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2种聚烯烃的水平流淌燃烧行为及熔体流变性

高分子材料科学与工程 2024年第6期40卷 92-98页

作者：王勇周奥辉李亚萍段蕾孙诗洋武汉科技大学资源与环境工程学院湖北武汉430081

聚合物熔融燃烧时会产生大量流滴熔体,严重影响燃烧行为和火灾危害,但是多数研究集中于垂直燃烧模式,仅少量研究探讨了几种生胶的水平燃烧行为。文中测定了聚乙烯和聚丙烯水平燃烧时的熔体流淌面积和质量损失速率,通过设计的锥形量热仪... 详细信息

聚合物熔融燃烧时会产生大量流滴熔体,严重影响燃烧行为和火灾危害,但是多数研究集中于垂直燃烧模式,仅少量研究探讨了几种生胶的水平燃烧行为。文中测定了聚乙烯和聚丙烯水平燃烧时的熔体流淌面积和质量损失速率,通过设计的锥形量热仪样品盒收集了水平流淌熔体并表征其熔融温度和剪切黏度。研究发现,与熔体流动受限相比,聚乙烯和聚丙烯的水平流淌燃烧面积增大约10倍,最大燃烧速率增加超过1倍。在50kW/m2热辐射作用下,聚乙烯和聚丙烯在临近着火时就出现熔体流淌现象,且水平燃烧流淌熔体分别占到试样初始质量的58%和42%,与垂直燃烧滴落熔体质量占比相近,流淌熔体的熔融温度比原聚合物低6.2℃,黏流活化能比原聚合物分别减小34.4%和29.9%。

关键词：锥形量热仪熔体流淌流变聚乙烯聚丙烯

深部矿山不同埋藏深度岩石拉压力学特性试验研究

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工程地质学报 2024年第1期32卷 86-95页

作者：李地元罗平框朱志根方旭刚周奥辉何啸马金银中南大学资源与安全工程学院长沙410083 长沙有色冶金设计研究院有限公司长沙410019 云南驰宏锌锗股份有限公司会泽矿业分公司会泽654200

岩石的物理力学特性随埋藏深度增大会发生变化。本文以云南某矿山900~1200 m深度范围内4个不同埋藏深度的矿体上下盘围岩(灰质白云岩)为研究对象,开展了不同含水条件下(自然状态和饱水状态)的单轴压缩和巴西劈裂试验,探明深部岩石力学... 详细信息

岩石的物理力学特性随埋藏深度增大会发生变化。本文以云南某矿山900~1200 m深度范围内4个不同埋藏深度的矿体上下盘围岩(灰质白云岩)为研究对象,开展了不同含水条件下(自然状态和饱水状态)的单轴压缩和巴西劈裂试验,探明深部岩石力学基本物理力学特性随埋深的变化规律。研究结果表明:在研究的深度范围内,岩石基本物理成分组成及结构相似,随着岩石埋藏深度的增加,岩石试样的密度、纵波波速、单轴抗压强度、抗拉强度和弹性模量等均略微增大,而泊松比呈先增大后减小的趋势。含水条件对岩石的力学特性影响显著,不同埋藏深度的岩石试样进行饱水处理后其抗压强度、抗拉强度和弹性模量均明显减小,泊松比显著增大,其中岩石单轴抗压强度对水的敏感性高于其他参数对水的敏感性,各参数对水的敏感性排序为:抗压强度>弹性模量>泊松比>抗拉强度。本研究很好地揭示了深部矿山不同埋藏深度围岩的拉压力学特性变化规律。

关键词：深部开采深部岩石力学工程地质含水率

双轴压缩下缓倾层状砂岩力学特性及损伤本构模型研究

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中南大学学报（自然科学版） 2023年第3期54卷 1074-1086页

作者：李地元周奥辉王立川张鹏飞中南大学资源与安全工程学院湖南长沙410083 中南大学土木工程学院湖南长沙410075 中铁十八局集团有限公司天津300222

为揭示缓倾层状岩石在双轴应力状态下的力学特征与损伤演化规律,开展15°倾角以内层状砂岩的双轴压缩试验。为准确描述层状岩石的损伤演化过程,采用等效应变原理,结合横观各向同性岩石的弹性本构关系和统计损伤力学理论,建立双轴应力作... 详细信息

为揭示缓倾层状岩石在双轴应力状态下的力学特征与损伤演化规律,开展15°倾角以内层状砂岩的双轴压缩试验。为准确描述层状岩石的损伤演化过程,采用等效应变原理,结合横观各向同性岩石的弹性本构关系和统计损伤力学理论,建立双轴应力作用下层状岩石的统计损伤本构模型,并对试样压密段进行修正。分别采用解析法和拟合法对统计损伤模型进行求解验证。研究结果表明:缓倾层状砂岩在双轴应力作用下,其峰值强度和弹性模量均随层理倾角的增大而减小,随侧压的增大而增大;试样在破坏时均表现出劈裂和剪切复合型破坏的形态,随着层理倾角增加,试样破坏的主控因素逐渐由穿切层面的剪切裂纹转变为沿层面的剪切裂纹,随着侧压增大,试样破坏时产生的宏观裂纹逐渐增多,试样被这些裂纹切割成块,甚至出现板裂状剥落破坏;在压密段采用拟合法、弹性段和峰值后区采用解析法所得到的模型曲线与试验曲线吻合很好,所建立的损伤本构方程可以较好地反映缓倾层状岩石在双轴压缩下的损伤效应。

关键词：缓倾层状砂岩双轴压缩试验破坏模式统计损伤本构横观各向同性

热辐射强度对5种橡胶生胶燃烧和热解特性的影响

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高分子材料科学与工程 2023年第6期39卷 54-63页

作者：邹成祥李肖肖张金香周奥辉王勇武汉科技大学资源与环境工程学院湖北武汉430081

为探究热辐射强度对橡胶生胶燃烧和热解特性的影响,以天然橡胶(NR)、三元乙丙橡胶(EPDM)、顺丁橡胶(BR)、丁腈橡胶(NBR)和丁苯橡胶(SBR)为研究对象,利用锥形量热仪测定生胶的燃烧行为,发现在不同强度热辐射作用下,NR和EPDM的热释放速率(... 详细信息

为探究热辐射强度对橡胶生胶燃烧和热解特性的影响,以天然橡胶(NR)、三元乙丙橡胶(EPDM)、顺丁橡胶(BR)、丁腈橡胶(NBR)和丁苯橡胶(SBR)为研究对象,利用锥形量热仪测定生胶的燃烧行为,发现在不同强度热辐射作用下,NR和EPDM的热释放速率(HRR)曲线均为后单峰型,但BR,NBR和SBR的HRR曲线会从35 kW/m^(2)热辐射强度下的后单峰型转变为15 kW/m^(2)热辐射强度下的双峰型。该双峰型曲线的形成可以通过着火前样品的外观变化和热解特性演化进行解释。在15 k W/m^(2)热辐射作用下,BR,NBR和SBR样品的上半部分出现了多分层现象,表面形成了较多的硬质炭层,且至少有1个分层的残碳率和热解反应活化能均大于35 kW/m^(2)热辐射作用下样品表层的残碳率和热解反应活化能。该分层现象和热解特性演化可能与低强度热辐射作用下生胶较长时间处于交联反应温度区间有关,而NR和EPDM的交联作用因为返原现象而大幅削弱,故而在15 kW/m^(2)热辐射强度下没有出现双峰型HRR曲线。

关键词：橡胶生胶锥形量热仪热释放速率热解动力学

Parallel Physics-Informed Neural Networks Method with Regularization Strategies for the Forward-Inverse Problems of the Variable Coefficient Modified KdV Equation

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Journal of Systems Science & Complexity 2024年第2期37卷 511-544页

作者： zhou Huijuan School of Science Shanghai Maritime UniversityShanghai 201306China

This paper mainly introduces the parallel physics-informed neural networks(PPINNs)method with regularization strategies to solve the data-driven forward-inverse problems of the variable coefficient modified Korteweg-de Vries(VC-MKdV)*** the forward problem of the VC-MKdV equation,the authors use the traditional PINN method to obtain satisfactory data-driven soliton solutions and provide a detailed analysis of the impact of network width and depth on solving accuracy and ***,the author finds that the traditional PINN method outperforms the one with locally adaptive activation functions in solving the data-driven forward problems of the VC-MKdV *** for the data-driven inverse problem of the VC-MKdV equation,the author introduces a parallel neural networks to separately train the solution function and coefficient function,successfully addressing the function discovery problem of the VC-MKdV *** further enhance the network’s generalization ability and noise robustness,the author incorporates two regularization strategies into the *** amount of numerical experimental data in this paper demonstrates that the PPINNs method can effectively address the function discovery problem of the VC-MKdV equation,and the inclusion of appropriate regularization strategies in the PPINNs can improves its performance.

关键词： Data-driven forward-inverse problems parallel physics-informed neural networks regularization strategies variable coefficient modified KdV equation

Influence of stearic acid surface modification on flowability and agglomeration of battery grade Li_(2)CO_(3)powder

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Particuology 2024年第9期92卷 263-277页

作者： Ming zhou Lithium Industry Center Zhejiang New Era Zhongneng Technology Co.Ltd.Shaoxing312000China

This work investigates the flow and agglomeration behaviors of battery grade Li_(2)CO_(3)powder and the influence of stearic acid surface *** degree of agglomeration is directly related to the uniformity of Li_(2)CO_(3)and its powder *** to the Chinese National Nonferrous Metal Industry Standard,battery grade Li_(2)CO_(3)powder has D50 equal to 3–8μm which belongs to a micron-sized superfine ***,with the extension of storage time,the serious agglomeration phenomenon occurs due to the large specific surface area and rough and irregular powder *** Hausner ratio(HR)of the unmodified sample increases from 1.14 to 1.41,and the corresponding flowability is classified as good to ***,among samples with doping stearic acid,the optimum amount of it is 0.10 wt%which exhibits an extremely stable HR value from 1.14 to ***,after 156 days,the repose angle(AR)obtained for samples without surface modification and using 0.10 wt%stearic acid are calculated to be 49°and 28°,*** on the values of HR and AR,the flowability of the unmodified sample is poor while the sample modified with 0.10 wt%of stearic acid still maintain excellent powder flow ***,The LiMn_(2)O_(4)cathode material synthesized from modified Li_(2)CO_(3)powder with a stearic acid content of 0.10 wt%exhibits good crystallinity and comparable electrochemical performance to that prepared by commercial Li_(2)CO_(3).These results indicate that stearic acid has the potential to be an ideal modifier for battery grade Li_(2)CO_(3)powder that needs to be kept for a long time.

关键词： Battery grade Li_(2)CO_(3)powder Flowability Surface modification Stearic acid

奥尔托喀讷什锰矿粗骨料胶结充填体试验研究及配比优化

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金属矿山 2023年第4期 37-44页

作者：姚宣成刘中柱罗平框周奥辉长沙有色冶金设计研究院有限公司湖南长沙410019 中南大学资源与安全工程学院湖南长沙410083

充填体材料的强度及充填体料浆的浓度、流动性和阻力坡降等是矿山充填体系统设计的关键指标,事关矿山的充填质量及矿山生产安全。为了保证矿山安全生产和降低矿山充填成本,针对奥尔托喀讷什锰矿矿山现状,选取了风化较少的青黑色废石和... 详细信息

充填体材料的强度及充填体料浆的浓度、流动性和阻力坡降等是矿山充填体系统设计的关键指标,事关矿山的充填质量及矿山生产安全。为了保证矿山安全生产和降低矿山充填成本,针对奥尔托喀讷什锰矿矿山现状,选取了风化较少的青黑色废石和风化较多的土黄色废石,分别开展了材料基本物化性质试验、充填料胶结强度配比优化试验研究、充填料浆流变参数及输送性能研究等一系列试验。研究了不同粗骨料、水灰比、养护时间及料浆浓度对粗骨料胶结充填体单轴抗压强度、塌落度及充填体料浆流动性的影响,并进一步对粗骨料胶结充填体物料配比进行了优化。实验结果表明:当粗料为全粒径≤10 mm混合废石、灰砂比为1∶4时,充填体试块强度最大,料浆不易堵管或大量堆积于管道中;料浆浓度保持在82%~80%时,充填料浆的和易性和流动性较好;充填体料浆流速随浓度的下降快速上升,静料柱高也显著下降。

关键词：粗骨料塌落度流动性充填体强度水灰比

Phase field modeling of ferroelastic variant switching in yttria-stabilized t'zirconia with strain gradient elasticity and interface tension

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Science China(Technological Sciences) 2024年第5期67卷 1443-1457页

作者： zhou QianQian WEI YueGuang zhou YiChun YANG Li College of Engineering BIC-ESATPeking UniversityBeijing100871China School of Advanced Materials and Nanotechnology Xidian UniversityXi’an710126China Frontier Research Center of Thin Films and Coatings for Device Applications Academy of Advanced Interdisciplinary ResearchXidian UniversityXi’an710126China

The 6–8 wt%yttria-stabilized zirconia with a tetragonal structure(t’-YSZ)is extensively employed in thermal barrier *** exceptional fracture toughness of t’-YSZ can be attributed to its distinctive ferroelastic toughening *** and interface tension play a critical role in ferroelastic variant switching at the micro-and *** paper presents an original thermodynamically consistent phase field(PF)theory for analyzing ferroelastic variant switching at the micro-and nano-scale of t’-*** theory incorporates strain gradient elasticity using higher-order elastic energy and interface tension tensor via geometric nonlinearity to represent biaxial tension resulting from interface ***,a mixed-type formulation is employed to implement the higher-order theory through the finite element *** an interface in equilibrium,the effects of strain gradient elasticity result in a more uniform distribution of stresses,whereas the presence of interface tension tensor significantly amplifies the stress magnitude at the *** introduction of an interface tension tensor increases the maximum value of stress at the interface by a factor of 4 to *** nucleation and evolution of variants at a pre-existing crack tip in a mono-phase t’-YSZ have also been *** strain gradient elasticity is capable of capturing the size effect of ferroelastic variant switching associated with microstructures in ***,when the grain size approaches that of the specimen,the critical load required for variant switching at the crack tip increases,resulting in greater dissipation of elastic energy during ferroelastic variant ***,the interface tension accelerates the evolution of *** presented framework exhibits significant potential in modeling ferroelastic variant switching at the micro-and nano-scale.

关键词： thermodynamics strain gradient elasticity interface tension phase field method ferroelastic variant switching

Deep-reinforcement-learning-based UAV autonomous navigation and collision avoidance in unknown environments

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Chinese Journal of Aeronautics 2024年第3期37卷 237-257页

作者： Fei WANG Xiaoping ZHU zhou zhou Yang TANG School of Astronautics Northwestern Polytechnical UniversityXi’an 710072China School of Aeronautics Northwestern Polytechnical UniversityXi’an 710072China

In some military application scenarios,Unmanned Aerial Vehicles(UAVs)need to perform missions with the assistance of on-board cameras when radar is not available and communication is interrupted,which brings challenges for UAV autonomous navigation and collision *** this paper,an improved deep-reinforcement-learning algorithm,Deep Q-Network with a Faster R-CNN model and a Data Deposit Mechanism(FRDDM-DQN),is proposed.A Faster R-CNN model(FR)is introduced and optimized to obtain the ability to extract obstacle information from images,and a new replay memory Data Deposit Mechanism(DDM)is designed to train an agent with a better *** training,a two-part training approach is used to reduce the time spent on training as well as retraining when the scenario *** order to verify the performance of the proposed method,a series of experiments,including training experiments,test experiments,and typical episodes experiments,is conducted in a 3D simulation *** results show that the agent trained by the proposed FRDDM-DQN has the ability to navigate autonomously and avoid collisions,and performs better compared to the FRDQN,FR-DDQN,FR-Dueling DQN,YOLO-based YDDM-DQN,and original FR outputbased FR-ODQN.

关键词： Faster R-CNN model Replay memory Data Deposit Mechanism(DDM) Two-part training approach Image-based Autonomous Navigation and Collision Avoidance(ANCA) Unmanned Aerial Vehicle(UAV)