全校師生：
我校定于2019年5月30日舉辦研究生靈犀學(xué)術(shù)殿堂——Piotr Breitkopf教授報(bào)告會(huì)，現(xiàn)將有關(guān)事項(xiàng)通知如下：
1.報(bào)告會(huì)簡(jiǎn)介
報(bào)告人：Piotr Breitkopf教授
時(shí)間：2019年5月30日（星期四）上午10：30-12：10
地點(diǎn)：長(zhǎng)安校區(qū)理學(xué)院數(shù)學(xué)系214會(huì)議室
報(bào)告題目：Model Order Reduction, Intrusive and Noninstrusive Approaches
模型降階/縮減模型，侵入式和非侵入式近似方法
內(nèi)容簡(jiǎn)介：
Industrial usage of numerical math-based tools such as the finite element method may in some applications become prohibitive due to the computational cost. This is particularly true in the automotive sector when optimizing the shape of a vehicle in crash situations. Model Order Reduction addresses this issue. Most model order reduction methods rely on the construction of a reduced basis to project the model on. The Proper Orthogonal Decomposition (POD) builds a modal basis from solution observations called snapshots. Data are in a first stage taken from full order model runs and then processed in a so-called off-line phase to give the reduced basis which is then used to build the reduced model. However, some difficulties arise in the POD. The data generated in the observation phase may become huge and hard to manipulate. Moreover, the computational cost for post-processing this data may as well explode. Another issue concerns the numerical integration schemes, i.e. the position of numerical integration points and the integration weights. Finally, the source code of the solver is not always available, requiring thus non-intrusive approaches.
在實(shí)際的工業(yè)應(yīng)用中，力求高精度的數(shù)值計(jì)算（有限元法、有限體積法以及邊界元法等）來(lái)獲得精確的目標(biāo)函數(shù)值和約束函數(shù)值，所需計(jì)算時(shí)間太長(zhǎng)，而在優(yōu)化過(guò)程中因需要多次這樣的迭代，往往讓計(jì)算量大到無(wú)法實(shí)現(xiàn)的地步。如何縮減理論的數(shù)值計(jì)算方法與實(shí)際復(fù)雜工程的巨大計(jì)算量的距離，成為不容忽視的一個(gè)難題，特別是在汽車(chē)行業(yè)，當(dāng)優(yōu)化車(chē)輛在碰撞情況下的形狀時(shí)尤其如此，目前已有一些模型降階方法來(lái)解決此類(lèi)問(wèn)題，但大多數(shù)模型降階方法依賴(lài)于所構(gòu)造的降階基來(lái)對(duì)模型進(jìn)行投影。利用正交分解(POD)從高精度的數(shù)值模型得到的快照（解的觀(guān)測(cè)值）信息來(lái)構(gòu)建一個(gè)模態(tài)基，然后在降維后的模型中進(jìn)行近似求解。然而，這種思路仍存在一些困難，這體現(xiàn)在這種縮減模型的構(gòu)造要求高精度的數(shù)值測(cè)量信息量必須很大，但對(duì)于一些復(fù)雜的實(shí)際問(wèn)題，往往很難得到這樣的大量信息；其次，對(duì)這些數(shù)據(jù)進(jìn)行后處理的計(jì)算成本也可能會(huì)激增；此外，還會(huì)涉及到數(shù)值積分問(wèn)題，即數(shù)值積分點(diǎn)的位置和積分權(quán)重的選取問(wèn)題；最后，求解程序的源代碼并不總是可用的，因此需要采用非侵入式算法。本報(bào)告重點(diǎn)對(duì)這種近似方式進(jìn)行詳細(xì)講解。
2.歡迎各學(xué)院師生前來(lái)聽(tīng)報(bào)告。報(bào)告會(huì)期間請(qǐng)關(guān)閉手機(jī)或?qū)⑹謾C(jī)調(diào)至靜音模式。
黨委學(xué)生工作部
理學(xué)院
2019年5月26日
報(bào)告人簡(jiǎn)介
Piotr Breitkopf is the head of the Multidisciplinary Design Optimization team at Université de Technologie de Compiègne (UTC), France. His research fields involve: computational mechanics, reduced order modeling, design optimization and high performance computing. He has obtained his PhD from Polish Academy of Sciences in 1988, and habilitation (HDR) from UTC in 1998. Since 2010 he is Deputy Director of Roberval Laboratory, a joint CNRS-UTC research unit. He is member of the steering committee of Labex MS2T. In 2014 he was nominated Oversea Expert of the Center for Foreign Talents Introduction and Academic Exchange of Mechanical Behavior of Advanced Structures and Materials at NPU. Together with Professor Zhang Weihong he presides the joint French-Chinese research group "Virtual Prototyping and Design". He serves at various editorial boards, scientific councils and scientific associations. He has authored and co-authored more than 200 peer reviewed journal papers, book chapters and referenced conference papers.
Piotr Breitkopf法國(guó)科學(xué)院高級(jí)工程師，1988年獲波蘭科學(xué)院博士，1998年獲法國(guó)貢比涅技術(shù)大學(xué)教授資格，研究領(lǐng)域涉及計(jì)算力學(xué)、縮減模型、優(yōu)化設(shè)計(jì)、高性能計(jì)算等。是法國(guó)貢比涅技術(shù)大學(xué)多學(xué)科優(yōu)化團(tuán)隊(duì)的帶頭人，2010年至今，擔(dān)任法國(guó)科學(xué)院與貢比涅技術(shù)大學(xué)聯(lián)合國(guó)家重點(diǎn)實(shí)驗(yàn)室(Roberval)副主任，Labex MS2T指導(dǎo)委員會(huì)成員。2014年被評(píng)為西北工業(yè)大學(xué)國(guó)外人才引進(jìn)和先進(jìn)結(jié)構(gòu)材料力學(xué)行為學(xué)術(shù)交流中心的國(guó)外專(zhuān)家，他與張衛(wèi)紅教授共同主持中法聯(lián)合研究小組“虛擬樣機(jī)與設(shè)計(jì)”。是各種編輯委員會(huì)、科學(xué)委員會(huì)和科學(xué)協(xié)會(huì)任職。撰寫(xiě)并合著200多篇同行評(píng)議的SCI期刊論文、書(shū)籍章節(jié)和參考會(huì)議論文。
