基于双DMD的红外场景投影仪的结构设计及有限元分析

红外场景投影仪能够模拟多种类型的目标与背景,对光电探测系统进行动态测试评估。为提高中波红外场景投影仪帧频速度和灰度等级,提出了一种基于双DMD (数字微反射器件)的设计方案。根据光学系统的特点及中波红外投影仪使用环境,对总体结构进行选型。根据投影仪的使用环境要求,对其进行有限元分析,结论表明力学性能满足指标要求。投影仪的测试结果表明此系统完全满足指标要求。Infrared scene projector can simulate multiple types of targets and backgrounds, which can evaluate dynamic test of photoelectric detection systems. In order to improve the frame rate and the grey level of the midwave (MWIR) scene projector, the design scheme based on dual-DMD (Digital micro-mirror device) is presented. The overall structure is selected according to the characteristic of optical system and operational environment of the midwave (MWIR) scene projector. The finite element analysis of the system is carried out according to operating environment requirements, which results show that the mechanical properties meet the specification. The results of the testing for the projector illustrate that the performances of the optical systems meet the specifications of the infrared scene projector.

基于POD/DMD降阶模型的离心泵蜗壳内非稳态流动分析

为深入研究离心泵蜗壳内非线性耦合流动的本质流动特征,本文以一单级单吸式离心泵蜗壳为研究对象,分别采用本征正交分解和动态模态分解2种降阶模型对蜗壳内非定常流场数据进行模态分析,获取流场主导流动结构,并对原流场进行重构。研究发现:蜗壳内流结构主要由速度正负交错,并且周期性特征与叶频及其倍频相关的成对涡旋组成。本征正交分解和动态模态分解方法均可以捕捉流场主要流动结构,并对原流场进行准确还原,两者重构流场与原流场的均方根误差均在0.4%以内。尽管本征正交分解方法在重构流场时整体均方根误差更小,但无法获取单频率流动结构,而动态模态分解方法可以获得不同频率流动结构对流场的贡献,从而捕捉到复杂流场中的不稳定模态。研究成果可以为增强离心泵全局流动的认知、关键水力部件优化设计及发展主/被动流动控制提供理论参考。

基于随机数据驱动SDMD的电力系统区域惯量评估方法

准确评估系统惯量对于支持未来低惯量电力系统的系统安全运行至关重要。文中提出了一种随机数据驱动下基于机电响应特征的系统惯量评估方法,从随机响应信号中实现了区域有效惯量的评估。首先,通过将随机Koopman理论与随机动态系统相结合,推导出了随机Koopman空间上机电特征与系统惯量的耦合关系。然后,利用子空间动态模式分解(SDMD),以数据驱动的方式提取系统机电响应特征。该算法通过正交投影和奇异值分解,在压缩数据的同时实现了系统状态矩阵的低秩近似,可以有效减弱观测噪声对计算结果的影响。最后,采用IEEE 4机2区系统和IEEE 10机39节点系统的数值模拟算例验证了所提算法的有效性和鲁棒性。

一例DMD基因Alu元件插入突变导致杜氏肌营养不良及其白发症状分析

杜氏肌营养不良(Duchenne muscular dystrophy,DMD)是由DMD基因突变引起的抗肌萎缩蛋白缺乏的一种严重X连锁隐性遗传病,突变形式主要包括外显子缺失和重复、点突变、插入突变等,这些突变通过不同方式影响了抗肌萎缩蛋白的正常表达,最终导致疾病的发生。本研究报告了1例DMD基因第59号外显子(exon 59,E59)插入突变引起的DMD,该患儿相关生化指标明显异常,表现较为明显的DMD早期症状,并出现了多处白发。其母亲和姐姐为携带者,生化指标轻微异常,母亲有轻微临床症状,姐姐无临床症状。其他成员基因和身体状况正常。经测序和序列比对发现,该插入片段为AluYa5亚家族的Alu元件,该片段插入可产生两个终止密码子,末端含一段多聚腺苷酸尾(polyA)。为了解该插入突变对于DMD基因的影响以及与临床症状的关联,通过外显子剪接增强子(exonic splicing enhancer,ESE)预测发现,该插入并不影响E59的剪接,由此推测该插入序列会最终出现在DMD基因的mRNA序列中,插入序列中的2个终止子和polyA很可能会在翻译过程中发挥终止作用,不能产生有功能的抗肌萎缩蛋白,这可能是导致DMD发生的机制。另外该患儿除了典型的DMD症状外,还出现了过早白发症状。本研究首次报道了1例DMD基因编码区插入Alu元件导致的DMD,为研究Alu序列逆转座引发基因突变提供线索,同时扩展了对DMD基因突变的认识。

双吸泵作液力透平叶轮内非定常流动DMD分析

为了精确分析双吸泵作液力透平叶轮内的非定常流动特性,采用SST k-ω湍流模型在设计工况下进行数值模拟。对一个周期的非定常速度场进行动态模态分解(DMD),并结合Q准则,得到前4阶主要模态及其相应的时空信息。分析结果表明:DMD方法将叶轮内复杂的流场特征分解为动静干扰模态、基本模态和耗散模态。其中动静干扰模态占主导地位,频率为叶轮旋转频率,反映出叶轮内流动受静止部件干扰的流动特征,涡结构主要为点状涡和不连续的管状涡;基本模态频率为0Hz,反映出叶片流道几何特征引起的稳态流场特征,涡结构主要为连续的管状涡;3阶及4阶模态为耗散模态,反映出叶轮内流动受静止部件干扰,在叶片上产生的流动分离及不稳定涡结构脱落的特征,以片状涡和不连续的管状涡为主。在特定频率下DMD方法可以对叶轮流场结构进行分解,能够清楚地分析双吸泵作液力透平叶轮内复杂流场的非定常特性。

Enhancing the Interaction of Carbon Nanotubes by Metal-Organic Decomposition with Improved Mechanical Strength and Ultra-Broadband EMI Shielding Performance

The remarkable properties of carbon nanotubes(CNTs)have led to promising applications in the field of electromagnetic inter-ference(EMI)shielding.However,for macroscopic CNT assemblies,such as CNT film,achieving high electrical and mechanical properties remains challenging,which heavily depends on the tube-tube interac-tions of CNTs.Herein,we develop a novel strategy based on metal-organic decomposition(MOD)to fabricate a flexible silver-carbon nanotube(Ag-CNT)film.The Ag particles are introduced in situ into the CNT film through annealing of MOD,leading to enhanced tube-tube interactions.As a result,the electrical conductivity of Ag-CNT film is up to 6.82×10^(5) S m^(-1),and the EMI shielding effectiveness of Ag-CNT film with a thickness of~7.8μm exceeds 66 dB in the ultra-broad frequency range(3-40 GHz).The tensile strength and Young’s modulus of Ag-CNT film increase from 30.09±3.14 to 76.06±6.20 MPa(~253%)and from 1.12±0.33 to 8.90±0.97 GPa(~795%),respectively.Moreover,the Ag-CNT film exhibits excellent near-field shield-ing performance,which can effectively block wireless transmission.This innovative approach provides an effective route to further apply macroscopic CNT assemblies to future portable and wearable electronic devices.

基于CYCBD和参数自适应DMD的滚动轴承微弱故障诊断

在旋转机械故障诊断中,传感器采集到的滚动轴承振动信号容易受到多个激励源的耦合影响,特别是微弱故障特征往往淹没在背景噪声中,给故障诊断带来挑战。为了抑制无关激励源并增强故障特征,本文提出一种基于最大二阶循环平稳盲解卷积(CYCBD)和参数自适应动态模式分解(DMD)的滚动轴承微弱故障诊断方法。首先根据包络谐波乘积谱(EHPS)估计CYCBD算法的关键参数循环频率α,将原始信号经CYCBD处理使故障特征得到增强;然后将CYCBD处理后的信号通过参数自适应DMD进一步消除残余噪声,其中DMD的最优截断秩参数r通过遗传算法自适应确定;最后通过包络谱分析来提取故障特征频率及倍频。仿真和试验结果证明了本方法的有效性。

风力机翼型S809绕流流动特性的POD和DMD对比分析

失速时的流动分离现象对风力机叶片的气动性能有重要影响,S809作为典型水平轴风力机翼型,在临界失速攻角下气动性能会大幅降低。基于流动特征提取的非定常流场降阶模型(reduced-order model,ROM)是进一步深入了解非定常流动的重要手段。本文通过计算流体力学方法得到轻、深失速攻角下翼型的流动特征,对时变速度场进行本征正交分解(proper orthogonal decomposition,POD)和动态模态分解(dynamic mode decomposition,DMD)分析,得到轻、深失速下翼型的非定常流场信息(能量占比、模态频率等)。通过两种方法的对比,结果表明,POD和DMD方法能够准确捕捉流动过程中的非定常结构和升力主频相同的典型模态,但是POD方法由于基于能量特征,在捕捉模态时会忽略与升力主频相近但能量较小的流动结构,而基于频率特征的DMD方法能够准确获得场的演化信息(增长率、频率等)。本文研究有利于针对主频结构发展相应的流动控制方法,从而改善翼型流场情况,提高气动性能。

Formation and transformation of metastable LPSO building blocks clusters in Mg-Gd-Y-Zn-Zr alloys by spinodal decomposition and heterogeneous nucleation

To study the formation and transformation mechanism of long-period stacked ordered(LPSO)structures,a systematic atomic scale analysis was conducted for the structural evolution of long-period stacked ordered(LPSO)structures in the Mg-Gd-Y-Zn-Zr alloy annealed at 300℃~500℃.Various types of metastable LPSO building block clusters were found to exist in alloy structures at different temperatures,which precipitate during the solidification and homogenization process.The stability of Zn/Y clusters is explained by the first principles of density functional theory.The LPSO structure is distinguished by the arrangement of its different Zn/Y enriched LPSO structural units,which comprises local fcc stacking sequences upon a tightly packed plane.The presence of solute atoms causes local lattice distortion,thereby enabling the rearrangement of Mg atoms in the different configurations in the local lattice,and local HCP-FCC transitions occur between Mg and Zn atoms occupying the nearest neighbor positions.This finding indicates that LPSO structures can generate necessary Schockley partial dislocations on specific slip surfaces,providing direct evidence of the transition from 18R to 14H.Growth of the LPSO,devoid of any defects and non-coherent interfaces,was observed separately from other precipitated phases.As a result,the precipitation sequence of LPSO in the solidification stage was as follows:Zn/Ycluster+Mg layers→various metastable LPSO building block clusters→18R/24R LPSO;whereas the precipitation sequence of LPSO during homogenization treatment was observed to be as follows:18R LPSO→various metastable LPSO building block clusters→14H LPSO.Of these,14H LPSO was found to be the most thermodynamically stable structure.

Reactive molecular dynamics insight into the thermal decomposition mechanism of 2,6-Bis(picrylamino)-3,5-dinitropyridine

2,6-bis(picrylamino)-3,5-dinitropyridine(PYX)has excellent thermostability,which makes its thermal decomposition mechanism receive much attention.In this paper,the mechanism of PYX thermal decomposition was investigated thoroughly by the ReaxFF-lg force field combined with DFT-B3LYP(6-311++G)method.The detailed decomposition mechanism,small-molecule product evolution,and cluster evolution of PYX were mainly analyzed.In the initial stage of decomposition,the intramolecular hydrogen transfer reaction and the formation of dimerized clusters are earlier than the denitration reaction.With the progress of the reaction,one side of the bitter amino group is removed from the pyridine ring,and then the pyridine ring is cleaved.The final products produced in the thermal decomposition process are CO_(2),H_(2)O,N_(2),and H_(2).Among them,H_(2)O has the earliest generation time,and the reaction rate constant(k_(3))is the largest.Many clusters are formed during the decomposition of PYX,and the formation,aggregation,and decomposition of these clusters are strongly affected by temperature.At low temperatures(2500 K-2750 K),many clusters are formed.At high temperatures(2750 K-3250 K),the clusters aggregate to form larger clusters.At 3500 K,the large clusters decompose and become small.In the late stage of the reaction,H and N in the clusters escaped almost entirely,but more O was trapped in the clusters,which affected the auto-oxidation process of PYX.PYX's initial decomposition activation energy(E_(a))was calculated to be 126.58 kJ/mol.This work contributes to a theoretical understanding of PYX's entire thermal decomposition process.

Sparse Modal Decomposition Method Addressing Underdetermined Vortex-Induced Vibration Reconstruction Problem for Marine Risers

When investigating the vortex-induced vibration(VIV)of marine risers,extrapolating the dynamic response on the entire length based on limited sensor measurements is a crucial step in both laboratory experiments and fatigue monitoring of real risers.The problem is conventionally solved using the modal decomposition method,based on the principle that the response can be approximated by a weighted sum of limited vibration modes.However,the method is not valid when the problem is underdetermined,i.e.,the number of unknown mode weights is more than the number of known measurements.This study proposed a sparse modal decomposition method based on the compressed sensing theory and the Compressive Sampling Matching Pursuit(Co Sa MP)algorithm,exploiting the sparsity of VIV in the modal space.In the validation study based on high-order VIV experiment data,the proposed method successfully reconstructed the response using only seven acceleration measurements when the conventional methods failed.A primary advantage of the proposed method is that it offers a completely data-driven approach for the underdetermined VIV reconstruction problem,which is more favorable than existing model-dependent solutions for many practical applications such as riser structural health monitoring.

基于FPGA与DMD的微型近红外光谱采集系统设计

为解决DMD型近红外光谱仪采集时间长、光谱实时性较低的问题,提出采用现场可编程门阵列(FPGA)作为主控单元,以DMD为核心的近红外光谱采集系统设计。FPGA控制图案数据通过24 bit的并行接口实时传输,驱动DMD选通入射光,同时进行A/D转换,实现光谱数据快速采集。对于阿达玛矩阵适配数字微镜面的问题,FPGA图案显示设计中,将常规阿达玛编码模板拆分为适配DMD微镜面的编码图案。最后通过样品采集实验对系统的性能进行测试验证,结果表明在900~1 700 nm的工作波段内,214个样本点的平均信噪比达到4 600∶1;在连续采集模式下,系统单次采集耗时优于0.147 s,满足工作中光谱实时采集的应用需求。

POD和DMD方法对燃料棒流致振动特性的分析

燃料棒的流致振动是造成燃料失效和反应堆停堆的重要因素之一,研究其流致振动机理非常必要。本文建立了燃料棒的高保真有限元模型,基于ANSYS Batch和随机振动理论批量计算了不同支撑刚度下燃料棒的流致振动响应,并搭建了1个流致振动响应数据库。该数据库采用不同支撑刚度值来模拟和检查燃料棒可能遇到的情况。基于数据库组装快照矩阵,采用两种数据驱动方法(POD方法和DMD方法)搭建了1个高保真降阶模型(ROM),该ROM能够实现流致振动响应的快速重构。对比了POD方法和DMD方法重构燃料棒流致振动响应的效果以及各自的优点和缺点。研究发现:使用相同数量的模态重构燃料棒的流致振动响应时,POD方法的重构效果优于DMD方法;基于相同数量的模态重构时,刚度为1 N/mm的重构效果最差,这主要是因为刚度越小,频率越小,系统的振幅越大,需要更多数量的模态才能捕捉大幅振动带来的影响;DMD方法不仅能够高效地重构燃料棒的振动响应,还能够判断每个DMD模态的稳定性。

基于DMD的并行压缩感知时域关联成像

针对非周期时变光信号的高速探测问题,文章提出一种并行压缩感知和时域关联成像相结合的测量方法,同时借助空间光调制器DMD高速调制能力,可在探测器单次曝光时间内恢复快速时变信号,对非周期性快速时变信号具有良好的恢复效果。通过实验验证,方法可恢复频率1kHz的时变信号,并且具有很高的信噪比。

Modified multiple-component scattering power decomposition for PolSAR data based on eigenspace of coherency matrix

A modified multiple-component scattering power decomposition for analyzing polarimetric synthetic aperture radar(PolSAR)data is proposed.The modified decomposition involves two distinct steps.Firstly,ei⁃genvectors of the coherency matrix are used to modify the scattering models.Secondly,the entropy and anisotro⁃py of targets are used to improve the volume scattering power.With the guarantee of high double-bounce scatter⁃ing power in the urban areas,the proposed algorithm effectively improves the volume scattering power of vegeta⁃tion areas.The efficacy of the modified multiple-component scattering power decomposition is validated using ac⁃tual AIRSAR PolSAR data.The scattering power obtained through decomposing the original coherency matrix and the coherency matrix after orientation angle compensation is compared with three algorithms.Results from the experiment demonstrate that the proposed decomposition yields more effective scattering power for different PolSAR data sets.

DMD基因突变的孤独症谱系障碍儿童1例报告并文献复习

目的对DMD基因突变的1例6岁孤独症谱系障碍(autism spectrum disorder,ASD)男性患儿进行报告,并通过文献回顾探讨DMD基因缺陷患者的ASD共患率,分析该类患者的遗传学特点,以提高对该亚型ASD的认识。方法利用染色体微阵列分析技术对ASD先证者进行检测,多重连接探针扩增技术(multiplex ligation-dependent probe amplification,MLPA)对候选突变进行家系验证。对患儿临床表型与基因型进行分析,并系统复习DMD基因突变与ASD的相关文献。结果患儿存在DMD基因arr[hg19]Xp21.1(31,518,750-31,878,971)×0微缺失,涉及DMD基因48—55号外显子,MLPA验证提示该缺失遗传自无疾病表型的母亲。文献回顾表明:贝克尔肌营养不良症(Becker muscular dystrophy,BMD)患者ASD的共患率在0.00%(0/17)~11.43%(8/70),而杜氏肌营养不良症(Duchenne muscular dystrophy,DMD)在0.0%(0/50)~54.5%(30/55)。BMD与DMD相比,前者所有队列ASD共患率的中位数(3.6%)低于后者的中位数(6.4%),但差异无统计学意义。DMD基因突变的位置与ASD发病是否相关存在争议。结论DMD基因48—55号外显子缺失可能是患儿存在BMD和ASD的共同病因。DMD基因的基因型与ASD临床表型的关系需要进一步的研究。

Ba promoter effect on cobalt-catalyzed ammonia decomposition kinetics: A theoretical analysis

Ammonia decomposition is a key reaction in the context of hydrogen storage, transport, and release. This study combines density functional theory(DFT) calculations with microkinetic modeling to address the promotion mechanism of Ba species for ammonia decomposition on Co catalysts. The modified adsorption properties of Co upon the addition of metallic Ba or BaO suggest that the promoters play a role in alleviating the competitive adsorption of H. Calculating the full reaction pathway of ammonia decomposition shows that limiting the investigation to the N–N association step, as done previously, overlooks the effect of the promoter on the energy barriers of the NHxdehydrogenation steps. Challenges of modeling the ammonia decomposition reaction are addressed by understanding that the NH_(2) intermediate is stabilized on the step sites rather than the terrace sites. When the effect of H-coverage on the adsorption of NH_(3) is not considered in the microkinetic simulations, the results conflict with the experiments.However, accounting for the effect of H-coverage, as performed here, shows that BaO-doped Co has higher rates than pristine Co and Ba-doped Co at the reaction temperature of 723.15 K. When H is adsorbed on the Ba-doped Co, the adsorption of ammonia becomes significantly endergonic, which makes the rates relatively slow. The superiority of the BaO-promoted catalyst is attributed to a lower energy for the transition state of the rate-determining step, coupled with a reduced impact of the hydrogen coverage on weakening the ammonia adsorption. The kinetic analysis of the influence of Ba and BaO on the Co surface shows that BaO-doped Co aligns more closely with experimental observations than Badoped Co. This implies that Ba on the Co surface is likely to be in an oxide form under reaction conditions.Understanding the kinetics of the ammonia decomposition reaction provides a foundation for developing highly effective catalysts to accelerate the industrial utilization of ammonia as a sustainable hydrogen carrier.

Rate-limiting factors in hydrate decomposition through depressurization across various scales:A mini-review

Natural gas hydrate is an energy resource for methane that has a carbon quantity twice more than all traditional fossil fuels combined.However,their practical application in the field has been limited due to the challenges of long-term preparation,high costs and associated risks.Experimental studies,on the other hand,offer a safe and cost-effective means of exploring the mechanisms of hydrate dissociation and optimizing exploitation conditions.Gas hydrate decomposition is a complicated process along with intrinsic kinetics,mass transfer and heat transfer,which are the influencing factors for hydrate decomposition rate.The identification of the rate-limiting factor for hydrate dissociation during depressurization varies with the scale of the reservoir,making it challenging to extrapolate findings from laboratory experiments to the actual exploitation.This review aims to summarize current knowledge of investigations on hydrate decomposition on the subject of the research scale(core scale,middle scale,large scale and field tests)and to analyze determining factors for decomposition rate,considering the various research scales and their associated influencing factors.

Evolutionary Multi/Many-Objective Optimisation via Bilevel Decomposition

Decomposition of a complex multi-objective optimisation problem(MOP)to multiple simple subMOPs,known as M2M for short,is an effective approach to multi-objective optimisation.However,M2M facilitates little communication/collaboration between subMOPs,which limits its use in complex optimisation scenarios.This paper extends the M2M framework to develop a unified algorithm for both multi-objective and manyobjective optimisation.Through bilevel decomposition,an MOP is divided into multiple subMOPs at upper level,each of which is further divided into a number of single-objective subproblems at lower level.Neighbouring subMOPs are allowed to share some subproblems so that the knowledge gained from solving one subMOP can be transferred to another,and eventually to all the subMOPs.The bilevel decomposition is readily combined with some new mating selection and population update strategies,leading to a high-performance algorithm that competes effectively against a number of state-of-the-arts studied in this paper for both multiand many-objective optimisation.Parameter analysis and component analysis have been also carried out to further justify the proposed algorithm.

Generalized load graphical forecasting method based on modal decomposition

In a“low-carbon”context,the power load is affected by the coupling of multiple factors,which gradually evolves from the traditional“pure load”to the generalized load with the dual characteristics of“load+power supply.”Traditional time-series forecasting methods are no longer suitable owing to the complexity and uncertainty associated with generalized loads.From the perspective of image processing,this study proposes a graphical short-term prediction method for generalized loads based on modal decomposition.First,the datasets are normalized and feature-filtered by comparing the results of Xtreme gradient boosting,gradient boosted decision tree,and random forest algorithms.Subsequently,the generalized load data are decomposed into three sets of modalities by modal decomposition,and red,green,and blue(RGB)images are generated using them as the pixel values of the R,G,and B channels.The generated images are diversified,and an optimized DenseNet neural network was used for training and prediction.Finally,the base load,wind power,and photovoltaic power generation data are selected,and the characteristic curves of the generalized load scenarios under different permeabilities of wind power and photovoltaic power generation are obtained using the density-based spatial clustering of applications with noise algorithm.Based on the proposed graphical forecasting method,the feasibility of the generalized load graphical forecasting method is verified by comparing it with the traditional time-series forecasting method.