General Properties of Low-frequency Power Losses in Fe-based Nanocrystalline Soft Magnetic Alloys

The dependences of the power loss per cycle on frequency f and amplitude flux density Bm have been investigated for the three main original magnetic states in five sorts of Fe-based nanocrystalline soft magnetic alloys in the ranges of 10 Hz<=f<=1000 Hz and 0.4 T<= Bm <=1.0 T. The total loss P is decomposed into the sum of the hysteresis loss Physt, the classical eddy current loss Pel and the excess loss Pexc. Physt has been found to be proportional to Bm^2 and f. The behavior of Pexc/f vs f being equivalent to P/f vs f clearly exhibits nonlinearity in the range not more than about 120 Hz, whereas the behavior of P/f vs f roughly shows linearity in the range far above 100 Hz and not more than 1000 Hz. In the range up to 1000 Hz, Physt is dominant in the original high permeability state and the state of low residual flux density, whereas Pexc in the state of high residual flux density is dominant in the wider range above about 100 Hz. The framework of the statistical theory of power loss has been used for representing the behavior of Pexc/f vs f. It has been found that the number n of the simultaneously active 'Magnetic Objects' linearly varies as n = n0 + Hexc/H0 as a function of the dynamic field Hexc in the range below about 120 Hz, whereas n approximately follows a law of the form n = n0 + (Hexc/H0)^m with 1 < m < 2 in the range far above 100 Hz and not more than 1000 Hz. The values of the field HO in principle related to the microstructure and the domain structure have been calculated for the three states.

Low-frequency data analysis and expansion

The use of low-frequency seismic data improves the seismic resolution, and the imaging and inversion quality. Furthermore, low-frequency data are applied in hydrocarbon exploration; thus, we need to better use low-frequency data. In seismic wavelets, the loss of low-frequency data decreases the main lobe amplitude and increases the first side lobe amplitude and results in the periodic shocking attenuation of the secondary side lobe. The loss of low frequencies likely produces pseudo-events and the false appearance of higher resolution. We use models to examine the removal of low-frequency data in seismic data processing. The results suggest that the removal of low frequencies create distortions, especially for steep structures and thin layers. We also perform low-frequency expansion using compressed sensing and sparse constraints and develop the corresponding module. Finally, we apply the proposed method to real common image point gathers with good results.

Mixed-Weights Least-Squares Stable Predictive Control Algorithm with Soft and Hard Constraints

Mixed-weight least-squares (MWLS) predictive control algorithm, compared with quadratic programming (QP) method, has the advantages of reducing the computer burden, quick calculation speed and dealing with the case in which the optimization is infeasible. But it can only deal with soft constraints. In order to deal with hard constraints and guarantee feasibility, an improved algorithm is proposed by recalculating the setpoint according to the hard constraints before calculating the manipulated variable and MWLS algorithm is used to satisfy the requirement of soft constraints for the system with the input constraints and output constraints. The algorithm can not only guarantee stability of the system and zero steady state error, but also satisfy the hard constraints of input and output variables. The simulation results show the improved algorithm is feasible and effective.

Modeling and Adaptive Neural Network Control for a Soft Robotic Arm With Prescribed Motion Constraints

This paper presents a dynamic model and performance constraint control of a line-driven soft robotic arm.The dynamics model of the soft robotic arm is established by combining the screw theory and the Cosserat theory.The unmodeled dynamics of the system are considered,and an adaptive neural network controller is designed using the backstepping method and radial basis function neural network.The stability of the closed-loop system and the boundedness of the tracking error are verified using Lyapunov theory.The simulation results show that our approach is a good solution to the motion constraint problem of the line-driven soft robotic arm.

Feasibility analysis and online adjustment of constraints in model predictive control integrated with soft sensor

Feasibility analysis of soft constraints for input and output variables is critical for model predictive control(MPC).When encountering the infeasible situation, some way should be found to adjust the constraints to guarantee that the optimal control law exists. For MPC integrated with soft sensor, considering the soft constraints for critical variables additionally makes it more complicated and difficult for feasibility analysis and constraint adjustment. Therefore, the main contributions are that a linear programming approach is proposed for feasibility analysis, and the corresponding constraint adjustment method and procedure are given as well. The feasibility analysis gives considerations to the manipulated, secondary and critical variables, and the increment of manipulated variables as well. The feasibility analysis and the constraint adjustment are conducted in the entire control process and guarantee the existence of optimal control. In final, a simulation case confirms the contributions in this paper.

Impact of product heterogeneity and soft budget constraint on excess capacity in Chinese energy industry based on the duopoly model

Chinese energy industries are facing serious problems such as excess capacity,homogeneous product,and soft budget constraint.This paper provides a duopoly model to investigate the influence of heterogeneity and soft budget constraint on production capacity decision and internal action mechanism,respectively,under Cournot and Bertrand competitions,which reveals the formation mechanism of excess capacity.We conclude that excess capacity would exist when the products are not wholly heterogeneous under Cournot competition,and the higher level of the soft budget constraint or the more homogeneous the products are,the worse the excess capacity will be.The insufficient capacity would exist provided that products are not wholly heterogeneous under Bertrand competition,and the higher level of soft budget constraint or the more homogeneous the products are,the more insufficient capacity will be.Both soft budget constraint and product heterogeneity mutually affect to decision-making of capacity and output.

Reflections on the Microeconomic Basis for Soft Budget Constraint in the Market Economy

Historical analysis of the market economy indicates that soft budget constraint is becoming increasingly pervasive and broad-rooted. Using an analysis of micro-level entities in the market economy, this paper describes how soft constraint derives from interdependence among corporations, banks, and the government. Soft constraint is explained in relation to changes in concentrated shareholding ownership, the increasing dominance of the financial sector, and financial insurance. We conclude： 1） concentrated shareholding ownership and institutionalized soft budget constraint create sub-optimal allocation of resources in the market economy; 2） neoclassical microeconomic principles cannot explain the economic actions of organizations in the market economy and should be revised; 3） externalities associated with soft budget constraint have spread across the globe to become both the cause and primary effect of cyclic global financial and economic crises. Hence, the government, banks, and the corporate sector must work together to overhaul supervisory mechanisms. On a global level, governments must collaborate to build a new international economic order. Correcting imbalances in international reserve currencies and fortifying administration of cross-national economic organizations will mitigate the effects of soft budget constraint.

Generalized linear joint PP-PS inversion based on two constraints

Conventional joint PP-PS inversion is based on approximations of the Zoeppritz equations and assumes constant VP/VS;therefore,the inversion precision and stability cannot satisfy current exploration requirements.We propose a joint PP-PS inversion method based on the exact Zoeppritz equations that combines Bayesian statistics and generalized linear inversion.A forward model based on the exact Zoeppritz equations is built to minimize the error of the approximations in the large-angle data,the prior distribution of the model parameters is added as a regularization item to decrease the ill-posed nature of the inversion,low-frequency constraints are introduced to stabilize the low-frequency data and improve robustness,and a fast algorithm is used to solve the objective function while minimizing the computational load.The proposed method has superior antinoising properties and well reproduces real data.

Constraints Adjustment and Objectives Coordination of Satisfying Optimal Control Applied to Heavy Oil Fractionators

In this paper, the feasibility and objectives coordination of real-time optimization (RTO) are systemically investigated under soft constraints. The reason for requiring soft constraints adjustment and objective relaxation simultaneously is that the result is not satisfactory when the feasible region is apart from the desired working point or the optimization problem is infeasible. The mixed logic method is introduced to describe the priority of the constraints and objectives, thereby the soft constraints adjustment and objectives coordination are solved together in RTO. A case study on the Shell heavy oil fractionators benchmark problem illustrating the method is finally presented.

Huber inversion-based reverse-time migration with de-primary imaging condition and curvelet-domain sparse constraint

Least-squares reverse-time migration(LSRTM) formulates reverse-time migration(RTM) in the leastsquares inversion framework to obtain the optimal reflectivity image. It can generate images with more accurate amplitudes, higher resolution, and fewer artifacts than RTM. However, three problems still exist:(1) inversion can be dominated by strong events in the residual;(2) low-wavenumber artifacts in the gradient affect convergence speed and imaging results;(3) high-wavenumber noise is also amplified as iteration increases. To solve these three problems, we have improved LSRTM: firstly, we use Hubernorm as the objective function to emphasize the weak reflectors during the inversion;secondly, we adapt the de-primary imaging condition to remove the low-wavenumber artifacts above strong reflectors as well as the false high-wavenumber reflectors in the gradient;thirdly, we apply the L1-norm sparse constraint in the curvelet-domain as the regularization term to suppress the high-wavenumber migration noise. As the new inversion objective function contains the non-smooth L1-norm, we use a modified iterative soft thresholding(IST) method to update along the Polak-Ribie re conjugate-gradient direction by using a preconditioned non-linear conjugate-gradient(PNCG) method. The numerical examples,especially the Sigsbee2 A model, demonstrate that the Huber inversion-based RTM can generate highquality images by mitigating migration artifacts and improving the contribution of weak reflection events.

瑞利波作用下考虑竖向荷载影响的单桩在饱和软土中的水平动力分析

桩在竖向荷载和瑞利波共同作用下产生水平振动,竖向荷载会因二阶效应导致水平位移增大。为研究桩在饱和软土地基中的水平动力响应,建立瑞利波作用下单桩动力响应的计算模型。基于Biot理论计算均匀自由场中饱和软土地基的水平动力响应。利用边界条件求得土体阻力封闭解。基于Timoshenko梁理论建立桩基动力微分方程,得到桩的水平位移、弯矩和转角的解析解。通过数值算例验证模型正确性,分析竖向荷载、无量纲频率对桩水平振动的影响。研究发现竖向荷载和桩长对水平振动影响较大。

考虑湿度应力的深部软岩隧道大变形控制研究

为探明深部高地应力软岩隧道大变形产生机理,制定适应大变形控制措施,以月直山隧道为工程依托,首先明确求解围岩形变压力与松动压力的Kastner与Caquot公式,基于岩体弹塑性力学与连续介质理论建立围岩湿度应力解析解,采用收敛-约束法绘制出3种围岩应力作用下围岩与初期支护特征曲线,分析断面变形过程中围岩与支护结构相互作用规律及3种应力占比演化规律。分别以混凝土与型钢钢架作为二衬支护结构对月直山隧道围岩稳定性进行计算分析,明确考虑湿度应力与松动压力条件下隧道二衬最优支护时机与支护参数,以支护结构安全系数FS评判出最优支护方案并对隧道软岩大变形进行治理。结果表明:当围岩径向位移达到550 mm时,仅考虑形变压力Pi时围岩对支护结构的压力P仅为0.813 MPa,考虑湿度应力Pw与松动压力Pa时P增大为1.372 MPa,湿度应力与松动应力总占比达40.7%,仅考虑形变压力而设计的支护结构不满足围岩稳定性要求;根据“卸压支护”理念,确定以“位移释放峰值upeak=0.325 m”与“间距d=0.7 m”作为增设第二层钢架的最佳支护时机与支护参数,现场二次钢架设置24天后使围岩变形收敛于50.8 mm,围岩大变形得到控制,研究成果可为今后相关隧道工程设计与施工提供参考。

DBO理论下的档案资政服务机制研究

认清档案资政服务的构成要素及其相互作用机理对提升档案资政服务能力具有重要意义。文章以驱动档案资政服务的社会机制为研究对象,以揭示档案资政服务发生机制为研究目标,运用DBO理论的机制解释模型,基于档案机构和公共决策机构的动机及其互动机会的分析框架,建构了档案资政服务的履职型交往机制、发展型交流机制和价值共创型交融机制三类具体机制。通过对重大活动和突发事件档案工作案例的过程追踪,验证和分析三类档案资政服务机制的运行及特点,以期实现机制的进一步优化和健全。

考虑动态时间锚点和典型特征约束的年日均负荷曲线预测

基于负荷趋势性、周期性和受日历特征影响的特点,考虑动态时间锚点和典型特征约束,实现年日均负荷曲线精确预测。首先,根据历史和预测年的日历关联关系建立动态时间锚点矩阵,结合标幺化和周期平滑处理后的历史年日均负荷形状因子曲线,提出DTA-Soft-DBA方法以获得预测年的日均负荷形状因子预测曲线;然后,进行反标幺化和反周期平滑处理,并结合电力电量特征预测值进行典型特征约束修正,获得年日均负荷预测曲线。基于某地区的算例结果表明,所提方法具有更高的预测精度,其结果与典型特征预测值相吻合,符合年内时序变化规律,能有效整合具有不同日历特征的历史样本时序共性规律。

预算软约束对地区经济增长的影响及其门槛效应研究

在内外需求日益疲软以及地方债务规模较大的情况下,我国推出了一系列积极的财政措施,这要求政府增加举债规模。本研究从全国范围和东、中、西部地区出发,使用基准回归模型和门槛效应模型对地方政府预算软约束对经济增长的影响进行了实证检验。研究发现,地方政府财政预算软约束显著阻碍了地区经济增长,且二者之间存在显著的门槛效应。异质性分析表明,地方政府预算软约束对经济增长的负向作用会受到区域差异的影响。因此,地方政府应采取优化转移支付制度、促进融资平台的市场化转型、完善过度负债约束机制、转变官员政绩考核理念、因地制宜地制定差异性防范政策等措施稳定地区经济增长。

考虑配电网灵活性的分布鲁棒优化调度

针对新能源占比不断增加导致的配电网线路过载和灵活性不足问题,提出一种考虑配电网灵活性的分布鲁棒优化调度方法。首先,考虑节点灵活性资源的功率支撑作用、网络灵活性资源智能软开关的系统潮流优化,提高配电网灵活运行能力;其次,考虑供需平衡和功率传输能力提出了灵活性裕度和线路容量裕度灵活性评价指标;然后,以灵活性裕度、线路容量裕度最优和运行成本最小为目标,构建基于数据驱动的两阶段分布鲁棒优化模型,通过列与约束生成算法对模型求解。最后,通过算例仿真验证了所提模型对提升配电网经济灵活运行的有效性。

基于PINNs算法的一维潜水流方程的渗流参数反演

在地下水领域中,渗流参数反演有助于了解地下水流动的性质,帮助确定地下水资源的分布、移动和质量,这对于地下水资源管理、水文模型开发和地下水补给的可持续性非常重要.近年来,神经网络方法快速发展,然而其针对潜水流渗流参数反演的研究较少.基于此,首次将物理信息神经网络(Physics-Informed Neural Networks,PINNs)方法结合软硬约束设置来解决潜水含水层渗透系数反演问题,以一维稳态非均质潜水流以及非稳态均质潜水流(含溶质运移)的渗透系数反演为例,对比了不同问题中PINNs软约束方法(PINNs-S)和硬约束方法(PINNs-H)反演渗透系数的表现.PINNs算例结果表明,PINNs算法反演渗透系数具有较高的计算精度.此外,PINNs硬约束算法和软约束算法各有优劣,在实际应用中应根据具体问题和实验效果来合理选择.

银行系金融科技公司对商业银行的作用机制——基于技术创新预算软约束视角的实证检验

技术创新普遍存在预算软约束问题。与商业银行内部研发部门相比,银行系金融科技公司对研发项目具有较强的决策权和事后止损机制,并通过市场优胜劣汰机制检验技术创新水平,进而影响商业银行生产经营,但银行系金融科技公司对商业银行的实际影响效果还有待探究。为此,基于我国54家商业银行共10期的平衡面板数据,通过广义最小二乘法随机效应模型、双向固定效应模型以及两阶段模型检验银行系金融科技公司的成立对商业银行投入产出效率的影响,并使用双重差分法进行稳健性检验。结果发现:银行系金融科技公司是硬化技术创新预算约束的直接手段,显著提高了商业银行自主研发能力和经营效率,是推动数字化转型的长期最优选择;现阶段我国银行系金融科技公司主要通过提高技术创新效率、硬化技术创新预算约束的途径影响商业银行经营效率。因此,应鼓励并规范银行系金融科技公司的发展,适时引入金融科技子公司牌照管理,促进商业银行技术创新效率提高。

“利益独享”还是“软预算约束”——基于关联性风险资本联合投资的研究视角

本文基于关联性风险资本联合投资的研究视角,结合软预算约束研究模型,以我国上市公司为研究样本,实证研究关联性风险资本对上市企业IPO抑价的影响。研究发现,关联性风险资本参与上市企业,其IPO抑价显著低于非关联性风险资本参与的上市企业;通过一个投资轮次而形成的关联性风险资本,其IPO抑价显著低于非关联性风险资本,后期参与发行企业的关联性风险资本,其IPO抑价也显著低于非关联性风险资本;参与同一上市企业的全部风险资本之间存在关联关系的关联性风险资本,与非关联性风险资本相比,其IPO抑价水平并不显著,这一类型的关联性风险资本能够软化预算约束,可以缓解差项目被清算的压力,进而影响关联性风险资本识别项目能力。

深埋隧洞软岩变形控制和应力拱圈形成分析

就深埋隧洞在高地应力软岩环境应力拱圈的形成、应力拱圈的强度和围压作用,以及围岩变形控制机理进行论述。分析超前地质预报、减少围岩扰动、数学模拟及监测、主动让压支护、围岩约束平稳过渡对变形控制及应力拱圈形成的作用,以及分析主动让压支护成功案例,阐明控制围岩应力释放的同时又及时提供围压的主动让压支护体系和使围岩约束平稳过渡的措施可以推动应力拱圈形成,能承担高地应力环境下的压应力。