Enhanced picosecond terahertz wave generation based on cascade effects in a terahertz parametric generator

Enhanced terahertz wave generation via a Stokes cascade process has been demonstrated using picosecond pulse pumped terahertz parametric generation at 1 kHz repetition rate.Clear cascade saturation of terahertz output was observed,and the corresponding cascade-Stokes spectra were analyzed.The maximum terahertz wave average power was 22μW under a pump power of 30 W,whereas the maximum power conversion efficiency was 8×10^(-7)under a pump power of 21 W.The THz power fluctuation was measured to be about 1%in 20 min.This THz parametric source with a relatively stable output is suitable for a variety of practical applications.

Parametric instability in the pure-quartic nonlinear Schrödinger equation

We study the nonlinear stage of modulation instability(MI)in the non-intergrable pure-quartic nonlinear Schrödinger equation where the fourth-order dispersion is modulated periodically.Using the three-mode truncation,we reveal the complex recurrence of parametric resonance(PR)breathers,where each recurrence is associated with two oscillation periods(PR period and internal oscillation period).The nonlinear stage of parametric instability admits the maximum energy exchange between the spectrum sidebands and central mode occurring outside the MI gain band.

Parametric resonance of axially functionally graded pipes conveying pulsating fluid

Based on the generalized Hamilton's principle,the nonlinear governing equation of an axially functionally graded(AFG)pipe is established.The non-trivial equilibrium configuration is superposed by the modal functions of a simply supported beam.Via the direct multi-scale method,the response and stability boundary to the pulsating fluid velocity are solved analytically and verified by the differential quadrature element method(DQEM).The influence of Young's modulus gradient on the parametric resonance is investigated in the subcritical and supercritical regions.In general,the pipe in the supercritical region is more sensitive to the pulsating excitation.The nonlinearity changes from hard to soft,and the non-trivial equilibrium configuration introduces more frequency components to the vibration.Besides,the increasing Young's modulus gradient improves the critical pulsating flow velocity of the parametric resonance,and further enhances the stability of the system.In addition,when the temperature increases along the axial direction,reducing the gradient parameter can enhance the response asymmetry.This work further complements the theoretical analysis of pipes conveying pulsating fluid.

Harmonic balance simulation of the influence of component uniformity and reliability on the performance of a Josephson traveling wave parametric amplifier

A Josephson traveling wave parametric amplifier(JTWPA),which is a quantum-limited amplifier with high gain and large bandwidth,is the core device of large-scale measurement and control systems for quantum computing.A typical JTWPA consists of thousands of Josephson junctions connected in series to form a transmission line and hundreds of shunt LC resonators periodically loaded along the line for phase matching.Because the variation of these capacitors and inductors can be detrimental to their high-frequency characteristics,the fabrication of a JTWPA typically necessitates precise processing equipment.To guide the fabrication process and further improve the design for manufacturability,it is necessary to understand how each electronic component affects the amplifier.In this paper,we use the harmonic balance method to conduct a comprehensive study on the impact of nonuniformity and fabrication yield of the electronic components on the performance of a JTWPA.The results provide insightful and scientific guidance for device design and fabrication processes.

Modularized and Parametric Modeling Technology for Finite Element Simulations of Underground Engineering under Complicated Geological Conditions

The surrounding geological conditions and supporting structures of underground engineering are often updated during construction,and these updates require repeated numerical modeling.To improve the numerical modeling efficiency of underground engineering,a modularized and parametric modeling cloud server is developed by using Python codes.The basic framework of the cloud server is as follows:input the modeling parameters into the web platform,implement Rhino software and FLAC3D software to model and run simulations in the cloud server,and return the simulation results to the web platform.The modeling program can automatically generate instructions that can run the modeling process in Rhino based on the input modeling parameters.The main modules of the modeling program include modeling the 3D geological structures,the underground engineering structures,and the supporting structures as well as meshing the geometric models.In particular,various cross-sections of underground caverns are crafted as parametricmodules in themodeling program.Themodularized and parametric modeling program is used for a finite element simulation of the underground powerhouse of the Shuangjiangkou Hydropower Station.This complicatedmodel is rapidly generated for the simulation,and the simulation results are reasonable.Thus,this modularized and parametric modeling program is applicable for three-dimensional finite element simulations and analyses.

Meta-Auto-Decoder:a Meta-Learning-Based Reduced Order Model for Solving Parametric Partial Differential Equations

Many important problems in science and engineering require solving the so-called parametric partial differential equations(PDEs),i.e.,PDEs with different physical parameters,boundary conditions,shapes of computational domains,etc.Typical reduced order modeling techniques accelerate the solution of the parametric PDEs by projecting them onto a linear trial manifold constructed in the ofline stage.These methods often need a predefined mesh as well as a series of precomputed solution snapshots,and may struggle to balance between the efficiency and accuracy due to the limitation of the linear ansatz.Utilizing the nonlinear representation of neural networks(NNs),we propose the Meta-Auto-Decoder(MAD)to construct a nonlinear trial manifold,whose best possible performance is measured theoretically by the decoder width.Based on the meta-learning concept,the trial manifold can be learned in a mesh-free and unsupervised way during the pre-training stage.Fast adaptation to new(possibly heterogeneous)PDE parameters is enabled by searching on this trial manifold,and optionally fine-tuning the trial manifold at the same time.Extensive numerical experiments show that the MAD method exhibits a faster convergence speed without losing the accuracy than other deep learning-based methods.

Research on Urban Building Parametric Modelling Method Based on CityEngine

With the advancement of technology and the development of cities,urban planning and management methods are also constantly improving.From paper-based assignments to modern digitization,new technologies have enabled more efficient design and management for cities.3D modeling can used to simulate the urban environment,which can assist in urban planning and management.However,large-scale modeling cannot be achieved through existing modeling methods,and there are still some shortcomings in the maintenance of the model.Therefore,this article proposes a Computer Generated Architecture(CGA)parametric 3D modeling method based on CityEngine.Research on expanding and customizing modeling rules to create indoor and outdoor modeling rule templates for buildings and methods for generating urban 3D models have been carried out.The results have shown that the completed model can be displayed on different platforms thanks to parameterized modeling.The model can be modified easily and directly applied to the analysis and decision-making of urban planning schemes.

Comparison of Type I Error Rates of Siegel-Tukey and Savage Tests among Non-Parametric Tests

This study aimed to examine the performance of the Siegel-Tukey and Savage tests on data sets with heterogeneous variances. The analysis, considering Normal, Platykurtic, and Skewed distributions and a standard deviation ratio of 1, was conducted for both small and large sample sizes. For small sample sizes, two main categories were established: equal and different sample sizes. Analyses were performed using Monte Carlo simulations with 20,000 repetitions for each scenario, and the simulations were evaluated using SAS software. For small sample sizes, the I. type error rate of the Siegel-Tukey test generally ranged from 0.045 to 0.055, while the I. type error rate of the Savage test was observed to range from 0.016 to 0.041. Similar trends were observed for Platykurtic and Skewed distributions. In scenarios with different sample sizes, the Savage test generally exhibited lower I. type error rates. For large sample sizes, two main categories were established: equal and different sample sizes. For large sample sizes, the I. type error rate of the Siegel-Tukey test ranged from 0.047 to 0.052, while the I. type error rate of the Savage test ranged from 0.043 to 0.051. In cases of equal sample sizes, both tests generally had lower error rates, with the Savage test providing more consistent results for large sample sizes. In conclusion, it was determined that the Savage test provides lower I. type error rates for small sample sizes and that both tests have similar error rates for large sample sizes. These findings suggest that the Savage test could be a more reliable option when analyzing variance differences.

Table-top optical parametric chirped pulse amplifiers: past and present

The generation of power-and wavelength-scalable few optical cycle pulses remains one of the major challenges in modern laser physics.Over the past decade,the development of table-top optical parametric chirped pulse amplificationbased systems was progressing at amazing speed,demonstrating excellent performance characteristics in terms of pulse duration,energy,peak power and repetition rate,which place them at the front line of modern ultrafast laser technology.At present,table-top optical parametric chirped pulse amplifiers comprise a unique class of ultrafast light sources,which currently amplify octave-spanning spectra and produce carrier-envelope phase-stable,few optical cycle pulses with multi-gigawatt to multi-terawatt peak powers and multi-watt average powers,with carrier wavelengths spanning a considerable range of the optical spectrum.This article gives an overview on the state of the art of table-top optical parametric chirped pulse amplifiers,addressing their relevant scientific and technological aspects,and provides a short outlook of practical applications in the growing field of ultrafast science.

Nonlinear optical imaging by detection with optical parametric amplification(invited paper)

Nonlinear optical imaging is a versatile tool that has been proven to be exceptionally useful in various research fields.However,due to the use of photomultiplier tubes(PMTs),the wide application of nonlinear optical imaging is limited by the incapability of imaging under am-bient light.In this paper,we propose and demonstrate a new optical imaging detection method based on optical parametric amplification(OPA).As a nonlinear optical process,OPA in-trinsically rejects ambient light photons by coherence gating.Periodical poled lithium niobate(PPLN)crystals are used in this study as the media for OPA.Compared to bulk nonlinear optical crystals,PPLN crystals support the generation of OPA signal with lower pump power.Therefore,this characteristic of PPLN crystals is particularly beneficial when using high-repetition-rate lasers,which facilitate high-speed optical signal detection,such as in spec-troscopy and imaging.A PPLN-based OPA system was built to amplify the emitted imaging signal from second harmonic generation(SHG)and coherent anti-Stokes Raman scattering(CARS)microscopy imaging,and the amplified optical signal was strong enough to be detected by a biased photodiode under ordinary room light conditions.With OPA detection,ambient-light-on SHG and CARS imaging becomes possible,and achieves a similar result as PMT detection under strictly dark environments.These results demonstrate that OPA can be used as a substitute for PMTs in nonlinear optical imaging to adapt it to various applications with complex.light ing conditions.

Coordinate-Parametric Matrix Model Inspired Square-Conjoint Pattern in Cross Woven for Conventional Bamboo Mat

In the study,it is proposed that a coordinate-parametric matrix model is performed to a square-conjoint pattern of cross woven(SCPCW)in the bamboo mat.The patterns of SCPCW are firstly detected according to the perspective of configuration,which is divided into the basic-monomer shape and the basic combination shape.Secondly,the compositions of design patterns in SCPCW are analyzed to attain the trend of curve shape.Based on the coordinate-parametric matrix model,the specimens of SCPCW are subsequently accomplished to elaborate the woven logic of bamboo mats.The digital innovation of SCPCW,defined by a mathematical resolution,is implemented by the software of Grasshopper(GH),which plays a crucial role in capturing image information by the Image Sampler component.Successively,the weaving logic of coordinated matrix is referred to apply in the computing component of Grasshopper software.Finally,the computer simulation could demonstrate that the coordinate-parametric matrix model of SCPCWwould be realized to analyze the micro-weaving structure and overall weaving effect in the bamboo mat.

A Comprehensive Guide for Selecting Appropriate Statistical Tests: Understanding When to Use Parametric and Nonparametric Tests

Choosing appropriate statistical tests is crucial but deciding which tests to use can be challenging. Different tests suit different types of data and research questions, so it is important to choose the right one. Knowing how to select an appropriate test can lead to more accurate results. Invalid results and misleading conclusions may be drawn from a study if an incorrect statistical test is used. Therefore, to avoid these it is essential to understand the nature of the data, the research question, and the assumptions of the tests before selecting one. This is because there are a wide variety of tests available. This paper provides a step-by-step approach to selecting the right statistical test for any study, with an explanation of when it is appropriate to use it and relevant examples of each statistical test. Furthermore, this guide provides a comprehensive overview of the assumptions of each test and what to do if these assumptions are violated.

A Comprehensive Guide for Selecting Appropriate Statistical Tests: Understanding When to Use Parametric and Nonparametric Tests

Choosing appropriate statistical tests is crucial but deciding which tests to use can be challenging. Different tests suit different types of data and research questions, so it is important to choose the right one. Knowing how to select an appropriate test can lead to more accurate results. Invalid results and misleading conclusions may be drawn from a study if an incorrect statistical test is used. Therefore, to avoid these it is essential to understand the nature of the data, the research question, and the assumptions of the tests before selecting one. This is because there are a wide variety of tests available. This paper provides a step-by-step approach to selecting the right statistical test for any study, with an explanation of when it is appropriate to use it and relevant examples of each statistical test. Furthermore, this guide provides a comprehensive overview of the assumptions of each test and what to do if these assumptions are violated.

Multiple parametric Marcinkiewicz integrals with mixed homogeneity along surfaces

In this paper, the multiple parametric Marcinkiewicz integral operators with mixed homogeneity along surfaces are studied. The Lp-mapping properties for such operators are obtained under the rather weakened size conditions on the integral kernels both on the unit sphere and in the radial direction. The main results essentially improve and extend certain previous results.

High power,widely tunable femtosecond MgO:PPLN optical parametric oscillator

We demonstrate a high power,widely tunable femtosecond MgO-doped periodically poled lithium niobate(MgO:PPLN)optical parametric oscillator(OPO)at 151 MHz,pumped by a Kerr-lens mode-locked Yb:KGW laser.With a maximum pump power of 7 W,the OPO is capable of delivering as high as 2.2 W of the signal centered around 1500 nm with tunable signal spectrum ranges of 1377 nm-1730 nm at an extraction efficiency of 31.4%,which exhibits a long-term passive power stability better than 0.71%rms over 4 h.The maximum idler bandwidths of 185 nm at 3613 nm are obtained across the idler tuning ranges of 2539 nm-4191 nm.By compensating intracavity dispersion,the signal has the shortest pulse duration of 170 fs at 1428 nm.

Mixed-Effects Parametric Proportional Hazard Model with Generalized Log-Logistic Baseline Distribution

Clustered survival data are widely observed in a variety of setting. Most survival models incorporate clustering and grouping of data accounting for between-cluster variability that creates correlation in order to prevent underestimate of the standard errors of the parameter estimators but do not include random effects. In this study, we developed a mixed-effect parametric proportional hazard (MEPPH) model with a generalized log-logistic distribution baseline. The parameters of the model were estimated by the application of the maximum likelihood estimation technique with an iterative optimization procedure (quasi-Newton Raphson). The developed MEPPH model’s performance was evaluated using Monte Carlo simulation. The Leukemia dataset with right-censored data was used to demonstrate the model’s applicability. The results revealed that all covariates, except age in PH models, were significant in all considered distributions. Age and Townsend score were significant when the GLL distribution was used in MEPPH, while sex, age and Townsend score were significant in MEPPH model when other distributions were used. Based on information criteria values, the Generalized Log-Logistic Mixed-Effects Parametric Proportional Hazard model (GLL-MEPPH) outperformed other models.

Flow-Induced Clogging in Microfiltration Membranes: Numerical Modeling and Parametric Study

Microfiltration membrane technology has been widely used in various industries for solid-liquid separation. However, pore clogging remains a persistent challenge. This study employs (CFD) and discrete element method (DEM) models to enhance our understanding of microfiltration membrane clogging. The models were validated by comparing them to experimental data, demonstrating reasonable consistency. Subsequently, a parametric study was conducted on a cross-flow model, exploring the influence of key parameters on clogging. Findings show that clogging is a complex phenomenon affected by various factors. The mean inlet velocity and transmembrane flux were found to directly impact clogging, while the confinement ratio and cosine of the membrane pore entrance angle had an inverse relationship with it. Two clog types were identified: internal (inside the pore) and external (arching at the pore entrance), with the confinement ratio determining the type. This study introduced a dimensionless number as a quantitative clogging indicator based on transmembrane flux, Reynolds number, filtration time, entrance angle cosine, and confinement ratio. While this hypothesis held true in simulations, future studies should explore variations in clogging indicators, and improved modeling of clogging characteristics. Calibration between numerical and physical times and consideration of particle volume fraction will enhance understanding.

Building Daylight Simulation Analysis Based on Ladybug+Honeybee Parametric Approach:A Case Study of Gando Primary School

The Gando Primary School project faces several challenges like extreme environmental constraints,resource scarcity,and design requirements.These challenges include the hot climate of Burkina Faso,economic underdevelopment,building material scarcity,and lack of electrical resources.To implement an architectural design for the classrooms that accommodates these difficulties,especially in the absence of an electrical system,architect Francis Kéréemployed various passive design strategies that can provide shelter from the rain and heat while achieving essential lighting levels and ventilation.This paper used Gando Primary School as the research object and utilized the parametric tools of Ladybug+Honeybee(L+H)to conduct numerical simulations and evaluations of the building’s daylighting,glare analysis,and indoor thermal comfort.The aim of this study is to investigate the application of passive design strategies in energy conservation under extreme environmental conditions,propose a parametric energy-saving evaluation strategy with L+H,and explore energy-saving design ideas in economically underdeveloped Third World countries.

基于径向基网络的堰塞体溃决峰值流量预测研究

堰塞体由天然滑坡堆积而成,受上游来流冲刷和渗透极易发生溃决,给下游人们生命财产造成严重威胁。快速、准确地预测溃决峰值流量是堰塞体抢险工作的重中之重。现有研究基于数据库—统计回归—溃决模型的思想,提出了一系列堰塞体溃决峰值流量预测模型,但均未综合考虑堰塞体冲蚀特性和颗粒组成对溃决流量的影响,且随着数据的不断扩充,预测模型难以取得预期效果。因此,本研究基于国内外2060例堰塞体溃决信息数据库,通过考虑堰塞体几何特征、冲蚀特性和颗粒组成,提炼出堰塞体高度(H_(d))、堰塞体宽度(W_(d))、堰塞体体积(V_(d))、水库库容(V_(l))、溃口深度(H_(w))、溃口平均宽度(W_(b))、堰塞体中值粒径(d_(50))7个影响参数,并将堰塞体冲蚀程度分为5类,构建了考虑冲蚀特性的堰塞体溃决峰值流量预测模型。选取数据齐全的120座堰塞体溃决案例对模型进行验证,均方根误差(RMSE)和相关系数(R2)分别为9581 m^(3)/s与0.965,并和国内外已有典型参数模型进行比较。结果表明,考虑堰塞体冲蚀特性和d50参数的模型可以更好地预测溃决峰值流量,能够为堰塞体溃决抢险进程中的溃决洪水演进、下游受灾区域划分等工作内容提供合理参考。

S135钻杆接头螺纹三维参数化建模及力学特性分析

S135钢级钻杆在矿井勘探、探放水、瓦斯抽采等钻孔施工中得到了广泛使用。然而,由于钻杆接头螺纹承受轴向拉压、扭转、弯曲及其复合载荷的循环作用,导致接头螺纹的使用寿命远远低于其设计寿命,是整个钻杆结构中最薄弱的环节。因此,通过万能拉伸试验获得钻杆接头材料的力学性能参数,经计算转化得到其本构参数,对钻杆接头进行有限元分析。为了提高有限元分析效率,推导垂直于钻杆接头轴线的螺纹截面轮廓几何表达式,基于旋转、抬升、缩径和连接节点的设计思路,提出了一种考虑钻杆接头锥度和台肩的三维螺纹参数化建模方法,并根据单元和节点之间的关系开发了钻杆接头连接的参数化三维六面体网格建模程序,通过与交互式建模方法计算结果的对比验证了其有效性和可行性。此外,对上扣扭矩、压扭及压弯扭复合载荷作用下接头外螺纹的力学特性进行了分析。结果表明:3种工况下钻杆接头外螺纹上的应力近似呈现“浴盆”形态,第1螺纹牙上的应力最大;随着圈次的增加,螺纹牙上的应力迅速下降,最后一圈螺纹牙上的应力呈现上升趋势;在弯矩的作用下,螺纹牙上的应力具有非对称特征。在接头螺纹设计时,必须考虑井眼曲率的影响并且需要重点关注接头压缩边第1螺纹牙上的应力。