ALBERT

Description: The electricity output from microbial fuel cell (MFC) with a microalgae assisted cathode is usually higher than that with an air cathode. The output of electricity from a photosynthetic microalgae MFC was positively correlated with the dissolved oxygen (DO) level in the microalgae assisted biocathode. However, DO is highly affected by the photosynthesis of microalgae, leading to the low stability in the electricity output that easily varies with the change in microalgae growth. In this study, to improve the electricity output stability of the MFC, a partially submerged carbon cloth cathode electrode was first investigated to use oxygen from both microalgae and air, with synthetic piggery wastewater used as the anolyte and anaerobically digested swine wastewater as the catholyte. When the DO levels dropped from 13.6–14.8 to 1.0–1.6 mg/L, the working voltages in the MFCs with partially submerged electrodes remained high (256–239 mV), whereas that for the conventional completely submerged electrodes dropped from 259 to 102 mV. The working voltages (average, 297 ± 26 mV) of the MFCs with the 50% submerged electrodes were significantly (p 〈 0.05) higher than with other partially or completely submerged electrodes. The associated maximum lipid production from wastewater was 250 ± 42 mg/L with lipid content of 41 ± 6% dry biomass. Although the partially submerged electrode had no significant effects on lipid production or nitrogen removal in wastewater, there was significant improvement in the stability of the electricity generated under variable conditions.

Description: With the convening of the annual global climate conference, the issue of global climate change has gradually become the focus of attention of the international community. As the largest carbon emitter in the world, China is facing a serious situation of carbon emission reduction. This paper uses the IPCC (The Intergovernmental Panel on Climate Change) method to calculate the carbon emissions of energy consumption in China from 1996 to 2016, and uses it as a dependent variable to analyze the influencing factors. In this paper, five factors, total population, per capita GDP (Gross Domestic Product), urbanization level, primary energy consumption structure, technology level, and industrial structure are selected as the influencing factors of carbon emissions. Based on the expanded STIRPAT (Stochastic Impacts by Regression on Population, Affluence, and Technology) model, the influencing degree of different factors on carbon emissions of energy consumption is analyzed. The results show that the order of impact on carbon emissions from high to low is total population, per capita GDP, technology level, industrial structure, primary energy consumption structure, and urbanization level. On the basis of the above research, the carbon emissions of China′s energy consumption in the future are predicted under eight different scenarios. The results show that, when the population and economy keep a low growth rate, while improving the technology level can effectively control carbon emissions from energy consumption, China′s carbon emissions from energy consumption will reach 302.82 million tons in 2020.

Description: To solve the self-alignment problem of the Strapdown Inertial Navigation System (SINS), a novel adaptive filter based on Complementary Ensemble Empirical Mode Decomposition (CEEMD) is proposed. The Gravitational Apparent Motion (GAM) is used in the coarse alignment, and the problem of obtaining the attitude matrix between the body frame and the navigation frame is attributed to obtaining the matrix between the initial body frame and the current navigation frame using two gravitational apparent motion vectors at different moments. However, the accuracy and time of this alignment method always suffer from the measurement noise of sensors. Thus, a novel adaptive filter based on CEEMD using an l 2 -norm to calculate the similarity measure between the Probability Density Function (PDF) of each Intrinsic Mode Function (IMF) and the original signal is proposed to denoise the measurements of the accelerometer. Furthermore, the advantage of this filter is verified by comparing with other conventional denoising methods, such as PDF-based EMD (EMD-PDF) and the Finite Impulse Response (FIR) digital low-pass filter method. The results of the simulation and experiments indicate that the proposed method performs better than the conventional methods in both alignment time and alignment accuracy.

Description: Model-free reinforcement learning is a powerful and efficient machine-learning paradigm which has been generally used in the robotic control domain. In the reinforcement learning setting, the value function method learns policies by maximizing the state-action value (Q value), but it suffers from inaccurate Q estimation and results in poor performance in a stochastic environment. To mitigate this issue, we present an approach based on the actor-critic framework, and in the critic branch we modify the manner of estimating Q-value by introducing the advantage function, such as dueling network, which can estimate the action-advantage value. The action-advantage value is independent of state and environment noise, we use it as a fine-tuning factor to the estimated Q value. We refer to this approach as the actor-dueling-critic (ADC) network since the frame is inspired by the dueling network. Furthermore, we redesign the dueling network part in the critic branch to make it adapt to the continuous action space. The method was tested on gym classic control environments and an obstacle avoidance environment, and we design a noise environment to test the training stability. The results indicate the ADC approach is more stable and converges faster than the DDPG method in noise environments.

Description: High strength steel has attracted a lot of attention due to its excellent advantage of weight reduction. A thin Al-Si coating covered on the surface of hot-press-forming (HPF) steel offers functions of antioxidation and decarburization under high temperature processing conditions. In this study, the microstructure characteristic, phase, microhardness, and tensile strength of laser welded Al-Si coated HPF steel joints were investigated at different laser powers. Experimental results show that the welding process becomes unstable because of metallic vapor generated by ablation of the coating. Some of the white bright rippled Fe-Al phase was observed to be distributed in the fusion zone randomly. It is found that microhardness, tensile strength, and cupping test qualification rate decreases with the increase of the laser power. For the 1.1 kW laser power, the sound weld performs the best mechanical properties: Microhardness of 466.53 HV and tensile strength of 1349.9 MPa.

Description: Energy transition is an important factor when dealing with climate change and energy crisis under resource constraints. The performance evaluation of it is significant for improving and promoting the process of energy transition. This paper explores the application of the support vector machine improved by the artificial bee colony algorithm (IABC-SVM) method in the energy transition performance evaluation process. It provides an intelligent evaluation tool for the evaluation of the regional energy transition performance. Firstly, the evaluation indicator system of energy transition is constructed from five dimensions: energy supply, demand, efficiency, institution, and environment. Then, the technique for order preference by a similar to ideal solution improved by a combination weighting (CW-TOPSIS) method and IABC-SVM are constructed. After that, according to the evaluation values of 30 provinces in China calculated by CW-TOPSIS, 10-fold cross validation is used to compare the errors of support vector machine (SVM), support vector machine optimized by the artificial bee colony algorithm (ABC-SVM), and IABC-SVM, which proves the effectiveness and accuracy of IABC-SVM in evaluating the performance of energy transition. Finally, the IABC-SVM is used to evaluate the energy transition performance of 30 provinces in 2016. Through a comparative analysis, the relevant suggestions of energy transition are put forward.

Description: The production and use of organochlorine pesticides (OCPs) for agricultural and industrial applications result in high levels of their residues, posing a significant risk to environmental and human health. At present, there are many techniques for OCP-contaminated soil remediation. However, the remediation of contaminated sites may suffer from a series of problems, such as a long recovery cycle, high costs, and secondary pollution, all of which could affect land redevelopment and reuse. Therefore, the selection of an appropriate technology is crucial for contaminated sites. In order to improve and support decision-making for the selection of remediation techniques, we provide a decision-making strategy for the screening of remediation techniques of OCP-contaminated sites. The screening procedure is proposed based on combining the analytic hierarchy process (AHP) and the technique for order preference by similarity to ideal solution (TOPSIS). The screening indexes include economic indicator, environmental indicator, and technical indicator. The assessment results show that co-processing in cement kiln obtained the highest overall score and was thus considered to be the most sustainable option. This suggested remediation technology was similar to the practical remediation project, indicating that the screening method could be applied for the selection of remediation technologies for sites contaminated with persistent organic pollutants.

Description: The main target of the energy revolution in the new period is coal, but the proportion of coal in primary energy consumption will gradually decrease. As coal is a major producer and consumer of energy, analyzing the trend of coal demand in the future is of great significance for formulating the policy of coal development planning and driving the revolution of energy sources in China. In order to predict coal demand scientifically and accurately, firstly, the index system of influencing factors of coal demand was constructed, and the grey relational analysis method was used to select key indicators as input variables of the model. Then, the kernel function of SVM (support vector machine) was optimized by taking advantage of the fast convergence speed of GSA (gravitational search algorithm), and the memory function and boundary mutation strategy of PSO (particle swarm optimization) were introduced to improve the gravitational search algorithm, and the improved GSA (IGSA)–SVM prediction model was obtained. After that, the effectiveness of IGSA–SVM in predicting coal demand was further proven through empirical and comparative analysis. Finally, IGSA–SVM was used to forecast China’s coal demand in 2018–2025. According to the forecasting results, relevant suggestions about coal supply, consumption, and transformation are put forward, providing scientific basis for formulating an energy development strategy.

Description: The Luojia 1-01 Satellite (LJ1-01) is the first professional night-light remote-sensing satellite in China, and thus, it is of pioneering significance for the development of night-light remote sensing satellites in China and the application of remote sensing in the social and economic fields. To ensure the application of night-light remote-sensing data, several studies concerning on-orbit geometric calibration and accuracy verification have been carried out for the complementary metal oxide semiconductor (CMOS) rolling shutter camera of LJ1-01 since the launch of the satellite. Owing to the lack of high-precision nightlight geometric reference at home and abroad, it is difficult to directly calibrate the nighttime light image of LJ1-01. Based on the principle of rolling shutter dynamic imaging, a rigorous geometric imaging model of the time-sharing exposure of the rolling shutter of LJ1-01 is established, and a geometric calibration method for daytime imaging calibration and compensated nighttime light data is proposed. The global public Landsat digital orthophoto image (DOM) with a 15-m resolution and 90-m Shuttle Radar Topography Mission digital elevation model (SRTM-DEM) are used as control data. The images obtained in England, Venezuela, Caracas, Damascus, and Torreon (Mexico) were selected as experimental data. The on-orbit calibration and accuracy verification of LJ1-01 were carried out. Experiments show that after on-orbit geometric calibration, the daytime calibration parameters can effectively compensate for the systematic errors of night-light images. After compensation, the positioning accuracy of night-light images without geometric control points (GCPs) is improved from nearly 20 km to less than 0.65 km. The internal accuracy of the calibrated night-light images is better than 0.3 pixels, which satisfies the requirement of subsequent applications.

Description: A novel multistage attitude determination alignment algorithm with different velocity models is proposed to implement the alignment process of in-motion attitude determination alignment (IMADA) aided by the ground velocity expressed in body frame ( V b ) in this paper. Normally, The V b -based IMADA is used to achieve the coarse alignment for strapdown inertial navigation system (SINS). The higher the coarse alignment accuracy, the better initial condition can be achieved to guarantee the performance of the subsequent fine alignment. Consider the influence of the principal model errors and the calculation errors on the alignment accuracy in traditional V b -based IMADA, this paper deals with a novel alignment algorithm by integrating two different velocity-based IMADAs and the multiple repeated alignment processes. The power of this novel alignment algorithm lies in eliminating the principal model errors and decreasing the calculation errors. Then, the higher alignment accuracy is achieved. Simulations and vehicle experiment are performed to demonstrate the validity of the proposed algorithm.