Temperature adaptability of the soluble lead flow battery using different solutions of fluoborate,perchlorate, methanesulfonate and trifluoromethanesulfonate

The evaluation of cell's weatherability is of practical interest. To further improve the soluble lead flow battery's weatherability, physiochemical properties of electrolytes containing fluoborate, perchlorate, methanesulfonate and trifluoromethanesulfonate are investigated from ?60 to 50 °C. Activities of CF₃SO₃H and HClO₄ are poor in trifluoromethanesulfonate and perchlorate solutions due to common anion effect. The solubility of lead salt can be improved by increasing temperature, but worsened by increasing acid's content. With the temperature increasing, the conductivity is enhanced, and the viscosity is lowered for four solutions. The same results have been found by increasing acid's content except for CF₃SO₃H. The high energy efficiency can be achieved for cells over ?40–0 °C using fluoborate and perchlorate solutions, 73.2% at ?40 °C and 78.1% at ?30 °C respectively. Over the temperature range of 20–50 °C, the cells with methanesulfonate and trifluoromethanesulfonate solutions have good performance, 77.4% and 73.7% at 50 °C respectively.     

田赛距离测量中全站仪的设计与实现

本文提出了将智能全站仪这种精密测量仪器广泛应用于田赛项目测量中，并结合其他科技元素用于解决田赛项目中跳远、投掷等项目的测量及数据管理问题，实现实时、自动、准确地裁定和报告比赛成绩。     

Assessment of the different sources of uncertainty in a SWAT model of the River Senne (Belgium)

Although rainfall input uncertainties are widely identified as being a key factor in hydrological models, the rainfall uncertainty is typically not included in the parameter identification and model output uncertainty analysis of complex distributed models such as SWAT and in maritime climate zones. This paper presents a methodology to assess the uncertainty of semi-distributed hydrological models by including, in addition to a list of model parameters, additional unknown factors in the calibration algorithm to account for the rainfall uncertainty (using multiplication factors for each separately identified rainfall event) and for the heteroscedastic nature of the errors of the stream flow. We used the Differential Evolution Adaptive Metropolis algorithm (DREAM_(zs)) to infer the parameter posterior distributions and the output uncertainties of a SWAT model of the River Senne (Belgium). Explicitly considering heteroscedasticity and rainfall uncertainty leads to more realistic parameter values, better representation of water balance components and prediction uncertainty intervals.     

Fully coupled LES-DEM of particle interaction and agglomeration in a turbulent channel flow

Coupled large eddy simulation and the discrete element method are applied to study turbulent particle–laden flows, including particle dispersion and agglomeration, in a channel. The particle–particle interaction model is based on the Hertz–Mindlin approach with Johnson–Kendall–Roberts cohesion to allow the simulation of van der Waals forces in a dry air flow. The influence of different particle surface energies, and the impact of fluid turbulence, on agglomeration behaviour are investigated. The agglomeration rate is found to be strongly influenced by the particle surface energy, with a positive relationship observed between the two. Particle agglomeration is found to be enhanced in two separate regions within the channel. First, in the near-wall region due to the high particle concentration there driven by turbophoresis, and secondly in the buffer region where the high turbulence intensity enhances particle–particle interactions.     

不同折流板结构螺旋折流板换热器传热性能的比较(英文)

Numerical simulations were performed on flow and heat transfer performances of heat exchangers having six helical baffles of different baffle shapes and assembly configurations, i.e., two trisection baffle schemes, two quadrant baffle schemes, and two continuous helical baffle schemes. The temperature contour or the pressure contour and velocity contour plots with superimposed velocity vectors on meridian, transverse and unfolded concentric hexagonal slices are presented to obtain a full angular view. For the six helix baffled heat exchangers, the different patterns of the single vortex secondary flow and the shortcut leakage flow were depicted as wel as the heat transfer properties were compared. The results show that the optimum scheme among the six configurations is a circumferential overlap trisection helix baffled heat exchanger with a baffle incline angle of 20° (20°TCO) scheme with an anti-shortcut baffle structure, which exhibits the second highest pressure dropΔpo, the highest overal heat transfer coefficient K, shel-side heat transfer coefficient ho and shel-side average comprehensive index ho/Δpo.     

A bi-layer optimization approach for a hybrid flow shop scheduling problem involving controllable processing times in the steelmaking industry

A steelmaking-continuous casting (SCC) scheduling problem is an example of complex hybrid flow shop scheduling problem (HFSSP) with a strong industrial background. This paper investigates the SCC scheduling problem that involves controllable processing times (CPT) with multiple objectives concerning the total waiting time, earliness/tardiness and adjusting cost. The SCC scheduling problem with CPT is seldom discussed in the existing literature. This study is motivated by the practical situation of a large integrated steel company in which the just-in-time (JIT) and cost-cutting production strategy have become a significant concern. To address this complex HFSSP, the scheduling problem is decomposed into two subproblems: a parallel machine scheduling problem (PMSP) in the last stage and an HFSSP in the upstream stages. First, a hybrid differential evolution (HDE) algorithm combined with a variable neighborhood decomposition search (VNDS) is proposed for the former subproblem. Second, an iterative backward list scheduling (IBLS) algorithm is presented to solve the latter subproblem. The effectiveness of this bi-layer optimization approach is verified by computational experiments on well-designed and real-world scheduling instances. This study provides a new perspective on modeling and solving practical SCC scheduling problems.     

靶面激光光斑尺寸原位测量的研究

提供了一种简便易行的靶面激光光斑尺寸原位测量的方法。从高斯光束的横向光强分布特性出发,建立了激光烧蚀斑半径与辐照激光能量、光斑尺寸、烧蚀阈值间的关系式,模拟分析发现辐照激光光斑尺寸对烧蚀斑半径随辐照能量变化曲线有较大影响。对于脉宽为2 ms,波长为1064 nm的激光,实验测量了不同能量激光辐照下相纸烧蚀斑半径,并用推导出的关系式拟合测量数据,获得了靶面处光斑尺寸和样品烧蚀阈值。同时,也测量了不同位置处的光斑尺寸和样品烧蚀阈值,对高斯光束束腰位置和样品烧蚀阈值的光斑尺寸效应进行了验证。研究结果表明该技术结果可靠,简单高效。该技术可以为高能激光与固体物质相互作用的基础研究和激光加工等应用领域中实现简单方便地测量靶面光斑尺寸提供帮助。     

High-resolution ISAR imaging of fast rotating targets based on pattern-coupled Bayesian strategy for multiple measurement vectors

Very high resolution inverse synthetic aperture radar (ISAR) imaging of fast rotating targets is a complicated task. There may be insufficient pulses or may introduce migration through range cells (MTRC) during the coherent processing interval (CPI) when we use the conventional range Doppler (RD) ISAR technique. With compressed sensing (CS) technique, we can achieve the high-resolution ISAR imaging of a target with limited number of pulses. Sparse representation based method can achieve the super resolution ISAR imaging of a target with a short CPI, during which the target rotates only a small angle and the range migration of the scatterers is small. However, traditional CS-based ISAR imaging method generally faced with the problem of basis mismatch, which may degrade the ISAR image. To achieve the high resolution ISAR imaging of fast rotating targets, this paper proposed a pattern-coupled sparse Bayesian learning method for multiple measurement vectors, i.e. the PC-MSBL algorithm. A multi-channel pattern-coupled hierarchical Gaussian prior is proposed to model the pattern dependencies among neighboring range cells and correct the MTRC problem. The expectation-maximization (EM) algorithm is used to infer the maximum a posterior (MAP) estimate of the hyperparameters. Simulation results validate the effectiveness and superiority of the proposed algorithm.     

A three-dimensional surface measurement system implemented with Gaussian process based adaptive sampling

Self-adaptive surface measurements that can reduce data redundancy and improve time efficiency are in high demand in many fields of science and technology. For this purpose, a system implemented with Gaussian process (GP) adaptive sampling is developed. The non-parametric GP model is applied to reconstruct the topography and guide the subsequent sampling position, which is determined from the inference uncertainty estimation. A criterion is proposed to terminate the GP adaptive measurement automatically without any prior model or data of the topography. Experiments on typical surfaces validate the intelligence, adaptability, and high accuracy of the GP method along with the stabilization of the automatic iteration termination. Compared with traditional raster sampling, data redundancy is reduced and the time efficiency is improved without sacrificing the surface reconstruction accuracy. The proposed method can be implemented in other systems with similar measurement principles, thus benefitting surface characterizations.     

A Complexing Agent to Enable a Wide-Temperature Range Bromine-Based Flow Battery for Stationary Energy Storage

Bromine-based flow batteries (Br-FBs) are considered one of the most promising energy storage systems due to their features of high energy density and low cost. However, they generally suffer from uncontrolled diffusion of corrosive bromine particularly at high temperatures. That is because the interaction between polybromide anions and the commonly used complexing agent (N–methyl–N–ethyl–pyrrolidinium bromide [MEP]) decreases with increasing temperatures, which causes serious self-discharge and capacity fade. Herein, a novel bromine complexing agent, 1–ethyl–2–methyl–pyridinium bromide (BCA), is introduced in Br-FBs to solve the above problems. It is proven that BCA can combine with polybromide anions very well even at a high temperature of 60 °C. Moreover, the BCA contributes to decreasing the electrochemical polarization of Br⁻/Br₂ couple, which in turn improves their power density. As a result, a zinc–bromine flow battery with BCA as the complexing agent can achieve a high energy efficiency of 84% at 40 mA cm⁻², even at high temperature of 60 °C and it can stably run for more than 400 cycles without obvious performance decay. This paper provides an effective complexing agent to enable a wide temperature range Br-FB.