Implementation of a separate fluid-neutral energy equation in SOLPS-ITER and its impact on the validity range of advanced fluid-neutral models

In plasma edge transport codes for nuclear fusion devices, fluid-neutral models offer an interesting alternative to the currently used kinetic Monte Carlo simulations, especially for cases of high ion-neutral collisionality. In this paper, we elaborate a separate neutral energy equation in the state-of-the-art SOLPS-ITER code suite, which previously assumed perfect ion-neutral temperature equilibration. Furthermore, we study the coupled plasma-neutral solutions for a range of divertor operating regimes, proving the validity of these fluid-neutral models for high-recycling and detached regimes.     

Geometry Optimization of Thermoelectric Modules: Deviation of Optimum Power Output and Conversion Efficiency

Besides the material research in the field of thermoelectrics, the way from a material to a functional thermoelectric (TE) module comes alongside additional challenges. Thus, comprehension and optimization of the properties and the design of a TE module are important tasks. In this work, different geometry optimization strategies to reach maximum power output or maximum conversion efficiency are applied and the resulting performances of various modules and respective materials are analyzed. A Bi₂Te₃-based module, a half-Heusler-based module, and an oxide-based module are characterized via FEM simulations. By this, a deviation of optimum power output and optimum conversion efficiency in dependence of the diversity of thermoelectric materials is found. Additionally, for all modules, the respective fluxes of entropy and charge as well as the corresponding fluxes of thermal and electrical energy within the thermolegs are shown. The full understanding and enhancement of the performance of a TE module may be further improved.     

Hydrodynamic and Thermodynamic Nonequilibrium Effects around Shock Waves: Based on a Discrete Boltzmann Method

A shock wave that is characterized by sharp physical gradients always draws the medium out of equilibrium. In this work, both hydrodynamic and thermodynamic nonequilibrium effects around the shock wave are investigated using a discrete Boltzmann model. Via Chapman–Enskog analysis, the local equilibrium and nonequilibrium velocity distribution functions in one-, two-, and three-dimensional velocity space are recovered across the shock wave. Besides, the absolute and relative deviation degrees are defined in order to describe the departure of the fluid system from the equilibrium state. The local and global nonequilibrium effects, nonorganized energy, and nonorganized energy flux are also investigated. Moreover, the impacts of the relaxation frequency, Mach number, thermal conductivity, viscosity, and the specific heat ratio on the nonequilibrium behaviours around shock waves are studied. This work is helpful for a deeper understanding of the fine structures of shock wave and nonequilibrium statistical mechanics.     

The Influence of Signal Polarization on Quantum Bit Error Rate for Subcarrier Wave Quantum Key Distribution Protocol

In this paper, we consider the influence of a divergence of polarization of a quantum signal transmitted through an optical fiber channel on the quantum bit error rate of the subcarrier wave quantum key distribution protocol. Firstly, we investigate the dependence of the optical power of the signal on the modulation indices’ difference after the second phase modulation of the signal. Then we consider the Liouville equation with regard to relaxation in order to develop expressions of the dynamics of the Stokes parameters. As a result, we propose a model that describes quantum bit error rate for the subcarrier wave quantum key distribution depending on the characteristics of the optical fiber. Finally, we propose several methods for minimizing quantum bit error rate.     

Dark energy versus modified gravity: Impacts on measuring neutrino mass

In this paper,we make a comparison for the impacts of smooth dynamical dark energy,modified gravity,and interacting dark energy on the cosmological constraints on the total mass of active neutrinos.For definiteness,we consider theΛCDM model,the w CDM model,the f(R)model,and two typical interacting vacuum energy models,i.e.,the IΛCDM1 model with Q=βHρc and the IΛCDM2 model with Q=βHρΛ.In the cosmological fits,we use the Planck 2015 temperature and polarization data,in combination with other low-redshift observations including the baryon acoustic oscillations,the type Ia supernovae,the Hubble constant measurement,and the large-scale structure observations,such as the weak lensing as well as the redshift-space distortions.Besides,the Planck lensing measurement is also employed in this work.We find that,the w CDM model favors a higher upper limit on the neutrino mass compared to theΛCDM model,while the upper limit in the f(R)model is similar with that in theΛCDM model.For the interacting vacuum energy models,the IΛCDM1 model favors a higher upper limit on neutrino mass,while the IΛCDM2 model favors an identical neutrino mass with the case ofΛCDM.     

Machine-Learned Free Energy Surfaces for Capillary Condensation and Evaporation in Mesopores

Using molecular simulations, we study the processes of capillary condensation and capillary evaporation in model mesopores. To determine the phase transition pathway, as well as the corresponding free energy profile, we carry out enhanced sampling molecular simulations using entropy as a reaction coordinate to map the onset of order during the condensation process and of disorder during the evaporation process. The structural analysis shows the role played by intermediate states, characterized by the onset of capillary liquid bridges and bubbles. We also analyze the dependence of the free energy barrier on the pore width. Furthermore, we propose a method to build a machine learning model for the prediction of the free energy surfaces underlying capillary phase transition processes in mesopores.     

The Effect of the Protein Synthesis Entropy Reduction on the Cell Size Regulation and Division Size of Unicellular Organisms

The underlying mechanism determining the size of a particular cell is one of the fundamental unknowns in cell biology. Here, using a new approach that could be used for most of unicellular species, we show that the protein synthesis and cell size are interconnected biophysically and that protein synthesis may be the chief mechanism in establishing size limitations of unicellular organisms. This result is obtained based on the free energy balance equation of protein synthesis and the second law of thermodynamics. Our calculations show that protein synthesis involves a considerable amount of entropy reduction due to polymerization of amino acids depending on the cytoplasmic volume of the cell. The amount of entropy reduction will increase with cell growth and eventually makes the free energy variations of the protein synthesis positive (that is, forbidden thermodynamically). Within the limits of the second law of thermodynamics we propose a framework to estimate the optimal cell size at division.     

面向变厚度柔性轧制工艺的帽型梁横向冲击吸能优化设计

作为汽车主要吸能构件的帽型梁的吸能提升设计是备受关注的问题.研究表明,通过优化薄壁结构的厚度可有效提升吸能性能,但复杂的厚度分布造成制造困难.针对可实现厚度调控的工艺,发展易制造的结构设计方法极为必要.本文基于变厚度柔性轧制工艺(variable gauge rolling, VGR)可实现厚度调控的特点,发展建立帽型梁横向冲击吸能优化设计方法.基于变厚度柔性轧制工艺生产的柔性轧制板(tailor rolled blanks, TRB)的特点,将受横向冲击的帽型薄壁梁设计成沿轴线分段变厚度、分段间设梯度过渡段的结构形式,通过调整各段厚度、分段位置和过渡层梯度变化规律,实现性能的优化.以应变能密度分布均匀为优化准则、基于混合元胞自动机(hybird cellular automata, HCA)方法构建优化模型和求解方法,并在迭代过程中施加满足轧制约束的过滤函数,使结构满足轧制工艺要求.其中,轧制约束的过滤函数由粒子群算法自动寻找.基于本文方法,具体设计了柔性轧制帽型梁横向冲击吸能最优的分段位置、各段厚度及过渡段厚度的梯度过渡方式,设计结果验证了方法的有效性.      

大脑血液动力学现象中的能量编码

神经信息的编码与解码是神经科学中的核心研究内容,同时又极具挑战性.传统的编码理论都具有各自的局限性,很难从脑的全局运行方式上给出有效的理论.而由于能量是一个标量具有可叠加性,因此能量编码理论可以从神经元活动的能量特征出发来研究脑功能的全局神经编码问题,取得了一系列的研究成果.本研究以王-张神经元能量计算模型为基础,构建了一个多层次结构的神经网络,通过计算机数值模拟得到了神经网络的能量消耗和血液中葡萄糖供能的变化情况.计算结果显示,和网络的神经活动达到峰值的时间相比,血液中葡萄糖的供能达到峰值的时间延迟了约5.6s.从定量的角度再现了功能性核磁共振(fMRI)中的血液动力学现象:大脑某个脑区的神经元集群被激活以后经过5~7 s的延迟,脑血流的变化才会大幅增加.模拟结果表明先前发表的由王-张神经元模型所揭示的负能量机制在控制大脑的血液动力学现象中起着核心的作用,预测了刺激条件下大脑的能量代谢与血流之间变化的本质是由神经元在发放动作电位过程中正、负能量之间的非平衡、不匹配性质所决定的.本文的研究结果为今后进一步探究血液动力学现象的生理学机制提供了新的研究方向,在神经网络的建模与计算方面给出了一个新的视角和研究方法.      

A STUDY OF LOW CYCLE FATIGUE PROPERTIES OF MATERIALS BASED ON THE FUNNEL-SHEET SPECIMENS1)

根据能量等效方法,针对漏斗薄片试样,提出了关联Ramberg-Osgood 幂律参数、试样几何参数的载荷-位移半解析统一模型。采用有限元数值模拟,正、反向验证了该模型的有效性。在此基础上,提出了通过漏斗薄片试样低循环试验实现材料低周疲劳性能的预测方法。基于薄片试样低循环试验数据,完成了SS316L, N18及SAPH440 三种材料的低周疲劳性能预测,预测结果与标准试样试验结果具有良好的一致性。并利用该方法完成了N18与SAPH在不同温度条件下的低周疲劳性能预测。