Deterministic and probabilistic ship pitch prediction using a multi-predictor integration model based on hybrid data preprocessing,reinforcement learning and improved QRNN

The deterministic and probabilistic prediction of ship motion is important for safe navigation and stable real-time operational control of ships at sea. However, the volatility and randomness of ship motion, the non-adaptive nature of single predictors and the poor coverage of quantile regression pose serious challenges to uncertainty prediction, making research in this field limited. In this paper, a multi-predictor integration model based on hybrid data preprocessing, reinforcement learning and improved quantile regression neural network (QRNN) is proposed to explore the deterministic and probabilistic prediction of ship pitch motion. To validate the performance of the proposed multi-predictor integrated prediction model, an experimental study is conducted with three sets of actual ship longitudinal motions during sea trials in the South China Sea. The experimental results indicate that the root mean square errors (RMSEs) of the proposed model of deterministic prediction are 0.0254°, 0.0359°, and 0.0188°, respectively. Taking series #2 as an example, the prediction interval coverage probabilities (PICPs) of the proposed model of probability predictions at 90%, 95%, and 99% confidence levels (CLs) are 0.9400, 0.9800, and 1.0000, respectively. This study signifies that the proposed model can provide trusted deterministic predictions and can effectively quantify the uncertainty of ship pitch motion, which has the potential to provide practical support for ship early warning systems.     

Thermo-economic investigation on the hydrogen production through the stored solar energy in a salinity gradient solar pond: A comparative study by employing APC and ORC with zeotropic mixture

In this paper, a salinity gradient solar pond (SGSP) is used to harness the solar energy for hydrogen production through two cycles. The first cycle includes an absorption power cycle (APC), a proton exchange membrane (PEM) electrolyzer, and a thermoelectric generator (TEG) unit; in the second one, an organic Rankine cycle (ORC) with the zeotropic mixture is used instead of APC. The cycles are analyzed through the thermoeconomic vantage point to discover the effect of key decision variables on the cycles’ performance. Finally, NSGA-II is used to optimize both cycles. The results indicate that employing ORC with zeotropic mixture leads to a better performance in comparison to utilizing APC. For the base mode, unit cost product (UCP), exergy, and energy efficiency when APC is employed are 59.9 $/GJ, 23.73%, and 3.84%, respectively. These amounts are 47.27 $/GJ, 29.48%, and 5.86% if ORC with the zeotropic mixture is utilized. The APC and ORC generators have the highest exergy destruction rate which is equal to 6.18 and 10.91 kW. In both cycles, the highest investment cost is related to the turbine and is 0.8275 $/h and 0.976 $/h for the first and second cycles, respectively. In the optimum state the energy efficiency, exergy efficiency, UCP, and H₂ production rate of the system enhances 42.44%, 27.54%,15.95%, and 38.24% when ORC with the zeotropic mixture is used. The maximum H₂ production is 0.47 kg/h, and is obtained when the mass fraction of R142b, LCZ temperature, pumps pressure ratio, generator bubble point temperature are 0.603, 364.35 K, 2.12, 337.67 K, respectively.     

Optimal operating conditions to maximize the net power of polymer electrolyte membrane fuel cells: The stack-system interface of a commercial 18 kW module

A new, experimental method based on air flow rate rather than current is presented to optimize operating parameters for the stacks and systems of proton exchange membrane fuel cells (PEMFCs) for maximizing their net power. This approach is illustrated for a commercial 18 kW PEMFC module. The impact of contamination pressure drop across the cathode air filter is also investigated on the compressor behavior. It is further shown that a 4V reduction in the compressor voltage reduces its power consumption by 9.1%. Using the 3D graphs of the power-pressure-flow data, it is found that the stack pressure of 180 kPaa is superior to the higher tested pressures as it enhances the net power by 7.0 and 13.7% at different conditions. Application of the present study will lead to the development of PEMFCs with higher power output by optimizing stack pressure, stoichiometry and air flow to properly deliver the system design specifications.     

Breeding schemes with optimum-contribution selection or truncation selection for beef cattle destined for use on dairy females

We tested the hypothesis that the size of a beef cattle population destined for use on dairy females is smaller under optimum-contribution selection (OCS) than under truncation selection (TRS) at the same genetic gain (ΔG) and the same rate of inbreeding (ΔF). We used stochastic simulation to estimate true ΔG realized at a 0.005 ΔF in breeding schemes with OCS or TRS. The schemes for the beef cattle population also differed in the number of purebred offspring per dam and the total number of purebred offspring per generation. Dams of the next generation were exclusively selected among the one-year-old heifers. All dams were donors for embryo transfer and produced a maximum of 5 or 10 offspring. The total number of purebred offspring per generation was: 400, 800, 1,600 or 4,000 calves, and it was used as a measure of population size. Rate of inbreeding was predicted and controlled using pedigree relationships. Each OCS (TRS) scheme was simulated for 10 discrete generations and replicated 100 (200) times. The OCS scheme and the TRS scheme with a maximum of 10 offspring per dam required approximately 783 and 1,257 purebred offspring per generation to realize a true ΔG of €14 and a ΔF of 0.005 per generation. Schemes with a maximum of 5 offspring per dam required more purebred offspring per generation to realize a similar true ΔG and a similar ΔF. Our results show that OCS and multiple ovulation and embryo transfer act on selection intensity through different mechanisms to achieve fewer selection candidates and fewer selected sires and dams than under TRS at the same ΔG and a fixed ΔF. Therefore, we advocate the use of a breeding scheme with OCS and multiple ovulation and embryo transfer for beef cattle destined for use on dairy females because it is favorable both from an economic perspective and a carbon footprint perspective.     

大豆蛋白纳米纤维对铁纳米颗粒的稳态化作用

为明确大豆蛋白纳米纤维的结构形成和扩宽铁强化剂的食品工业应用，以大豆分离蛋白（soy protein isolate，SPI）为原料，通过5 h的酸热处理制备纳米纤维（soy protein isolate fibrils，Fib SPI），系统研究纤维形成前后蛋白结构的变化，并进一步制备铁纳米颗粒（iron nanoparticles，Fe NPs），探究Fib SPI对铁的稳态化作用。研究结果表明：在酸热处理过程中，SPI产生大量的β-折叠结构，其与硫磺素T结合，显示出增强的荧光强度；此外，7S组分先发生降解，利于纤维成核形成，随后11S逐渐被水解，促进纤维生长；同时水解产生大量的小肽组分，提高了产物的还原力。研究进一步利用Fib SPI递送铁纳米颗粒（Fe NPs），发现与原始SPI相比，铁纳米颗粒可在Fib SPI原位形成胶体稳定的铁-大豆蛋白纳米纤维复合物（Fe FibSPI），并以Fe（II）形式存在，其对乳液体系色泽及稳定性的影响较硫酸亚铁或氯化铁小。该研究可为构建新型植物基铁强化剂递送体系提供理论和方法指导。     

基于VMD和改进TCN的短期光伏发电功率预测

光伏发电功率存在波动性,且光伏出力易受各种气象特征影响,传统TCN网络容易过度强化空间特性而弱化个体特性。针对上述问题,文中提出一种基于VMD和改进TCN的短期光伏发电功率预测模型。通过VMD将原始光伏发电功率时间序列分解为若干不同频率的模态分量,将各个模态分量以及相对应的气象数据输入至改进TCN网络进行建模学习。利用中心频率法确定VMD的最优分解模态分解个数。在传统TCN预测模型的基础上,使用DropBlock正则化取代Dropout正则化以达到抑制卷积层中信息协同的效果,并引入注意力机制自主挖掘并突出关键气象输入特征的影响,量化各气象因素对光伏发电的影响,从而提高预测精度。以江苏省某光伏电站真实数据为例进行仿真实验,结果表明所提预测方法的RMSE为0.62 MW,MAPE为2.03%。     

Efficient utilization of waste heat from molten carbonate fuel cell in parabolic trough power plant for electricity and hydrogen coproduction

Direct steam generating parabolic trough power plant is an important technology to match future electric energy demand. One of the problems related to its emergence is energy storage. Solar-to-hydrogen is a promising technology for solar energy storage. Electrolysis is among the most processes of hydrogen production recently investigated. High temperature steam electrolysis is a clean process to efficiently produce hydrogen. In this paper, steam electrolysis process using solar energy is used to produce hydrogen. A heat recovery steam generator generates high temperature steam thanks to the molten carbonate fuel cell's waste heat. The analytical study investigates the energy efficiency of solar power plant, molten carbonate fuel cell and electrolyser. The impact of waste heat utilization on electricity and hydrogen generation is analysed. The results of calculations done with MATLAB software show that fuel cell produces 7.73 MWth of thermal energy at design conditions. 73.37 tonnes of hydrogen and 14.26 GWh of electricity are yearly produced. The annual energy efficiency of electrolyser is 70% while the annual mean electric efficiency of solar power plant is 18.30%.The proposed configuration based on the yearly electricity production and hydrogen generation has presented a good performance.     

Influence of applied voltage and conductive material in DIET promotion for methane generation

The utilization of biological-, electrode- and conductive material-mediated direct interspecies electron transfer (DIET) between exoelectrogenic bacteria and methanogenic archaea for enhancing methane productivity is widely reported in the literature. However, two cardinal questions are still controversial, i.e., which applied voltage value would be more recommended to enhance methane generation? and how the DIET over IIET has the upper hand in enhancing methane productivity? Herein, the influence of different applied voltages to promote biological-, conductive- and electrode-mediated DIET was investigated in MEC-AD reactors with conductive material. Polarized bioelectrodes induced electrode-mediated DIET (eDIET) and biological DIET (bDIET), in addition to cDIET (conductive material-mediated DIET), improved the methane yield to 315.40 mL/g COD_r with an applied voltage of 0.9 V. Whereas further increase of applied voltage 1.2 V, lessened methane production efficiency due to high-voltage inhibition and adverse effect on DIET promotion. The anaerobic digestion coupled microbial electrolysis cells with optimal electric potential selectively promotes the DIET through polarized electrodes were confirmed through microbial analysis. As the contribution of DIET increased to 80%, the methane yield increased, and the substrate residue decreased, resulting in a significant improvement in methane production.     

高耸桥墩保护性爆破拆除关键技术

为解决高耸钢砼桥墩上部倾斜导致的工程质量不合格问题,采用保护性控制爆破将上部倾斜部分钢砼桥墩予以拆除,同时保留下部未偏斜部分桥墩不受破坏。采用开设组合形状切口,预开定向窗、导向窗;设置组合高差卸荷槽,预伤钢筋弱化抗压抗拉能力为关键措施的控制爆破方案。方案实施取得了十分满意的效果,上部拟拆除部分桥墩顺利倾倒下坠,下部保留部分桥墩完好无损。采用保护性控制爆破技术能高效、安全地解决类似高耸钢砼桥墩(构筑物)部分拆除、部分保留利用的问题,并能取得可观的经济、社会效益。     

Directional separation of hydrogen-containing gas mixture by hydrate-membrane coupling method

Recovery of hydrogen (H₂) from H₂-containing gas mixtures has great significance for energy conservation, cost reduction and benefit increase. However, the common separation methods have the ubiquitous problem due to phase equilibrium principle and results in the conflict between H₂ concentration and H₂ recovery rate in the product gas. Consequently, an innovative conception of hydrate-membrane coupling approach is proposed in this work. In the separation process, hydration and membrane permeation two separation driving forces coexist to achieve the aim of strengthening mass transfer kinetics. H₂ and non-H₂ components (hydrocarbons) are synchronously and directionally selected by membrane and hydrate to improve different phase compositions. Therefore, the gas in feed side could keep relatively high two separation driving forces (H₂ fugacity and hydrocarbons fugacity). The results show that the coupling method could synchronously increase both the concentration and the recovery rate of H₂ in the product gas. At the same time, the volume and concentration of the hydrocarbons in hydrate both increases effectively. It indicates that hydrate and membrane separation methods support each other in the separation process. The hydrate-membrane coupling method fundamentally solves the issue of the decreasing driving force resulting from single separation method and phase equilibrium relationship.