ALBERT

Description: Although many types of simulated radionuclides have been widely used as a substitute for actual nuclear waste in the studies of nuclear waste solidification, the understanding of the applicability and validity of simulated radionuclides is still insufficient. In particular, the selection and use of simulated radionuclides, which can play a decisive role in the accuracy of the experimental results, still lack unified or integrated references. This paper provides a critical review on the selection, experimental methods, and applicability of the most commonly studied simulated radionuclides, followed by a careful discussion and recommendation of simulated radionuclides suitable for different solidified bodies. The main factors (e.g., temperature, pH, and atmosphere) affecting the choice of simulated radionuclides were analyzed in detail. This work helps to integrate the selection and use of simulated radionuclides, and it will be beneficial for improving the effectiveness of nuclide solidification research.

Description: Wireless sensor networks are always deployed in remote and hostile environments to gather sensitive information, in which sensor nodes are apt to encounter some serious leakage of sensitive data. Hence, privacy-preserving is becoming an increasingly important issue in security data aggregation for wireless sensor networks. In this paper, we propose a balance privacy-preserving data aggregation model (BPDA) based on slicing and mixing technology. Compared to fixed or random slicing, BPDA model gives a balance slicing mechanism to ensure that slice can be sent to the nodes which have lower privacy preservation and enhance the privacy-preserving efficacy. Furthermore, according to the influence of the node degree and energy, three different schemes are presented to keep the privacy-preserving data aggregation balance. Theoretical analysis and simulation show that BPDA model demonstrates a good performance in terms of privacy-preserving efficacy and communication overhead and prolongs the lifetime of network.

Description: Cellular automata (CA) are simple models of computation which exhibit fascinatingly complex behavior. Due to the universality of CA model, it has been widely applied in traditional cryptography and image processing. The aim of this paper is to present a new image encryption scheme based on balanced two-dimensional cellular automata. In this scheme, a random image with the same size of the plain image to be encrypted is first generated by a pseudo-random number generator with a seed. Then, the random image is evoluted alternately with two balanced two-dimensional CA rules. At last, the cipher image is obtained by operating bitwise XOR on the final evolution image and the plain image. This proposed scheme possesses some advantages such as very large key space, high randomness, complex cryptographic structure, and pretty fast encryption/decryption speed. Simulation results obtained from some classical images at the USC-SIPI database demonstrate the strong performance of the proposed image encryption scheme.

Description: It is not easy to find marine cracks of structures by directly manual testing. When the cracks of important components are extended under extreme offshore environment, the whole structure would lose efficacy, endanger the staff’s safety, and course a significant economic loss and marine environment pollution. Thus, early discovery of structure cracks is very important. In this paper, a beam structure damage identification model based on intelligent algorithm is firstly proposed to identify partial cracks in supported beams on ocean platform. In order to obtain the replacement mode and strain mode of the beams, the paper takes simple supported beam with single crack and double cracks as an example. The results show that the difference curves of strain mode change drastically only on the injured part and different degrees of injury would result in different mutation degrees of difference curve more or less. While the model based on support vector machine (SVM) and BP neural network can identify cracks of supported beam intelligently, the methods can discern injured degrees of sound condition, single crack, and double cracks. Furthermore, the two methods are compared. The results show that the two methods presented in the paper have a preferable identification precision and adaptation. And damage identification based on support vector machine (SVM) has smaller error results.

Description: In the electric power steering (EPS) system, low-frequency disturbances such as road resistance, irregular mechanical friction, and changing motor parameters can cause steering wheel torque fluctuation and discontinuity. In order to improve the steering wheel torque smoothness, an improved torque control method of an EPS motor is proposed in the paper. A target torque algorithm is established, which is related to steering process parameters such as steering wheel angle and angular speed. Then, a target torque closed-loop control strategy based on the improved ADRC is designed to estimate and compensate the internal and external disturbance of the system, so as to reduce the impact of the disturbance on the steering torque. The simulation results show that the responsiveness and anti-interference ability of the improved ADRC is better than that of the conventional ADRC and PI. The vehicle experiment shows that the proposed control method has good motor current stability, steering torque smoothness, and flexibility when there is low-frequency disturbance.

Description: With the development of economy, the requirement of financial planning for individuals or families is emerging. In the era of the Internet, individual investors can conveniently enter the market and purchase financial products. Traditional portfolio management models focus on risky markets such as stock markets. However, risk-averse investors, such as normal families, may concern appropriate long-term financial planning. This paper considers the problem of portfolio management of bank financial products with a long-term planning horizon. By taking into account the final return and the flexibility, a multiobjective model of long-term portfolio is proposed. A multiobjective evolutionary approach is employed for the handling of conflicting objectives. Test instances are generated to illustrate the problem. Experiment results show that the presented algorithm can efficiently find trade-off solutions. Our experimental results also show that crossover probabilities should be separately implemented for long-term portfolio problems with hybrid encoding. Performance comparison of different crossover operators suggest that, for a real-valued encoding part, the simulated binary crossover (SBX) has a better performance than BLX- operator. While for a binary encoding part, a uniform crossover operator might be appropriate for large-scale instances. The proposed multiobjective model in this paper provides risk-averse investors with an appropriate decision support model for the long-term financial planning and management.

Description: The intermittence and fluctuation character of solar irradiance places severe limitations on most of its applications. The precise forecast of solar irradiance is the critical factor in predicting the output power of a photovoltaic power generation system. In the present study, Model I-A and Model II-B based on traditional long short-term memory (LSTM) are discussed, and the effects of different parameters are investigated; meanwhile, Model II-AC, Model II-AD, Model II-BC, and Model II-BD based on a novel LSTM-MLP structure with two-branch input are proposed for hour-ahead solar irradiance prediction. Different lagging time parameters and different main input and auxiliary input parameters have been discussed and analyzed. The proposed method is verified on real data over 5 years. The experimental results demonstrate that Model II-BD shows the best performance because it considers the weather information of the next moment, the root mean square error (RMSE) is 62.1618 W/m2, the normalized root mean square error (nRMSE) is 32.2702%, and the forecast skill (FS) is 0.4477. The proposed algorithm is 19.19% more accurate than the backpropagation neural network (BPNN) in terms of RMSE.

Description: Different from the existing equivalent circuit analysis method of the transducer, based on the vibration theory of the mechanical system and combined with the constitutive equation, this paper analyzes the radial vibration characteristics of the transducer. The piezoelectric ceramic composite ultrasonic transducer is simplified as a mechanical model of a composite thick wall tube composed of a piezoelectric ceramic tube and a metal prestressed tube. The mathematical model of radial vibration of the transducer is established, which consists of the wave equation of radial coupling vibration of the piezoelectric ceramic tube and the metal prestressed tube, the continuity conditions, and the boundary conditions of radial vibration of composite thick wall tube. The characteristic equation and the mode function of radial vibration are derived. The calculated results of natural frequency are in good agreement with the existing experimental results. Based on the analytical method and the difference method, the numerical simulation models of radial vibration are established, and the amplitude-frequency characteristic curves and the displacement responses are given. The simulation results show that the amplitude-frequency characteristic curves and the displacement responses of the two methods are the same, which verifies the correctness of simulation results. Through the simulation analysis, the influence rule of the transducer’s structure sizes on its radial vibration natural frequency is given: when the thickness of the metal prestressed tube and the piezoelectric ceramic tube are constant, the natural frequency decreases with the increase of the inner diameter of the piezoelectric ceramic tube; when the outer diameter of the metal prestressed tube and the inner diameter of the piezoelectric ceramic tube are constant, the natural frequency decreases with the increase of the thickness-to-wall ratio. The calculation method of natural frequency based on elastic vibration theory is clear in concept and simple in calculation, and the simulation models can analyze the mechanical vibration of the transducer.

Description: A grain-based rock model was developed and applied to study mechanical characteristics and failure micromechanics in thick-walled cylinder and wellbore stability tests. The rock is represented as an assembly of tetrahedral blocks with bonded contacts. Material heterogeneity is modeled by varying the tensile strength at the block contacts. This grain-based rock model differs from previous disk/sphere particle-based rock models in its ability to represent a zero (or very low) initial porosity condition, as well as highly interlocked irregular block shapes that provide resistance to movement even after contact breakage. As a result, this model can reach higher uniaxial compressive strength to tensile strength ratios and larger friction coefficients than the disk/sphere particle-based rock model. The model captured the rock fragmentation process near the wellbore due to buckling and spalling. Thin fragments of rock similar to onion skins were produced, as observed in laboratory breakout experiments. The results suggest that this approach may be well suited to study the rock disaggregation process and other geomechanical problems in the rock excavation.