Class Of Schemes Research Articles

Renewable Energy Investments, Support Schemes and the Dirty Option

ABSTRACTIn a real options framework, we analyze the behavior of a large energy producer who can invest in a portfolio of Renewable Energy Source (RES) and dirty energy source. Competitive fuel prices challenge the investments in RES. Given a budget constraint, the agent allocates the optimal capacities of both energy instalments and selects the optimal investment time. We use the model to compare the effectiveness of classical support schemes such as Feed‐in Tariffs or Green Certificate with respect to forms of taxation of dirty technology such as Carbon Taxes or Carbon Permits. This paper proposes a conceptual framework and qualitative analysis to understand which support system enhances the attractiveness of renewable energy investments.

A Relaxation Scheme for the Simulation of Two‐Phase Flows With Inaccessible Pore Volume in Polymer Flooding

ABSTRACTThe simulation of polymer injection in a reservoir is of paramount importance in enhanced oil recovery. Despite decades of research, the computation of polymer flows in porous media remains a challenging task. The main difficulty lies in the necessity to take into account the effect of inaccessible pore volumes (IPV), for which standard closure laws give rise to a weakly hyperbolic or even non‐hyperbolic system. In the latter case, exponential instabilities may appear at the continuous level, which must be addressed at the discrete level so as to prevent a premature stop of the numerical simulations. The notion of IPV was introduced by engineers in order to account for the following observation: when a polymer solution is injected into an initial core saturated with water, the breakthrough of the polymer at the exit occurs before that of the water in which it is injected. It seems that due to their large size, the polymer molecules cannot insinuate themselves into all pores as well as water. Having less volume to flood, the polymer molecules see their speed increased, hence the ad hoc acceleration factor associated with the polymer. In this work, we propose a relaxation method that guarantees some practical robustness for all IPV laws. This is achieved by replacing the original system by a relaxation model which is always hyperbolic. The designed relaxation model involves two parameters which enable us not only to adjust the correct amount of numerical dissipation, but also to ensure positivity for some critical quantities such as water saturation and polymer concentration. Extensive numerical tests are performed in order to compare the relaxation scheme to the more classical upwind scheme for several IPV laws.

Multivariate asymptotic normality determined by high moments

We extend a general result showing that the asymptotic behavior of high moments, factorial or standard, of random variables, determines asymptotically normality, from the one dimensional to the multidimensional setting. This approach differs from the usual moment method which requires that the moments of each fixed order converge. We illustrate our results by considering a joint distribution of the numbers of bins (having the same, finite, capacity) containing a prescribed number of balls in a classical allocation scheme.

Выбор сопротивления нагрузки приемной электрически малой антенны по критерию минимальной неравномерности группового времени запаздывания принятого сигнала

The accuracy of determining coordinates in terrestrial radio navigation systems (RNS) depends on the receiving antenna frequency response irregularity: received signal power and group delay time (GD). Due to the limited space on the carrier, the RNS receiving antennas are small and cannot be effectively matched with feeder over the entire operating frequency band. The paper considers two options for the RNS receiver input circuit. First is a classical matching scheme and second is direct connection of the antenna to the receiver input. It is shown that the most uniform frequency characteristics are achieved when the antenna is connected directly to reciever. In this case, the maximum received signal power occurs when the antenna input resistance module and the load resistance are equal. At the same time, high load resistance increases the frequency response irregularity. Therefore, the choice of load resistance should be made compromising manner, taking into account signal level, available input amplifier gain and the allowed frequency response irregularity.

Electromechanical processes in electric power steering system based on permanent magnet synchronous motor

Relevance. Electric power steering of vehicles successfully competes with hydraulic boosters of similar purposes, showing high efficiency, energy saving and environmental friendliness. Aim. To study and research electromechanical processes of electric power steering system based on permanent magnet synchronous motor. Methods. Mathematical and numerical modeling using the Matlab/Simulink software package. Results. The article discusses the operating modes of an electric power steering based on an electric motor with permanent magnets. The authors analyzed two classic schemes for constructing steering systems with electric power steering – with the electric motor placed on the steering column and on the steering rack. Block diagrams of the mechanical and electrical parts of the steering system have been developed. Based on mathematical dependencies characterizing the operating modes of the steering system, a complete dynamic simulation model of the electric power amplifier was obtained on the MATLAB/Simulink platform. Based on a preliminary analysis of control methods and algorithms in the system to solve the problem of control stability, PI controllers with low-pass filters are implemented to regulate the current and voltage of the electric motor depending on the speed of the vehicle and the angle of rotation of the steering wheels. The simulation results were used to design a real electric power steering for a specific vehicle. Conclusions. The complete simulation model of an electric booster based on a synchronous motor with permanent magnets in a car steering system obtained by the authors adequately reflects the dynamic control processes and can be used in the design of automotive vehicles.

A multi-dimensional, robust, and cell-centered finite-volume scheme for the ideal MHD equations

We present a new multi-dimensional, robust, and cell-centered finite-volume scheme for the ideal MHD equations. This scheme relies on relaxation and splitting techniques and can be easily used at high order. A fully conservative version is not entropy satisfying but is observed experimentally to be more robust than standard constrained transport schemes at low plasma beta. At very low plasma beta and high Alfvén number, we have designed an entropy-satisfying version that is not conservative for the magnetic field but preserves admissible states and we switch locally a-priori between the two versions depending on the regime of plasma beta and Alfvén number. This strategy is robust in a wide range of standard MHD test cases, all performed at second order with a classic MUSCL-Hancock scheme.

Active flux based adaptive and non-adaptive observer for sensorless interior permanent magnet synchronous machine drive

The use of the interior permanent magnet synchronous machine (IPMSM) drive has profoundly increased in a large number of applications due to numerous advantages. Owing to the disadvantages of mechanical sensors, sensorless control techniques are employed to enhance the performance of the IPMSM drive by removing the effect of noise and gain drift due to the sensor, increasing reliability, cost saving, and reducing overall size. This article presents the comparative analysis between the adaptive observer and non-adaptive extended electromotive force (EEMF) observer based on the active flux concept in a stationary reference frame (α–β). Moreover, the effect of slot harmonics and non-sinusoidal distribution of rotor flux is present in the three-phase IPMSM, this problem is considered as the control system disturbances in this article. Due to the non-sinusoidal distribution of flux and slot harmonics, the observer structure in the rotating reference frame (d–q) fails to estimate at the low-speed operation range. Comparative analysis between adaptive and non-adaptive observer structures is provided for a wide speed range. The effectiveness of the observer structures is examined using the classical field-oriented control scheme. In the end, simulation and experimental results are demonstrated to validate the performance of the sensorless control scheme using the adaptive and non-adaptive observer structures for the three-phase IPMSM drive setup.

Traditional and innovative in the poetics of I. S. Nikitin (to the 200th anniversary of the birth)

The article examines I. S. Nikitin’s poetics from the point of view of its continuity in relation to the achievements of his predecessors, lyric poets, and those original features the poet himself developed. The main method is an end-to-end textual analysis of I. S. Nikitin’s poetry collection in the unity of content and form. Additionally, the study used the research methods of linguistic stylistics, linguistic poetics, semasiology, and structural-semantic syntax. The metrical features of poetic texts are given in the interpretations of M. L. Gasparov’s school. Though I. S. Nikitin considered A. V. Koltsov his immediate teacher, his poems contain noticeable images, motifs, and linguistic reminiscences referring to other poets’ creative work, especially A. S. Pushkin’s. I. S. Nikitin creatively interpreted certain Pushkinian linguo-poetic techniques (the antithesis of vice–virtue in the reflection on the role of the poet and poetry, the illustrative comprehension of canonical Christian texts, the realistic use of the ballad and idyll genres, the patriotic pathos of civic poems, the use of classical metrical schemes, and others). I. S. Nikitin made a significant contribution to improving the artistic language of Russian realist poetry. He developed the song genre in literature, introduced a variety of dramaturgical principles into lyric poetry, and proposed original compositional schemes for philosophical, social, and landscape poems. In his writings, I. S. Nikitin refined the poetic syntax of homogeneous constructions. Moreover, he extended the motivic boundaries of Russian lyric poetry through elaboration and precise observations, as well as enriched the linguo-stylistic repertoire of its vocabulary. I. S. Nikitin’s work is organically, closely, and versatilely connected with the content and language development of Russian poetry in the second half of the 19th century.

Leveraging quantum uncertainty: Quantum randomness through the lens of classical communication networks

The generation of random numbers and the study of its properties have been an elusive field for a fair portion of the century. The application of random numbers is employed in many use cases such as cryptography, neural networks, numerical simulation, and gambling. The performance of each of these use cases is profoundly impacted by the employed random numbers; henceforth, the quality of randomness is of critical importance when it comes to their usage. A poorly generated random number can make a security system vulnerable, or any numerical or statistical evaluation misleading. Although various modes of classical random number generators exist and still function to provide strong cryptographic properties, emergence of quantum mechanical randomness has shed light on a novel path of generating certified randomness which supersedes the classical counterpart in terms of security. Harnessing quantum mechanical phenomena enables generation of true random numbers which can be certified and further implemented to elevate the net quality of the specific use cases. In this work, we generate and analyze random numbers from three different sources — 50: 50 beam splitter (BS), quantum key distribution (QKD) setup with classical post-processing scheme, and a commercially available quantum random number generator (QRNG) (ID Quantique (IDQ)). The quality of the generated random numbers from the various sources is checked in statistical tests and compared. Further on, we have developed a system which implements the QRNG-based random numbers to facilitate message authentication code (MAC) and one time password (OTP) protocols, demonstrating a communication network application. In this manner we discuss about a network which integrates quantum mechanics to the current classical networking approaches to enhance certain aspects of the networking protocol — in this case, the security.

Dimensionality reduction using neural networks for lattice-based cryptographic keys

Post Quantum Cryptography has received an increasing amount of active research. This has been made prominent by the ever-growing field of quantum computing which poses a formidable threat to the modern cybersecurity landscape. Recently, post quantum schemes have been standardized for adoption into existing security services and protocols. In comparison to contemporary cryptographic schemes, these approaches are lagging behind in terms of performance with regards to functional speed and package sizes. A study into the various applications of neural networks used in classical and post quantum cryptographic schemes has been explored to demonstrate their different possible applications within the various fields of cybersecurity. The main contribution of this work is to investigate the feasibility of dimensionality reduction using the autoencoder neural network on lattice-based keys generated by the Kyber key encapsulation mechanism scheme. Moreover, this work also presents a comparative analysis of the different implemented autoencoder models to showcase their relative performance.

LearningTuple: A packet classification scheme with high classification and high update

Packet classification is widely used in network infrastructures and is the key technique that supports security and other functions. The real-time nature of network services naturally demands high classification speed, while the emerging SDN makes rule changes more flexible, thus placing higher demands on the performance of rule update in classification schemes. In this paper, Learning Tuple(LT) is proposed to achieve high classification performance for packets while maintaining the high update characteristics of tuple space-based schemes. Specifically, to solve the issue of excessive tuples and rule overlap due to merging tuples, LT iteratively divides the space by using rule overlap and hash collisions as negative feedback and applies a reinforcement learning algorithm, SARSA, at each level to ensure its reasonableness. Efficient space partitioning guides the construction of tuples, and an excellent rule mapping method called PLR is designed, which improves classification performance. Experimental results demonstrate that compared with classic and advanced classification schemes TSS, TupleMerge, MultilayerTuple, PartitionSort, HybridTSS, and TupleTree, LT achieves average classification performance improvements of 9.23x, 1.74x, 1.45x, 2.85x, 1.37x and 1.25x, as well as average update performance improvements of 1.83x, 6.75x, 1.22x, 6.16x, 1.21x, 10.66x, respectively.

Interface stabilization and propagation in phase field models of solidification: resolving the issue of large driving forces

Abstract One of the long-standing problems in the phase field, namely, combining the principles of thermodynamics and capillarity with the numerical aspects of interface propagation in simulations, is re-investigated. Numerical schemes are discussed which allow for stable simulations with arbitrary driving forces, considering or excluding capillarity. We re-investigate a classical stabilization scheme that decouples interface stabilization from curvature evaluation, ensuring stable simulations even under large driving forces. A novel mathematical analysis gives a rigorous estimate for the time stepping and a numerical value of the required stabilization strength. The proposed stabilization scheme is benchmarked for 3-dimensional dendritic growth under directional solidification conditions for different solidification speeds.

A cooperative timestamp-free clock synchronization scheme based on fast unscented Kalman filtering for time-sensitive networking

Clock synchronization, built on the classical two-way message exchange scheme, is the key prerequisite for the normal operation of time-sensitive networking (TSN). In practical TSN, the imperfect oscillator caused by environmental changes leads to clock parameters drift. Moreover, synchronization errors accumulate in multi-hop networks, making it difficult for nodes at the edge of the network to achieve precise synchronization performance. Additionally, in some industrial and vehicular scenarios, the energy consumption and complexity of clock synchronization are important factors that need to be considered. To address these problems, this paper proposes a cooperative synchronization clock offset and clock skew joint tracking algorithm based on fast Unscented Kalman filter (FUKF). To further reduce the computation and energy consumption caused by clock synchronization, we introduce randomized singular value decomposition and timestamp-free exchange. The former uses small sub-matrices approximations to replace extremely high-dimensional matrices, reducing computational time in the update stage of the UKF. The latter reduces energy consumption by setting response intervals at the receiving end, eliminating the need for timestamp exchange during the synchronization process. Therefore, this algorithm can achieve long-term synchronization without requiring excessive computational and communication overhead. The results show that the proposed method, while maintaining accuracy unchanged, reduced the running time by 20% to 90% as the number of observations increased, thus verifying the effectiveness of the algorithm.

PARAMETER-UNIFORM HYBRID NUMERICAL SCHEME FOR SINGULARLY PERTURBED PARABOLIC CONVECTION-DIFFUSION PROBLEMS WITH DISCONTINUOUS INITIAL CONDITIONS

This article presents a parameter-uniform hybrid numerical technique for singularly perturbed parabolic convection-diffusion problems (SPPCDP) with discontinuous initial conditions (DIC). It utilizes the classical backward-Euler technique for time discretization and a hybrid finite difference scheme ( which is a proper combination of the midpoint upwind scheme in the outer regions and the classical central difference scheme in the interior layer regions(generated by the DIC)) for spatial discretization. The scheme produces parameter-uniform numerical approximations on a piecewise- uniform Shishkin mesh. When the perturbation parameter ε(0 < ε ≪ 1) is small, it becomes difficult to solve these problems using the classical numerical methods (standard central difference or a standard upwind scheme) on uniform meshes because discontinuous initial conditions frequently appear in the solutions of this class of problems. The method is shown to converge uniformly in the discrete supremum with nearly second-order spatial accuracy. The suggested method is subjected to a stability study, and parameter-uniform error estimates are generated. In order to support the theoretical findings, numerical results are presented.

Analysis of the mechanical behavior of porous materials containing two populations of voids under dynamic spherical loading

A computational homogenization analysis is performed on three-dimensional representative volume elements (RVE) that contain two distinct populations of voids, to demonstrate the influence of the interaction between cavities. RVEs are constructed as cubic elastic perfectly-plastic matrices embedding two families of spherical voids, and subjected to dynamic loading under homogeneous kinematic boundary conditions. Multiple microstructure models are considered by varying the number, position, and size of voids to evaluate the micro-inertia contribution to the overall macroscopic stress. Velocity fields within numerical RVEs are investigated to reveal the interaction of voids and their key role in the dynamic macroscopic response of the porous material. Based on numerical simulation results, a homogenization analytical model considering void interaction is proposed to describe the mechanical behavior under dynamic loadings. This model relies on adjusting the strain rate level at the boundary of unit cells composing the porous material. Comparison between our numerical and analytical results with those obtained using the classical Taylor homogenization scheme highlights the limitations of the Taylor model in the case of porous materials under dynamic loading.

(Digital Presentation) The Effects of Heat Treatment on Electroreduction of Tungsten (VI) Oxide

According to the classic scheme of the FFC Cambridge process, oxides of refractory metals are reduced in the solid state. Before electrolysis, oxides are shaped into cylindrical preforms and annealed at high-temperatures (~1000 °С). Therefore, the purpose of this study is to establish the effect of heat treatment of the initial sample of tungsten trioxide on its electrochemical reduction on a solid cathode in a CaCl2–NaCl melt.There are two types of tablets (preforms) were used for research: non-sintered (only compressed) WO3 and annealed at a temperature of 1000 °C. The surface of a pelletized tungsten trioxide sample without sintering is characterized by a uniform distribution of particles, shown in the SEM image (Fig. a). The particles agglomeration is characteristic for the sample WO3 after heat treatment (1000 °С) (Fig. b), which leads to a decrease in the area and an increase in the size of the voids. The unsintered sample has a larger surface area between the particles due to their dispersed state, which facilitates the penetration of the melt compared to the annealed sample.Electrochemical reduction of pressed WO3 samples (d=0.8 cm, h=0.15±0.20 cm, m=0.45–0.50 g) was carried out under galvanostatic conditions (800 °С) with using steel as the cathode and graphite as the anode. It was established that preliminary heat treatment of WO3 does not contribute to its electrochemical reduction. After applying 1.20 A·h of electricity, the porous granules of unsintered WO3 were completely transformed into metallic tungsten (W), which is shown in Fig. c, line 1. However, sintered samples after electrolysis (quantity of electricity is 1.42 A·h) reduced only partially: W – 74.1%; CaWO4 – 25.9% (Fig. c, line. 2).The results show that the reduction occurs more intensively in samples with more micropores, through which mass transfer occurs at the phase interface: tungsten compound to be reduced molten electrolyte mixture. That is why in the unsintered WO3 sample, the electrochemical reduction is faster. It can be assumed that the degree of reduction of WO3 on a solid electrode in CaCl2–NaCl also depends on its crystal structure. The annealed sample (tetragonal structure) is less susceptible to electrochemical reduction compared to the unannealed sample of tungsten trioxide (monoclinic structure). This is due to the fact that tetragonal WO3 (above 740 °C) is resistant to chemical attack, a poor conductor of electricity and has a low surface area. Monoclinic WO3 (from 17 to 330 °C) is more reactive, a better conductor of electricity and has a higher surface area. Figure 1

Privacy-preserving keyword query quantum scheme for outsourced data in cloud environments

Cloud computing, as a popular technology in recent years, has greatly facilitated the development of data outsourcing services. However, when users access sensitive data stored in the cloud, ensuring the security of data remains a pressing challenge. In this paper, we present a privacy-preserving keyword query scheme for outsourced data in cloud environment. Furthermore, to implement this scheme, we propose a series of quantum basic protocols with single qubits. The proposed basic protocols do not require the execution of quantum gate operations, and the necessary measurements are only Bell measurements based on measurement-device-independence. Therefore, it is practical and feasible under current technology. Moreover, compared with classical schemes, our scheme has higher security (i.e., quantum security). Finally, we conduct simulation experiments in IBM Qiskit to verify the correctness and feasibility of the critical parts of the scheme.

Transforming recycled polyester/cotton (Gossypium hirsutum L.) fibers into dye-free and eco-friendly denim fabrics: Preparation, properties evaluation, and feasibility analysis

Conventional denim production is plagued by the issue of wastewater pollution from warp dyeing. In this investigation, recycled cotton (R-CO), virgin cotton (V-CO), and dope-dyed recycled polyester (R-PET) fibers were spun into blue/white spaced warp yarns through a dual-feed-opening rotor spinning technique. These yarns were woven with V-CO weft yarns to produce fabrics featuring the classic denim color scheme of blue and white stripes, without the need for warp dyeing and complex finishing processes. The resulting fabrics fulfilled industry standards for tensile strength (>600 N), tearing resistance (>50 N), abrasion resistance (>25000 cycles), pH (≈6.5), and formaldehyde content (<10 mg/kg). The fabrics' air/moisture permeability and wearability (including crease-resistance, flexibility, drapability, and washing size stability) were outstanding. The fabrics' light and crocking colorfastness ratings all exceed grade 4, indicating excellent performance. A rise in R-CO content resulted in the degradation of several properties. The production of the denim covered by this study was more cost-effective and environment-friendly than that of conventional denim. This research provides a paradigm for the conversion of waste textiles into value-added and eco-friendly textile products.

Enhancing interpolation and approximation error estimates using a novel Taylor-like formula

In this paper, we present an approach to enhance interpolation and approximation error estimates. Based on a previously derived first-order Taylor-like formula, we demonstrate its applicability in improving the P1-interpolation error estimate. Following the same principles, we have also developed a novel numerical scheme for the heat equation that provides a better error estimate compared to the classical implicit finite differences scheme. Numerical illustrations confirm this behavior.

When Federated Learning Meets Privacy-Preserving Computation

Nowadays, with the development of artificial intelligence (AI), privacy issues attract wide attention from society and individuals. It is desirable to make the data available but invisible, i.e., to realize data analysis and calculation without disclosing the data to unauthorized entities. Federated learning (FL) has emerged as a promising privacy-preserving computation method for AI. However, new privacy issues have arisen in FL-based application because various inference attacks can still infer relevant information about the raw data from local models or gradients. This will directly lead to the privacy disclosure. Therefore, it is critical to resist these attacks to achieve complete privacy-preserving computation. In light of the overwhelming variety and a multitude of privacy-preserving computation protocols, we survey these protocols from a series of perspectives to supply better comprehension for researchers and scholars. Concretely, the classification of attacks is discussed including four kinds of inference attacks as well as malicious server and poisoning attack. Besides, this paper systematically captures the state of the art of privacy-preserving computation protocols by analyzing the design rationale, reproducing the experiment of classic schemes, and evaluating all discussed protocols in terms of efficiency and security properties. Finally, this survey identifies a number of interesting future directions.