semi-flow anaerobic reactors with the volume of 40 L under mesophilic conditions (35 °C) at hydraulic retention time (HRT) of 20, 18, and 16 d. The application of substrates to SS resulted in enhancements of methane yields as compared to SS mono-digestion. The statistically significant differences were observed in terti... [more]

Scarcity of resources and their waste, as well as deteriorating quality of life and the environment, are pressing problems of modern civilisations. Rational and efficient energy consumption is one of the possibilities for preventing harmful practices and the degradation of ecosystems. Understanding the consumer’s way of thinking and acting by identifying his needs and preferences are essential for effective efforts for smart, sustainable, and inclusive economic growth. Therefore, the aim of this article was a comprehensive socioeconomic analysis of particular behavioural types of energy consumers, as a continuation of the authors’ previous research. The paper uses statistical methods (chi-square test and correspondence analysis) dedicated to non-metric variables for an effective analysis of the data obtained from the questionnaires. The identification of socioeconomic factors was carried out on a representative sample of n = 4506 respondents from eight European countries (the Czech Rep... [more]

Power forecasting models offer valuable insights on the electricity consumption patterns of clients, enabling the development of advanced strategies and applications aimed at energy saving, increased energy efficiency, and smart energy pricing. The data collection process for client consumption models is not always ideal and the resulting datasets often lead to compromises in the implementation of forecasting models, as well as suboptimal performance, due to several challenges. Therefore, combinations of elements that highlight relationships between clients need to be investigated in order to achieve more accurate consumption predictions. In this study, we exploited the combined effects of client similarity and causality, and developed a power consumption forecasting model that utilizes ensembles of long short-term memory (LSTM) networks. Our novel approach enables the derivation of different representations of the predicted consumption based on feature sets influenced by similarity an... [more]

The rising adoption of renewable energy sources means we must turn our eyes to limitations in traditional energy systems. Intermittency, if left unaddressed, may lead to several power-quality and energy-efficiency issues. The objective of this work is to develop a working tool to support photovoltaic energy forecast models for real-time operation applications. The current paradigm of intra-hour solar-power forecasting is to use image-based approaches to predict the state of cloud composition for short time horizons. Since the objective of intra-minute forecasting is to address high-frequency intermittency, data must provide information on and surrounding these events. For that purpose, acquisition by exception was chosen as the guiding principle. The system performs power measurements at 1 Hz frequency, and whenever it detects variations over a certain threshold, it saves the data 10 s before and 4 s after the detection point. A multilayer perceptron neural network was used to determin... [more]

Currently, lightning phenomenon, mechanisms, and impacts on lives and infrastructures have been satisfactorily decoded and studied. Sound knowledge of lightning parameters is available in international literature. Yet, there are few studies referring to lightning statistics such as the number of flashes over an area, current amplitude distribution, etc., except for official documentation from national weather services, perhaps because of the stochastic nature of lightning. This work presents full recorded data for lightning flashes over wind farms distributed at the Hellenic territory. The data come from real time measurements at wind farm stations from 2011 to 2020 and concern number of CG flashes and lightning current amplitude. They are statistically processed and analyzed and contain useful information regarding the lightning characteristics of various geographic regions all over the country. Furthermore, the study displays data from field measurements of ground resistance at wind... [more]

In order to analyze the nature of electrical demand series in deregulated electricity markets, various forecasting tools have been used. All these forecasting models have been developed to improve the accuracy of the reliability of the model. Therefore, a Wavelet Packet Decomposition (WPD) was implemented to decompose the demand series into subseries. Each subseries has been forecasted individually with the help of the features of that series, and features were chosen on the basis of mutual correlation among all-time lags using an Auto Correlation Function (ACF). Thus, in this context, a new hybrid WPD-based Linear Neural Network with Tapped Delay (LNNTD) model, with a cyclic one-month moving window for a one-year market clearing volume (MCV) forecasting has been proposed. The proposed model has been effectively implemented in two years (2015−2016) and unconstrained MCV data collected from the Indian Energy Exchange (IEX) for 12 grid regions of India. The results presented by the propo... [more]

Thermochemical energy storage systems from carbonates, mainly those based on calcium carbonate, have been gaining momentum in the last few years. However, despite the considerable interest in the process, the Technology Readiness Level (TRL) is still low. Therefore, facing the progressive development of the technology at different scales is essential to carry out a comprehensive risk assessment and a Failure Mode Effect and Analysis (FMEA) process to guarantee the safety and operation of the technology systems. In this study, the methodology was applied to a first-of-its-kind prototype, and it is a valuable tool for assessing safe design and operation and potential scaling up. The present work describes the methodology for carrying out these analyses to construct a kW-scale prototype of an energy storage system based on calcium carbonate. The main potential risks occur during the testing and operation stages (>50% of identified risks), being derived mainly from potential overheating in... [more]

The concept of risk is well known in the energy sector. It is normally recognized when it comes to price and cost forecasting, annual production calculation, or evaluating project lifetime. Nevertheless, it should be pointed out that the quantitative evaluation of risk is usually difficult. The discount rate is the only parameter reflecting risk in the discounted cash flow analysis. Therefore, knowledge of the discount rate along with the major components affecting its level is of fundamental significance for making investment decisions, capital budgeting, and project management. By referring to the standard coal-fired power generation projects the authors of the paper tackle the analysis of the composition of discount rate for onshore wind farm technologies in the Polish conditions. The study was carried out on the basis of a typical (hypothetical) onshore wind farm project assessed at the feasibility stage. To enable comparisons and discussions, it was assumed that the best reference... [more]

This article models a system of partial differential equations (PDEs) for the thermal and solute characteristics under gradients (concentration and temperature) in the magnetohydrodynamic flow of Casson liquid in a Darcy porous medium. The modelled problems are highly non-linear with convective boundary conditions. These problems are solved numerically with a finite element approach under a tolerance of 10−8. A numerical algorithm (finite element approach) is provided and a numerical procedure is discussed. Convergence is also observed via 300 elements. Simulations are run to explore the dynamics of flow and the transport of heat and mass under parametric variation. To examine the impact of a temperature gradient on the transport of mass and the role of a concentration gradient on the transport of heat energy, simulations are recorded. Remarkable changes in temperature and concentration are noted when Dufour and Soret numbers are varied.

Isopropanol has potential as a future bio-derived fuel and is a promising substitute for ethanol in gasoline blends. Even so, little has been done in terms of high-temperature chemical kinetic speciation studies of this molecule. To this end, experiments were conducted in a shock tube using simultaneous CO and H2O laser absorption measurements. Water and CO formation during isopropanol pyrolysis was also examined at temperatures between 1127 and 2162 K at an average pressure of 1.42 atm. Species profiles were collected at temperatures between 1332 and 1728 K and at an average pressure of 1.26 atm for equivalence ratios of 0.5, 1.0, and 2.0 in highly diluted mixtures of 20% helium and 79.5% argon. Species profiles were also compared to four modern C3 alcohol mechanisms, including the impact of recent rate constant measurements. The Li et al. (2019) and Saggese et al. (2021) models both best predict CO and water production under pyrolysis conditions, while the AramcoMech 3.0 and Capriolo... [more]

Nonintrusive Load Monitoring (NILM) uses computational methods to disaggregate and classify electrical appliances signals. The classification is usually based on the power signatures of the appliances obtained by a feature extractor. State-of-the-art results were obtained extracting NILM features with convolutional neural networks (CNN). However, it depends on the training process with large datasets or data augmentation strategies. In this paper, we propose a feature extraction strategy for NILM using the Scattering Transform (ST). The ST is a convolutional network analogous to CNN. Nevertheless, it does not need a training process in the feature extraction stage, and the filter coefficients are analytically determined (not empirically, like CNN). We perform tests with the proposed method on different publicly available datasets and compare the results with state-of-the-art deep learning-based and traditional approaches (including wavelet transform and V-I representations). The result... [more]

Different technological, socio-economic, geopolitical, and demographic factors have a significant influence on labor markets. Currently, due to COVID-19, the global economy is in a challenging situation, and millions of people from different countries have lost their jobs. The employee’s mental health and well-being are in risk conditions. In the coming years, the Polish energy sector will face several transformations. Emerging technologies are intended to deal with the problems in energy management. One of the main industry forces is human capital, people who will be able to project and manage the innovative technologies. Thus, this paper examines the determinants of managerial competences transformation in the energy industry from the labor market perspective. The paper fulfills the research gap in the energy manager profession’s transformation in Poland. The aim of the paper was to present the current state of the energy manager profession in Poland. Two methodological approaches we... [more]

Forecasting wind speed has become one of the most attractive topics to researchers in the field of renewable energy due to its use in generating clean energy, and the capacity for integrating it into the electric grid. There are several methods and models for time series forecasting at the present time. Advancements in deep learning methods characterize the possibility of establishing a more developed multistep prediction model than shallow neural networks (SNNs). However, the accuracy and adequacy of long-term wind speed prediction is not yet well resolved. This study aims to find the most effective predictive model for time series, with less errors and higher accuracy in the predictions, using artificial neural networks (ANNs), recurrent neural networks (RNNs), and long short-term memory (LSTM), which is a special type of RNN model, compared to the common autoregressive integrated moving average (ARIMA). The results are measured by the root mean square error (RMSE) method. The compar... [more]

A standard model, one of the lattice Boltzmann models for incompressible flow, is broadly applied in mesoscopic fluid with obvious compressible error. To eliminate the compressible effect and the limits in 2D problems, three different models (He-Luo model, Guo’s model, and Zhang’s model) have been proposed and tested by some benchmark questions. However, the numerical accuracy of models adopted in complex geometry and the effect of structural complexity are rarely studied. In this paper, a 2D dimensionless steady flow model is proposed and constructed by fractal geometry with different structural complexity. Poiseuille flow is first simulated to verify the code and shows good agreements with the theoretical solution, supporting further the comparative study on four models to investigate the effect of structural complexity and grid resolution, with reference results obtained by the finite element method (FEM). The work confirms the latter proposed models and effectively reduces compress... [more]

The rapid development of innovations in the industry 4.0 era led to new or evolved companies. At the same time, the accepted concept of carbon-free development requires building a new philosophy for the company’s management. The paper aims to analyse the key attributes of teal organisations (as a new type of a company) from the energy sector (as a core sector for carbon-free transformation). The paper summarises the core features of teal organisations and their attributes. In the paper, three hypotheses are tested: innovations and technologies are the most used attributes among teal organisations from the energy sector; organisational and corporate culture are the least used attributes among teal organisations from the energy sector; in the energy sector, the companies that have the attributes of teal organisations primarily work in countries with a high level of innovation and information technologies (as a core indicator of Industry 4.0) and economic development. For testing the hypo... [more]

The present study investigates the thermo-hydraulic characteristics of a microchannel sink with novel trefoil Shaped ribs. The motivation for this form of rib shape is taken from the design of lung alveoli that exchange oxygen and carbon dioxide. This study has been conducted numerically by using a code from the commercially available Fluent software. The trefoil shaped ribs were mounted on the centerline of different walls of the microchannel in three different configurations. These consisted of base wall trefoil ribs (MC-BWTR), sidewall trefoil ribs (MC-SWTR), all wall trefoil ribs (MC-AWTR) and smooth channel (MC-SC) having no ribs on its wall. The streamline distance between the ribs was kept constant at 0.4 mm, and the results were compared by using pressure drop (∆p), Nusselt number (Nu), thermal resistance (Rth) and thermal enhancement factor (η). The results indicated that the addition of trefoil ribs to any wall improved heat transfer characteristics at the expense of an incre... [more]

We examine the predictive value of gold-to-silver and gold-to-platinum price ratios, as proxies for global risks affecting the realized variance (RV) of oil-price movements, using monthly data over the longest available periods of 1915:01−2021:03 and 1968:01−2021:03, respectively. Using the two ratios, we find statistically significant evidence of in-sample predictability for increases in RV for both ratios. This finding also translates into statistically significant out-of-sample forecasting gains derived from these two ratios for RV. Given the importance of real-time forecasts of the volatility of oil-price movements, our results have important implications for investors and policymakers.

The growing importance of creative knowledge workers as a resource of particular significance for the growth of organizations is becoming one of the greatest challenges of the knowledge-based economy. Thus, the growing role of creative organizations contributes to building the economic potential of cities, regions, countries, but also of various organizations operating in the market. The development of civilization at its current stage has always been a source of this type of activity. Hence, the issue of understanding how creative knowledge workers operate has been and continues to be addressed by researchers around the world in recent years. The topic presented in this article on the knowledge and creativity of employees and their impact on the growth of creative organizations to a certain extent responds to this demand. The aim of the article is to clarify and extend the conceptualization in terms of creative activities performed by knowledge workers and the correlations with their... [more]