bluuebunny/crossref_metadata_2025 huggingface dataset:
Quantum Gravity If Non-Locality Is Fundamental
Authors: Kauffman Stuart A.
Published: April 2022

I take non-locality to be the Michelson–Morley experiment of the early 21st century, assume its universal validity, and try to derive its consequences. Spacetime, with its locality, cannot be fundamental, but must somehow be emergent from entangled coherent quantum variables and their behaviors. There are, then, two immediate consequences: (i). if we start with non-locality, we need not explain non-locality. We must instead explain an emergence of locality and spacetime. (ii). There can be no emergence of spacetime without matter. These propositions flatly contradict General Relativity, which is foundationally local, can be formulated without matter, and in which there is no “emergence” of spacetime. If these be true, then quantum gravity cannot be a minor alteration of General Relativity but must demand its deep reformulation. This will almost inevitably lead to: matter not only curves spacetime, but “creates” spacetime. We will see independent grounds for the assertion that matter both curves and creates spacetime that may invite a new union of quantum gravity and General Relativity. This quantum creation of spacetime consists of: (i) fully non-local entangled coherent quantum variables. (ii) The onset of locality via decoherence. (iii) A metric in Hilbert space among entangled quantum variables by the sub-additive von Neumann entropy between pairs of variables. (iv) Mapping from metric distances in Hilbert space to metric distances in classical spacetime by episodic actualization events. (v) Discrete spacetime is the relations among these discrete actualization events. (vi) “Now” is the shared moment of actualization of one among the entangled variables when the amplitudes of the remaining entangled variables change instantaneously. (vii) The discrete, successive, episodic, irreversible actualization events constitute a quantum arrow of time. (viii) The arrow of time history of these events is recorded in the very structure of the spacetime constructed. (ix) Actual Time is a succession of two or more actual events. The theory inevitably yields a UV cutoff of a new type. The cutoff is a phase transition between continuous spacetime before the transition and discontinuous spacetime beyond the phase transition. This quantum creation of spacetime modifies General Relativity and may account for Dark Energy, Dark Matter, and the possible elimination of the singularities of General Relativity. Relations to Causal Set Theory, faithful Lorentzian manifolds, and past and future light cones joined at “Actual Now” are discussed. Possible observational and experimental tests based on: (i). the existence of Sub- Planckian photons, (ii). knee and ankle discontinuities in the high-energy gamma ray spectrum, and (iii). possible experiments to detect a creation of spacetime in the Casimir system are discussed. A quantum actualization enhancement of repulsive Casimir effect would be anti-gravitational and of possible practical use. The ideas and concepts discussed here are not yet a theory, but at most the start of a framework that may be useful.
Implicit Subgrid-Scale Modeling of a Mach 2.5 Spatially Developing Turbulent Boundary Layer
Authors: Araya Guillermo , Lagares Christian
Published: April 2022

We employ numerically implicit subgrid-scale modeling provided by the well-known streamlined upwind/Petrov–Galerkin stabilization for the finite element discretization of advection–diffusion problems in a Large Eddy Simulation (LES) approach. Whereas its original purpose was to provide sufficient algorithmic dissipation for a stable and convergent numerical method, more recently, it has been utilized as a subgrid-scale (SGS) model to account for the effect of small scales, unresolvable by the discretization. The freestream Mach number is 2.5, and direct comparison with a DNS database from our research group, as well as with experiments from the literature of adiabatic supersonic spatially turbulent boundary layers, is performed. Turbulent inflow conditions are generated via our dynamic rescaling–recycling approach, recently extended to high-speed flows. Focus is given to the assessment of the resolved Reynolds stresses. In addition, flow visualization is performed to obtain a much better insight into the physics of the flow. A weak compressibility effect is observed on thermal turbulent structures based on two-point correlations (IC vs. supersonic). The Reynolds analogy (u′ vs. t′) approximately holds for the supersonic regime, but to a lesser extent than previously observed in incompressible (IC) turbulent boundary layers, where temperature was assumed as a passive scalar. A much longer power law behavior of the mean streamwise velocity is computed in the outer region when compared to the log law at Mach 2.5. Implicit LES has shown very good performance in Mach 2.5 adiabatic flat plates in terms of the mean flow (i.e., Cf and UVD+). iLES significantly overpredicts the peak values of u′, and consequently Reynolds shear stress peaks, in the buffer layer. However, excellent agreement between the turbulence intensities and Reynolds shear stresses is accomplished in the outer region by the present iLES with respect to the external DNS database at similar Reynolds numbers.
Entropy Could Quantify Brain Activation Induced by Mechanical Impedance-Restrained Active Arm Motion: A Functional NIRS Study
Authors: Yu Byeonggi , Jang Sung-Ho , Chang Pyung-Hun
Published: April 2022

Brain activation has been used to understand brain-level events associated with cognitive tasks or physical tasks. As a quantitative measure for brain activation, we propose entropy in place of signal amplitude and beta value, which are widely used, but sometimes criticized for their limitations and shortcomings as such measures. To investigate the relevance of our proposition, we provided 22 subjects with physical stimuli through elbow extension-flexion motions by using our exoskeleton robot, measured brain activation in terms of entropy, signal amplitude, and beta value; and compared entropy with the other two. The results show that entropy is superior, in that its change appeared in limited, well established, motor areas, while signal amplitude and beta value changes appeared in a widespread fashion, contradicting the modularity theory. Entropy can predict increase in brain activation with task duration, while the other two cannot. When stimuli shifted from the rest state to the task state, entropy exhibited a similar increase as the other two did. Although entropy showed only a part of the phenomenon induced by task strength, it showed superiority by showing a decrease in brain activation that the other two did not show. Moreover, entropy was capable of identifying the physiologically important location.
Blockchain Technology, Cryptocurrency: Entropy-Based Perspective
Authors: Liu Feng , Fan Hao-Yang , Qi Jia-Yin
Published: April 2022

The large-scale application of blockchain technology is an expected to be an inevitable trend. This study revolves around published papers and articles related to blockchain technology, relevance analysis and sorting through the retrieved documents with six core layers of blockchain: Application Layer, Contract Layer, Actuator Layer, Consensus Layer, Network Layer and Data Layer. Based on the analysis results, this study found that China’s research is more towards the preference and application of landing and industry and smart cities with blockchain as the underlying technology. International research is more focused on the research of finance as the underlying technology of blockchain and tries to combine crypto assets with real industries, such as crypted assets and payment systems for traditional industries. This paper studies the impact of monetary entropy on cryptocurrencies in smart cities and uses the monetary entropy formula to measure the crypto-economic entropy. We use Kolmogorov entropy to describe the degree of chaos in the cryptocurrency market in a smart city. The study illustrates the current status of blockchain technology and applications from the perspective of cryptocurrency in a smart city. We find that smart cities and cryptocurrencies have a mutually reinforcing effect.
Suspicion Distillation Gradient Descent Bit-Flipping Algorithm
Authors: Ivaniš Predrag , Brkić Srdjan , Vasić Bane
Published: April 2022

We propose a novel variant of the gradient descent bit-flipping (GDBF) algorithm for decoding low-density parity-check (LDPC) codes over the binary symmetric channel. The new bit-flipping rule is based on the reliability information passed from neighboring nodes in the corresponding Tanner graph. The name SuspicionDistillation reflects the main feature of the algorithm—that in every iteration, we assign a level of suspicion to each variable node about its current bit value. The level of suspicion of a variable node is used to decide whether the corresponding bit will be flipped. In addition, in each iteration, we determine the number of satisfied and unsatisfied checks that connect a suspicious node with other suspicious variable nodes. In this way, in the course of iteration, we “distill” such suspicious bits and flip them. The deterministic nature of the proposed algorithm results in a low-complexity implementation, as the bit-flipping rule can be obtained by modifying the original GDBF rule by using basic logic gates, and the modification is not applied in all decoding iterations. Furthermore, we present a more general framework based on deterministic re-initialization of the decoder input. The performance of the resulting algorithm is analyzed for the codes with various code lengths, and significant performance improvements are observed compared to the state-of-the-art hard-decision-decoding algorithms.
Dynamics of Remote Communication: Movement Coordination in Video-Mediated and Face-to-Face Conversations
Authors: Zubek Julian , Nagórska Ewa , Komorowska-Mach Joanna , Skowrońska Katarzyna , Zieliński Konrad , Rączaszek-Leonardi Joanna
Published: April 2022

The present pandemic forced our daily interactions to move into the virtual world. People had to adapt to new communication media that afford different ways of interaction. Remote communication decreases the availability and salience of some cues but also may enable and highlight others. Importantly, basic movement dynamics, which are crucial for any interaction as they are responsible for the informational and affective coupling, are affected. It is therefore essential to discover exactly how these dynamics change. In this exploratory study of six interacting dyads we use traditional variability measures and cross recurrence quantification analysis to compare the movement coordination dynamics in quasi-natural dialogues in four situations: (1) remote video-mediated conversations with a self-view mirror image present, (2) remote video-mediated conversations without a self-view, (3) face-to-face conversations with a self-view, and (4) face-to-face conversations without a self-view. We discovered that in remote interactions movements pertaining to communicative gestures were exaggerated, while the stability of interpersonal coordination was greatly decreased. The presence of the self-view image made the gestures less exaggerated, but did not affect the coordination. The dynamical analyses are helpful in understanding the interaction processes and may be useful in explaining phenomena connected with video-mediated communication, such as “Zoom fatigue”.
There Is No Spooky Action at a Distance in Quantum Mechanics
Authors: Boughn Stephen
Published: April 2022

Einstein became bothered by quantum mechanical action at a distance within two years of Schrödinger’s introduction of his eponymous wave equation. If the wave function represents the “real” physical state of a particle, then the measurement of the particle’s position would result in the instantaneous collapse of the wave function to the single, measured position. Such a process seemingly violates not only the Schrödinger equation but also special relativity. Einstein was not alone in this vexation; however, the dilemma eventually faded as physicists concentrated on using the Schrödinger equation to solve a plethora of pressing problems. For the next 30 years, wave function collapse, while occasionally discussed by physicists, was primarily a topic of interest for philosophers. That is, until 1964, when Bell introduced his famous inequality and maintained that its violation proved that quantum mechanics and, by implication, nature herself are nonlocal. Unfortunately, this brought the topic back to mainstream physics, where it has remained and continues to muddy the waters. To be sure, not all physicists are bothered by the apparent nonlocality of quantum mechanics. So where have those who embrace quantum nonlocality gone wrong? I argue that the answer is a gratuitous belief in the ontic nature of the quantum state.
Calorimetric Measurements of Biological Interactions and Their Relationships to Finite Time Thermodynamics Parameters
Authors: Zhang Yuwei , Kowalski Gregory J.
Published: April 2022

A description and examination of the potential for calorimetry for use in exploring the entropy flows in biological and or reacting systems is presented. A calorimeter operation background is provided, and two case studies are investigated using a transient numerical simulation. The first case describes a single cell calorimeter containing a single phase material excited by heat generation source function such as joule heating. The second case is a reacting system. The basic observation parameter, the temperature, cannot be used to separate the entropy property changes and the rate of entropy production in the second case. The calculated transient response can be further analyzed to determine the equilibrium constant once the reaction equation and stoichiometric constants are specified which allows entropy property changes and the rate of entropy production to be determined. In a biological community, the equivalent of the reaction equation and a definition of an equilibrium constant are not available for all systems. The results for the two cases illustrate that using calorimetry measurements to identify the entropy flows in biological community activities requires further work to establish a framework similar to that chemical reacting systems that are based on an equilibrium type parameter.
A Risk Curtailment Strategy for Solar PV-Battery Integrated Competitive Power System
Authors: Das Arup , Dawn Subhojit , Gope Sadhan , Ustun Taha Selim
Published: April 2022

Power system networks are becoming more complex and decentralized with the foreword of deregulation in the global power sector. In this scenario, an independent system operator (ISO) is responsible for determining the appropriate actions to deliver stable and quality power to the customers connected to the network at the lowest cost without violating the system security limits. Violations of any security limit may result in system risk. The unstable and non-reliable system always has some drawbacks and is not desirable from the consumer’s point of view. A deregulated power market always keeps the consumer on the advantage side by giving stable, reliable, and less costly power. By using risk assessment tools, we identify the fault conditions and we try to minimize the risk by various uses of sequential programming methods. In this paper, a novel power system risk analysis and congestion management approach are introduced with considering meta-heuristic algorithms i.e., Slime Mould Algorithm (SMA) and Artificial Bee Colony Algorithm (ABC) in renewable energy integrated electricity market. The proposed power system risk analysis is constructed with the help of two risk valuation tools named Conditional-Value-at-risk (CVaR) and Value-at-risk (VaR). The higher negative value of VaR and CVaR represents the higher risk system and lower negative value or towards a positive value of VaR and CVaR denotes the less risk or stable system. The projected method has been experienced on the IEEE 14-bus test system and IEEE 30-bus test system to examine the usefulness of the meta-heuristic algorithm in system risk analysis under the deregulated environment. The importance of renewable energy integration in system risk curtailment has also been depicted in this work: basically, to measure the system’s risk, hence enhancing the system’s reliability and societal welfare. As a result, it will benefit both supply and demand-side participants.
Video Streaming Adaptive QoS Routing with Resource Reservation (VQoSRR) Model for SDN Networks
Authors: Elbasheer Majda Omer , Aldegheishem Abdulaziz , Alrajeh Nabil , Lloret Jaime
Published: April 2022

Video streaming has become extremely widespread, especially with the growing number of users and the spread of mobile devices, along with the increase in the availability and diversity of multimedia applications and communication technologies. Real-time video communication requires awareness of the quality of experience (QoE) to provide customers with a satisfactory service, for example, in smart cities that use video surveillance systems. The quality of service (QoS) is dependent on network performance, which directly affects the QoE. However, reliance on traditional network infrastructure and routing protocols cannot assure QoS. The emergence of software defined networks (SDN) may eliminate current network limitations. Due to SDN’s global view and programmability characteristics, such capabilities could help in providing an automated QoS control and management. This paper introduces video streaming adaptive QoS-based routing and resource reservation (VQoSRR), which gives SDN networks the ability to meet video demands and enhance user experience over best effort networks, such as the ones required for video surveillance in smart cities. In order to implement QoS-based routing (QBR), we developed algorithms for calculating routing, installing routing paths in the forwarding devices, and shifting traffic to an alternative path when QoE is violated. As well, we used queuing mechanisms to allocate resources based on the QoE requirements of video streaming. Our results indicate that resource reservation mechanisms combined with QoS-based routing enable effective control over routes and resources. Our framework guarantees the video quality as well. This technique of using video streaming would improve the tools and applications used for smart cities such as surveillance systems for hospitals and civil defense organizations.
Detection and Diagnosis of Stator and Rotor Electrical Faults for Three-Phase Induction Motor via Wavelet Energy Approach
Authors: Hussein Ameer M. , Obed Adel A. , Zubo Rana H. A. , Al-Yasir Yasir I. A. , Saleh Ameer L. , Fadhel Hussein , Sheikh-Akbari Akbar , Mokryani Geev , Abd-Alhameed Raed A.
Published: April 2022

This paper presents a fault detection method in three-phase induction motors using Wavelet Packet Transform (WPT). The proposed algorithm takes a frame of samples from the three-phase supply current of an induction motor. The three phase current samples are then combined to generate a single current signal by computing the Root Mean Square (RMS) value of the three phase current samples at each time stamp. The resulting current samples are then divided into windows of 64 samples. Each resulting window of samples is then processed separately. The proposed algorithm uses two methods to create window samples, which are called non-overlapping window samples and moving/overlapping window samples. Non-overlapping window samples are created by simply dividing the current samples into windows of 64 samples, while the moving window samples are generated by taking the first 64 current samples, and then the consequent moving window samples are generated by moving the window across the current samples by one sample each time. The new window of samples consists of the last 63 samples of the previous window and one new sample. The overlapping method reduces the fault detection time to a single sample accuracy. However, it is computationally more expensive than the non-overlapping method and requires more computer memory. The resulting window samples are separately processed as follows: The proposed algorithm performs two level WPT on each resulting window samples, dividing its coefficients into its four wavelet subbands. Information in wavelet high frequency subbands is then used for fault detection and activating the trip signal to disconnect the motor from the power supply. The proposed algorithm was first implemented in the MATLAB platform, and the Entropy power Energy (EE) of the high frequency WPT subbands’ coefficients was used to determine the condition of the motor. If the induction motor is faulty, the algorithm proceeds to identify the type of the fault. An empirical setup of the proposed system was then implemented, and the proposed algorithm condition was tested under real, where different faults were practically induced to the induction motor. Experimental results confirmed the effectiveness of the proposed technique. To generalize the proposed method, the experiment was repeated on different types of induction motors with different working ages and with different power ratings. Experimental results show that the capability of the proposed method is independent of the types of motors used and their ages.
Information Separation Network for Domain Adaptation Learning
Authors: Zhang Zeqing , Gao Zuodong , Li Xiaofan , Lee Cuihua , Lin Weiwei
Published: April 2022

The Bai People have left behind a wealth of ancient texts that record their splendid civilization, unfortunately fewer and fewer people can read these texts in the present time. Therefore, it is of great practical value to design a model that can automatically recognize the Bai ancient (offset) texts. However, due to the expert knowledge involved in the annotation of ancient (offset) texts, and its limited scale, we consider that using handwritten Bai texts to help identify ancient (offset) Bai texts for handwritten Bai texts can be easily obtained and annotated. Essentially, this is a problem of domain adaptation, and some of the domain adaptation methods were transplanted to handle ancient (offset) Bai text recognition. Unfortunately, none of them succeeded in obtaining a high performance due to the fact that they do not solve the problem of how to separate the style and content information of an image. To address this, an information separation network (ISN) that can effectively separate content and style information and eventually classify with content features only, is proposed. Specifically, our network first divides the visual features into a style feature and a content feature by a separator, and ensures that the style feature contains only style and the content feature contains only content by cross-domain cross-reconstruction; thus, achieving the separation of style and content, and finally using only the content feature for classification. This greatly reduces the impact brought by cross-domain. The proposed method achieves leading results on five public datasets and a private one.
Preserving Privacy of High-Dimensional Data by l-Diverse Constrained Slicing
Authors: Amin Zenab , Anjum Adeel , Khan Abid , Ahmad Awais , Jeon Gwanggil
Published: April 2022

In the modern world of digitalization, data growth, aggregation and sharing have escalated drastically. Users share huge amounts of data due to the widespread adoption of Internet-of-things (IoT) and cloud-based smart devices. Such data could have confidential attributes about various individuals. Therefore, privacy preservation has become an important concern. Many privacy-preserving data publication models have been proposed to ensure data sharing without privacy disclosures. However, publishing high-dimensional data with sufficient privacy is still a challenging task and very little focus has been given to propound optimal privacy solutions for high-dimensional data. In this paper, we propose a novel privacy-preserving model to anonymize high-dimensional data (prone to various privacy attacks including probabilistic, skewness, and gender-specific). Our proposed model is a combination of l-diversity along with constrained slicing and vertical division. The proposed model can protect the above-stated attacks with minimal information loss. The extensive experiments on real-world datasets advocate the outperformance of our proposed model among its counterparts.
Non-Invasive Diagnosis of Liver Fibrosis in Chronic Hepatitis C using Mathematical Modeling and Simulation
Authors: Shukla Nehal , Angelopoulou Anastasia , Hodhod Rania
Published: April 2022

Hepatitis C is a viral infection (HCV) that causes liver inflammation, and it was found that it affects over 170 million people around the world, with Egypt having the highest rate in the world. Unfortunately, serial liver biopsies, which can be invasive, expensive, risky, and inconvenient to patients, are typically used for the diagnosis of liver fibrosis progression. This study presents the development, validation, and evaluation of a prediction mathematical model for non-invasive diagnosis of liver fibrosis in chronic HCV. The proposed model in this article uses a set of nonlinear ordinary differential equations as its core and divides the population into six groups: Susceptible, Treatment, Responder, Non-Responder, Cured, and Fibrosis. The validation approach involved the implementation of two equivalent simulation models that examine the proposed process from different perspectives. A system dynamics model was developed to understand the nonlinear behavior of the diagnosis process over time. The system dynamics model was then transformed to an equivalent agent-based model to examine the system at the individual level. The numerical analysis and simulation results indicate that the earlier the HCV treatment is implemented, the larger the group of people who will become responders, and less people will develop complications such as fibrosis.
Bagged Tree and ResNet-Based Joint End-to-End Fast CTU Partition Decision Algorithm for Video Intra Coding
Authors: Li Yixiao , Li Lixiang , Fang Yuan , Peng Haipeng , Ling Nam
Published: April 2022

Video coding standards, such as high-efficiency video coding (HEVC), versatile video coding (VVC), and AOMedia video 2 (AV2), achieve an optimal encoding performance by traversing all possible combinations of coding unit (CU) partition and selecting the combination with the minimum coding cost. It is still necessary to further reduce the encoding time of HEVC, because HEVC is one of the most widely used coding standards. In HEVC, the process of searching for the best performance is the source of most of the encoding complexity. To reduce the complexity of the coding block partition in HEVC, a new end-to-end fast algorithm is presented to aid the partition structure decisions of the coding tree unit (CTU) in intra coding. In the proposed method, the partition structure decision problem of a CTU is solved by a novel two-stage strategy. In the first stage, a bagged tree model is employed to predict the splitting of a CTU. In the second stage, the partition problem of a 32 × 32-sized CU is modeled as a 17-output classification task for the first time, so that it can be solved by a single prediction. To achieve a high prediction accuracy, a residual network (ResNet) with 34 layers is employed. Jointly using bagged tree and ResNet, the proposed fast CTU partition algorithm is able to generate the partition quad-tree structure of a CTU through an end-to-end prediction process, which abandons the traditional scheme of making multiple decisions at various depth levels. In addition, several datasets are used in this paper to lay the foundation for high prediction accuracy. Compared with the original HM16.7 encoder, the experimental results show that the proposed algorithm can reduce the encoding time by 60.29% on average, while the Bjøntegaard delta rate (BD-rate) loss is as low as 2.03%, which outperforms the results of most of the state-of-the-art approaches in the field of fast intra CU partition.
Influence of Low Inlet Pressure and Temperature on the Compressor Map Limits of Electrical Turbo Chargers for Airborne Fuel Cell Applications
Authors: Schröter Jonas , Frank Daniel , Radke Valentin , Bauer Christiane , Kallo Josef , Willich Caroline
Published: April 2022

For the optimal high-efficiency operation of a PEM fuel cell system, the temperature, pressure, humidity and mass flow of the supplied air must be tuned to the fuel cell stack requirements. Especially for aircraft applications, this requires a thorough understanding of the fuel cell air supply system behavior and how it changes when the ambient pressure is below 1 bar(a) during flight. This work investigates the influence of low inlet pressures and varying inlet temperatures on the compression map of an electrical turbo charger. This is especially relevant in airborne fuel cell application and not much literature can be found on that topic. Compressor limits are evaluated experimentally and theoretically. The theory of mass flow and speed correction is compared to experimental findings and found to be applicable for the surge and speed limit of the investigated turbo chargers as long as the compressor map is not limited by the power of the electric motor and inverter. Based on this, a prediction of the compressor map for altitudes up to 10,000 m is made with the help of a developed software tool.
Integrated Three-Level Dual-Phase Inverter
Authors: Odeh Charles Ikechukwu , Lewicki Arkadiusz , Morawiec Marcin , Jąderko Andrzej
Published: April 2022

In view of reducing the number of inverter legs that provide dual-phase, three-level output voltages (as may be needed in an uninterruptible power supply), and that also provide a wide range of output frequencies (as needed in an advanced motor drive system with wide speed ranges), a three-level, dual-phase inverter topology is presented in this paper. Its three-level attribute was based on the F-type inverter topological concept, and its dual-output feature was based on the common representation of the inverter-leg concept. The proposed inverter could deliver single- and three-phase voltages to corresponding one- and three-phase loads, in common or different frequency modes of operation. A boundary between these modes of operation was established for the proposed inverter. An additional possibility of either operation in the one-phase or the three-phase system was offered by the inverter configuration. A modified carrier-based sinusoidal pulse-width modulation scheme is presented for the control of the inverter topology. The performances of the dual-phase inverter are given in the simulation results and demonstrated with a hardware prototype.
Exploiting Olive Mill Wastewater via Thermal Conversion of the Organic Matter into Gaseous Biofuel—A Case Study
Authors: Crialesi Alfredo , Mazzarotta Barbara , Santalucia Marco , Di Caprio Fabrizio , Pozio Alfonso , Santucci Alessia , Farina Luca
Published: April 2022

Olive oil is one excellence of the Italian food industry: around 300 kt yr−1 are produced, creating roughly the same amount of olive mill wastewater (OMW) to be disposed of. The present work describes a process to exploit OMW by converting its organic compounds to valuable gaseous biofuel. A sample OMW was characterized (COD, TOC, solids, and polyphenols) and submitted to membrane filtration tests to concentrate the organic compounds. Based on the results of the experiments, a treatment process was outlined: the retentate streams from microfiltration and ultrafiltration steps were fed to a cracking and a steam reforming reactor, respectively; the obtained syngas streams were then mixed and sent to a methanation reactor. The process was simulated with Aspen Plus (AspenTech©) software, assessing operating conditions and streams compositions: the final biofuel is around 81 mol.% methane, 4 mol.% hydrogen, and 11 mol.% carbon dioxide. The permeate stream cannot be directly disposed of, but both its amount and its polluting charge are greatly reduced. The heat needed by the process, mainly due to the endothermic reactions, can be obtained by burning an amount of olive pomaces, roughly corresponding to one-third of the amount left by olive treatments giving rise to the processed OMW feed.
The Effect of Different Pressure Conditions on Shock Waves in a Supersonic Steam Ejector
Authors: Li Yiqiao , Shen Shengqiang , Niu Chao , Guo Yali , Zhang Liuyang
Published: April 2022

The complex flow phenomena in a three-dimensional supersonic steam ejector were simulated with a non-equilibrium condensation model including real physical properties in different pressure conditions. The different working conditions include discharge pressure, motive pressure, and suction pressure. The influence of different pressures on shock waves in the steam ejector was investigated comprehensively. The intrinsic causes of shock wave variation with pressure conditions were explained in detail. The results show that the width of the primary shock train region expand with an increase in the motive pressure or a decrease in suction pressure. The diamond shock waves move downstream with an increase in motive pressure or a decrease in suction pressure. The shocking position in the diffuser moves upstream until it reaches the diffuser entrance with an increase in discharge pressure or a decrease in motive pressure or suction pressure. The intensity and number of oblique shock waves in the diffuser increase with an increase in motive pressure and suction pressure or a decrease in discharge pressure. The existence of only one shock wave in the diffuser is a necessary and insufficient condition for the ejector to enter a double choking mode.
Biomass and Coal Modification to Prepare Activated Coke for Desulfurization and Denitrification
Authors: Liu Guangkui , Wang Liwei , Li Yukun , Ren Xiaohan
Published: April 2022

SO2 and NOx in flue gas are serious environmental pollutants. As an excellent adsorbent, activated coke has good application potential in flue gas desulfurization and denitrification. In this study, different concentrations of NH3 and K2CO3 solutions were used to modify the activated coke made from biomass and coal, and then separate and coordinated desulfurization and denitrification experiments were carried out. The adsorption efficiency of activated coke and the adsorption capacity of SO2 and NO were compared, and the adsorption relationship between SO2 and NO was clarified. The changes of the surface functional groups of activated coke before and after adsorption and the forms of SO2 and NO after adsorption were analyzed by Fourier transform infrared spectrometer and X-ray diffractometer patterns. Results show that K2CO3 and NH3 modification can promote the adsorption of SO2 and NO in activated coke, and K2CO3 modification is more significant for improving the denitrification and desulfurization capacity. When the unmodified activated coke synergistically adsorbs SO2 and NO, there is a competitive adsorption between NO and SO2. However, when the activated coke modified with K2CO3 solution and NH3 synergistically adsorbs SO2 and NO, both have a promoting effect. After the adsorption of NH3-modified activated coke, CaSO4 and Na2SO4 crystals will appear. K2SO4 will exist after the adsorption of activated coke modified with K2CO3 solution.
Reformulation of the Used Model to Estimate Soil Temperature
Authors: Diniz Júlio M. T. , Santos Carlos A. C. dos , Silva Jean P. S. da , Rocha Álvaro B. da
Published: April 2022

The Earth is permanently surrounded by cloud cover that, particularly, is an essential component in the planet’s energy balance. In turn, cloud cover intervenes in the main conditioning factor for soil temperature: solar radiation. In particular, the soil thermal amplitude should be dampened with the attenuation of solar radiation. However, the scientific community rarely analyzes this relationship, neglecting the model that is used to estimate the soil temperature. In this context, the present study seeks to reformulate the model by inserting a variable referent to cloud cover. Thus, to achieve this objective, a physical-mathematical review of the heat flow in the vertical profile of soil is performed. The reformulated model indicates the influence of cloud cover, intervening for both the soil’s heating (nighttime period) and cooling (daytime period). Finally, the reformulated model should be employed to estimate the soil thermal behavior (in particular, on “overcast sky” days).
Understanding Microgrid Sustainability: A Systemic and Comprehensive Review
Authors: Boche Antoine , Foucher Clément , Villa Luiz Fernando Lavado
Published: April 2022

There is a growing research interest in studying microgrids as a way to overcome the lack of access to energy. These microgrids could be the key to global energy access because of their many advantages related to flexibility, efficiency, and reliability. Despite all these qualities, microgrids remain challenging to implement in a sustainable and resilient way without a clear consensus on what causes these failures. To this end, this work proposes a new paradigm to make a multidisciplinary and comprehensive review of the operation of microgrids. By reconciling the different fields inherent to microgrids, this review enables the study of microgrids within a unified framework. Microgrids will be presented through energy, information, financial, and social fields to provide the necessary elements for their systemic understanding. Each field will be presented with its internal elements, architecture, and significant issues. By elaborating on this new vision of microgrids, this article hopes to open the way to a deeper understanding of their systemic operation and diagnose their long-term sustainability.
A Novel Hybrid Transfer Learning Framework for Dynamic Cutterhead Torque Prediction of the Tunnel Boring Machine
Authors: Fu Tao , Zhang Tianci , Song Xueguan
Published: April 2022

A tunnel boring machine (TBM) is an important large-scale engineering machine, which is widely applied in tunnel construction. Precise cutterhead torque prediction plays an essential role in the cost estimation of energy consumption and safety operation in the tunneling process, since it directly influences the adaptable adjustment of excavation parameters. Complicated and variable geological conditions, leading to operational and status parameters of the TBM, usually exhibit some spatio-temporally varying characteristic, which poses a serious challenge to conventional data-based methods for dynamic cutterhead torque prediction. In this study, a novel hybrid transfer learning framework, namely TRLS-SVR, is proposed to transfer knowledge from a historical dataset that may contain multiple working patterns and alleviate fresh data noise interference when addressing dynamic cutterhead torque prediction issues. Compared with conventional data-driven algorithms, TRLS-SVR considers long-ago historical data, and can effectively extract and leverage the public latent knowledge that is implied in historical datasets for current prediction. A collection of in situ TBM operation data from a tunnel project located in China is utilized to evaluate the performance of the proposed framework.
Pore Connectivity Characteristics and Controlling Factors for Black Shales in the Wufeng-Longmaxi Formation, Southeastern Sichuan Basin, China
Authors: Zhao Fei , Dong Zaitian , Wang Chaoyong , Zhang Wenli , Yu Rui
Published: April 2022

Investigations into the connectivity and complexity of pore systems in shales are essential for understanding the flow of shale gas and the capacities of the associated reservoirs. In the present study, eight shale samples from the Wufeng-Longmaxi (WF-LMX) Formation that were collected from Well Yucan-6 in the southeast of the Sichuan Basin were analyzed for microstructural, pore network, and pore connectivity characteristics. The measurement results of low-pressure nitrogen adsorption illustrated that all shale samples contain micropores, mesopores, and macropores. Micropores and mesopores account for a high proportion of the total pores, and the dominant pore throat size is in the range of 2–6 nm. High-pressure mercury injection tests reveal that the porosity, total pore volume, and total specific surface area of pores for samples from the WF Formation are higher than those for samples from the LMX Formation. In spontaneous absorption experiments, the slopes of the absorption curves of n-decane (oil-wetting) and deionized water (water-wetting) in the WF and LMX Formations varied from 0.254 to 0.428 and from 0.258 to 0.317, respectively. These results indicate that shales in both formations exhibit mixed wettability characteristics, but lipophilic pores are better connected relative to hydrophilic pores. The total organic carbon and silica contents are the main factors controlling the pore connectivity in these shales, while the effects of other minerals are not significant. The findings of this work can improve our understanding of the pore structure characteristics of black shale.
A Control Strategy to Avoid Drop and Inrush Currents during Transient Phases in a Multi-Transmitters DIPT System
Authors: Kabbara Wassim , Bensetti Mohamed , Phulpin Tanguy , Caillierez Antoine , Loudot Serge , Sadarnac Daniel
Published: April 2022

Electrical Vehicles (EVs) have gained popularity in recent years in the automotive field. They are seen as a way to reduce the CO2 footprint of vehicles. Although EVs have witnessed significant advancement in recent years, they still have two major setbacks: limited autonomy and long recharging time. Dynamic Inductive Power Transfer (DIPT) systems permit charging EVs while driving, provide unlimited autonomy, and eliminate stationary charging time and lower battery dependency. Multiple transmitters are required to achieve DIPT; thus, dealing with transient phases is essential because every time a receiver crosses over from one transmitter to another, it experiences a new transient phase. This article presents a novel control strategy for multi-transmitter DIPT systems that ensures a continuous and stable power transfer to a moving EV. The proposed control strategy eliminates drop and inrush currents during transient phases. The control integrates a soft start feature and a degraded operating mode at a predefined maximum current value. The studied structure is a symmetrical series–series compensation network. Each transmitter coil is driven by a variable frequency inverter (around 85 kHz) to ensure Zero Phase Angle mode. The control strategy was numerically validated using MATLAB Simulink and then tested experimentally. Results show a relatively low power disruption after applying the proposed control during transmitter sequencing.
Outflow from a Biogas Plant as a Medium for Microalgae Biomass Cultivation—Pilot Scale Study and Technical Concept of a Large-Scale Installation
Authors: Zieliński Marcin , Dębowski Marcin , Kazimierowicz Joanna
Published: April 2022

Microalgae-based technologies have huge potential for application in the environment sector and the bio-energy industry. However, their cost-efficiency has to be improved by drawing on design and operation data for large-scale installations. This paper presents a technical concept of an installation for large-scale microalgae culture on digestate liquor, and the results of a pilot-scale study to test its performance. The quality of non-treated digestate has been shown to be insufficient for direct use as a growth medium due to excess suspended solids, turbidity, and organic matter content, which need to be reduced. To that end, this paper proposes a system based on mechanical separation, flotation, and pre-treatment on a biofilter. The culture medium fed into photobioreactors had the following parameters after the processing: COD—340 mgO2/dm3, BOD5—100 mgO2/dm3, TN—900 mg/dm3, and TP—70 mg/dm3. The installation can produce approx. 720 kgVS/day of microalgal biomass. A membrane unit and a thickening centrifuge (thickener) were incorporated into the design to separate and dehydrate the microalgal biomass, respectively. The total energy consumption approximated 1870 kWh/day.
Multiobjective Load Dispatch for Coal-Fired Power Plants under Renewable-Energy Accommodation Based on a Nondominated-Sorting Grey Wolf Optimizer Algorithm
Authors: Cao Yue , Li Tao , He Tianyu , Wei Yuwei , Li Ming , Si Fengqi
Published: April 2022

Coal-fired power plants are widely used to achieve a power balance in grids with renewable energy, which leads to new requirements for speediness in load dispatch. This paper presents a nondominated-sorting grey wolf optimizer algorithm (NSGWO) for the multiobjective load dispatch of coal-fired power plants that employed efficient nondominated sorting, a reference-point selection strategy, and a simulated binary crossover operator. The optimization results of the benchmark functions indicated that the NSGWO algorithm had a better accuracy and a better distribution than the traditional multiobjective grey wolf optimizer algorithm. Regarding the load dispatch of economy, environmental protection, and speediness strategies, the NSGWO had the best performance of all the simulated algorithms. The optimal-compromise solutions of the economy and speediness strategies of the NSGWO algorithm had a good distribution, which elucidated that this novel algorithm was favorable to allowing coal-fired power plants to accommodate renewable energy.
Multi-Sensor Data Fusion Approach for Kinematic Quantities
Authors: D’Arco Mauro , Guerritore Martina
Published: April 2022

A theoretical framework to implement multi-sensor data fusion methods for kinematic quantities is proposed. All methods defined through the framework allow the combination of signals obtained from position, velocity and acceleration sensors addressing the same target, and improvement in the observation of the kinematics of the target. Differently from several alternative methods, the considered ones need no dynamic and/or error models to operate and can be implemented with low computational burden. In fact, they gain measurements by summing filtered versions of the heterogeneous kinematic quantities. In particular, in the case of position measurement, the use of filters with finite impulse responses, all characterized by finite gain throughout the bandwidth, in place of straightforward time-integrative operators, prevents the drift that is typically produced by the offset and low-frequency noise affecting velocity and acceleration data. A simulated scenario shows that the adopted method keeps the error in a position measurement, obtained indirectly from an accelerometer affected by an offset equal to 1 ppm on the full scale, within a few ppm of the full-scale position. If the digital output of the accelerometer undergoes a second-order time integration, instead, the measurement error would theoretically rise up to 12n(n+1) ppm in the full scale at the n-th discrete time instant. The class of methods offered by the proposed framework is therefore interesting in those applications in which the direct position measurements are characterized by poor accuracy and one has also to look at the velocity and acceleration data to improve the tracking of a target.