Development and Manufacturing of Highly Damage Resistant Fiber Glass Reinforced Window Panels for Buildings in Hurricane Prone Areas
为飓风多发地区的建筑物开发和制造高抗损伤玻璃纤维增强窗板
基本信息
- 批准号:9975382
- 负责人:
- 金额:$ 28.9万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Continuing Grant
- 财政年份:1999
- 资助国家:美国
- 起止时间:1999-08-15 至 2001-09-30
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
This project attempts to develop and manufacture a new fiber-glass reinforced transparent laminated glass window to alleviate the breakage of glass panels during windstorms. The proposed glass panel will consist of an outer glass ply; a fiber glass reinforced plastic (polyester) ply, and an inner glass ply. Subsequently the reinforced panels will be subjected to extensive testing and fracture analysis under simulated windstorm conditions.The goal is to obtain maximum toughness and an optimized glass composite panel, which is highly damage resistant, lighter and cheaper than the present panels. The study will also focus on the effect of the variations in the interface properties such as adhesion between layers and the interface fracture toughness. Interfacial properties between glass and polyester matrix will be studied by carrying out fiber pull-out and nanohardness tests using an Interfacial Force Microscope (IFM), a scanning force microscope capable of performing nanomechanical measurements and imaging. Stress field equations will be developed for a crack in the istropic-anistropic bimaterial interface. These stress field equations will be combined with the orthotropic stress optic law to analyze the isochromatic fringe patterns around an interface crack tip under mixed mode loading to determine the stress intensity factors. The body of knowledge generated and experience gained from this effort will be useful in developing other similar types of panels based on different composite systems in future. Also other agencies involved in producing advanced materials for civil infrastructure and transport systems can benefit. The successful implementation of the experimental and analytical approaches and fabrication of the proposed product (the composite-glass panel), will have a lasting effect on several industries and businesses, and contribute to the advancement of knowledge and science of composite materials. Collaboration with an industrial partner in Saint Louis has been established to facilitate the manufacturing and utilization of the glass reinforced panels.
本项目试图开发和制造一种新型的玻璃纤维增强透明夹层玻璃窗,以减轻玻璃板在风暴中的破碎。 建议的玻璃面板将包括外部玻璃层、玻璃纤维增强塑料(聚酯)层和内部玻璃层。 随后,将在模拟风暴条件下对增强板进行广泛的测试和断裂分析,目标是获得最大的韧性和优化的玻璃复合板,这种玻璃复合板比目前的板具有高度的抗破坏性,重量更轻,价格更便宜。 该研究还将集中在界面性能的变化,如层间粘附力和界面断裂韧性的影响。 玻璃和聚酯基体之间的界面性能将进行研究,通过使用界面力显微镜(IFM),能够进行纳米力学测量和成像的扫描力显微镜进行纤维拔出和纳米硬度测试。 将建立各向同性-各向异性双材料界面裂纹的应力场方程。 将这些应力场方程与正交各向异性应力光学定律相结合,分析了复合型载荷下界面裂纹尖端的等色线条纹图,从而确定了应力强度因子。 从这一努力中产生的知识和经验将有助于今后开发基于不同复合系统的其他类似类型的面板。 参与生产民用基础设施和运输系统先进材料的其他机构也可以受益。 实验和分析方法的成功实施以及拟议产品(复合玻璃面板)的制造将对多个行业和企业产生持久影响,并有助于复合材料知识和科学的进步。 与圣刘易斯的一个工业伙伴建立了合作关系,以促进玻璃强化板的制造和利用。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Sanjeev Khanna其他文献
Maximum Bipartite Matching in ?2+?(1) Time via a Combinatorial Algorithm
通过组合算法在 ?2+?(1) 时间内实现最大二分匹配
- DOI:
- 发表时间:
2024 - 期刊:
- 影响因子:0
- 作者:
Julia Chuzhoy;Sanjeev Khanna - 通讯作者:
Sanjeev Khanna
Palette Sparsification Beyond (∆ + 1) Vertex 1 Coloring 2
调色板稀疏化超出 (Δ + 1) 顶点 1 着色 2
- DOI:
- 发表时间:
2020 - 期刊:
- 影响因子:0
- 作者:
Noga Alon;Sepehr Assadi;Suman Bera;Amit Chakrabarti;Prantar Ghosh;Guru Guruganesh;David Harris;Sanjeev Khanna;Hsin - 通讯作者:
Hsin
Theory of Computing
计算理论
- DOI:
10.4086/toc - 发表时间:
2013 - 期刊:
- 影响因子:0
- 作者:
Alexandr Andoni;Nikhil Bansal;P. Beame;Giuseppe Italiano;Sanjeev Khanna;Ryan O’Donnell;T. Pitassi;T. Rabin;Tim Roughgarden;Clifford Stein;Rocco Servedio;Amir Abboud;Nima Anari;Ibm Srinivasan Arunachalam;T. J. Watson;Research Center;Petra Berenbrink;Aaron Bernstein;Aditya Bhaskara;Sayan Bhattacharya;Eric Blais;H. Bodlaender;Adam Bouland;Anne Broadbent;Mark Bun;Timothy Chan;Arkadev Chattopadhyay;Xue Chen;Gil Cohen;Dana Dachman;Anindya De;Shahar Dobzhinski;Zhiyi Huang;Ken;Robin Kothari;Marvin Künnemann;Tu Kaiserslautern;Rasmus Kyng;E. Zurich;Sophie Laplante;D. Lokshtanov;S. Mahabadi;Nicole Megow;Ankur Moitra;Technion Shay Moran;Google Research;Christopher Musco;Prasad Raghavendra;Alex Russell;Laura Sanità;Alex Slivkins;David Steurer;Epfl Ola Svensson;Chaitanya Swamy;Madhur Tulsiani;Christos Tzamos;Andreas Wiese;Mary Wootters;Huacheng Yu;Aaron Potechin;Aaron Sidford;Aarushi Goel;Aayush Jain;Abhiram Natarajan;Abhishek Shetty;Adam Karczmarz;Adam O’Neill;Aditi Dudeja;Aditi Laddha;Aditya Krishnan;Adrian Vladu Afrouz;J. Ameli;Ainesh Bakshi;Akihito Soeda;Akshay Krishnamurthy;Albert Cheu;A. Grilo;Alex Wein;Alexander Belov;Alexander Block;Alexander Golovnev;Alexander Poremba;Alexander Shen;Alexander Skopalik;Alexandra Henzinger;Alexandros Hollender;Ali Parviz;Alkis Kalavasis;Allen Liu;Aloni Cohen;Amartya Shankha;Biswas Amey;Bhangale Amin;Coja;Yehudayoff Amir;Zandieh Amit;Daniely Amit;Kumar Amnon;Ta;Beimel Anand;Louis Anand Natarajan;Anders Claesson;André Chailloux;André Nusser;Andrea Coladangelo;Andrea Lincoln;Andreas Björklund;Andreas Maggiori;A. Krokhin;A. Romashchenko;Andrej Risteski;Anirban Chowdhury;Anirudh Krishna;A. Mukherjee;Ankit Garg;Anna Karlin;Anthony Leverrier;Antonio Blanca;A. Antoniadis;Anupam Gupta;Anupam Prakash;A. Singh;Aravindan Vijayaraghavan;Argyrios Deligkas;Ariel Kulik;Ariel Schvartzman;Ariel Shaulker;A. Cornelissen;Arka Rai;Choudhuri Arkady;Yerukhimovich Arnab;Bhattacharyya Arthur Mehta;Artur Czumaj;A. Backurs;A. Jambulapati;Ashley Montanaro;A. Sah;A. Mantri;Aviad Rubinstein;Avishay Tal;Badih Ghazi;Bartek Blaszczyszyn;Benjamin Moseley;Benny Pinkas;Bento Natura;Bernhard Haeupler;Bill Fefferman;B. Mance;Binghui Peng;Bingkai Lin;B. Sinaimeri;Bo Waggoner;Bodo Manthey;Bohdan Kivva;Brendan Lucier Bundit;Laekhanukit Burak;Sahinoglu Cameron;Seth Chaodong Zheng;Charles Carlson;Chen;Chenghao Guo;Chenglin Fan;Chenwei Wu;Chethan Kamath;Chi Jin;J. Thaler;Jyun;Kaave Hosseini;Kaito Fujii;Kamesh Munagala;Kangning Wang;Kanstantsin Pashkovich;Karl Bringmann Karol;Wegrzycki Karteek;Sreenivasaiah Karthik;Chandrasekaran Karthik;Sankararaman Karthik;C. S. K. Green;Larsen Kasturi;Varadarajan Keita;Xagawa Kent Quanrud;Kevin Schewior;Kevin Tian;Kilian Risse;Kirankumar Shiragur;K. Pruhs;K. Efremenko;Konstantin Makarychev;Konstantin Zabarnyi;Krišj¯anis Pr¯usis;Kuan Cheng;Kuikui Liu;Kunal Marwaha;Lars Rohwedder László;Kozma László;A. Végh;L'eo Colisson;Leo de Castro;Leonid Barenboim Letong;Li;Li;L. Roditty;Lieven De;Lathauwer Lijie;Chen Lior;Eldar Lior;Rotem Luca Zanetti;Luisa Sinisclachi;Luke Postle;Luowen Qian;Lydia Zakynthinou;Mahbod Majid;Makrand Sinha;Malin Rau Manas;Jyoti Kashyop;Manolis Zampetakis;Maoyuan Song;Marc Roth;Marc Vinyals;Marcin Bieńkowski;Marcin Pilipczuk;Marco Molinaro;Marcus Michelen;Mark de Berg;M. Jerrum;Mark Sellke;Mark Zhandry;Markus Bläser;Markus Lohrey;Marshall Ball;Marthe Bonamy;Martin Fürer;Martin Hoefer;M. Kokainis;Masahiro Hachimori;Matteo Castiglioni;Matthias Englert;Matti Karppa;Max Hahn;Max Hopkins;Maximilian Probst;Gutenberg Mayank Goswami;Mehtaab Sawhney;Meike Hatzel;Meng He;Mengxiao Zhang;Meni Sadigurski;M. Parter;M. Dinitz;Michael Elkin;Michael Kapralov;Michael Kearns;James R. Lee;Sudatta Bhattacharya;Michal Koucký;Hadley Black;Deeparnab Chakrabarty;C. Seshadhri;Mahsa Derakhshan;Naveen Durvasula;Nika Haghtalab;Peter Kiss;Thatchaphol Saranurak;Soheil Behnezhad;M. Roghani;Hung Le;Shay Solomon;Václav Rozhon;Anders Martinsson;Christoph Grunau;G. Z. —. Eth;Zurich;Switzerland;Morris Yau — Massachusetts;Noah Golowich;Dhruv Rohatgi — Massachusetts;Qinghua Liu;Praneeth Netrapalli;Csaba Szepesvári;Debarati Das;Jacob Gilbert;Mohammadtaghi Hajiaghayi;Tomasz Kociumaka;B. Saha;K. Bringmann;Nick Fischer — Weizmann;Ce Jin;Yinzhan Xu — Massachusetts;Virginia Vassilevska Williams;Yinzhan Xu;Josh Alman;Kevin Rao;Hamed Hatami;—. XiangMeng;McGill University;Edith Cohen;Xin Lyu;Tamás Jelani Nelson;Uri Stemmer — Google;Research;Daniel Alabi;Pravesh K. Kothari;Pranay Tankala;Prayaag Venkat;Fred Zhang;Samuel B. Hopkins;Gautam Kamath;Shyam Narayanan — Massachusetts;Marco Gaboardi;R. Impagliazzo;Rex Lei;Satchit Sivakumar;Jessica Sorrell;T. Korhonen;Marco Bressan;Matthias Lanzinger;Huck Bennett;Mahdi Cheraghchi;V. Guruswami;João Ribeiro;Jan Dreier;Nikolas Mählmann;Sebastian Siebertz — TU Wien;The Randomized k ;Conjecture Is;False;Sébastien Bubeck;Christian Coester;Yuval Rabani — Microsoft;Wei;Ethan Mook;Daniel Wichs;Joshua Brakensiek;Sai Sandeep — Stanford;University;Lorenzo Ciardo;Stanislav Živný;Amey Bhangale;Subhash Khot;Dor Minzer;David Ellis;Guy Kindler;Noam Lifshitz;Ronen Eldan;Dan Mikulincer;George Christodoulou;E. Koutsoupias;Annamária Kovács;José Correa;Andrés Cristi;Xi Chen;Matheus Venturyne;Xavier Ferreira;David C. Parkes;Yang Cai;Jinzhao Wu;Zhengyang Liu;Zeyu Ren;Zihe Wang;Ravishankar Krishnaswamy;Shi Li;Varun Suriyanarayana - 通讯作者:
Varun Suriyanarayana
Approximation algorithms for data placement on parallel disks
并行磁盘上数据放置的近似算法
- DOI:
10.1145/1597036.1597037 - 发表时间:
2009 - 期刊:
- 影响因子:0
- 作者:
L. Golubchik;Sanjeev Khanna;Samir Khuller;R. Thurimella;An Zhu - 通讯作者:
An Zhu
A greedy approximation algorithm for minimum-gap scheduling
- DOI:
10.1007/s10951-016-0492-y - 发表时间:
2016-07-27 - 期刊:
- 影响因子:1.800
- 作者:
Marek Chrobak;Uriel Feige;Mohammad Taghi Hajiaghayi;Sanjeev Khanna;Fei Li;Seffi Naor - 通讯作者:
Seffi Naor
Sanjeev Khanna的其他文献
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{{ truncateString('Sanjeev Khanna', 18)}}的其他基金
Collaborative Research: AF: Medium: Fast Combinatorial Algorithms for (Dynamic) Matchings and Shortest Paths
合作研究:AF:中:(动态)匹配和最短路径的快速组合算法
- 批准号:
2402284 - 财政年份:2024
- 资助金额:
$ 28.9万 - 项目类别:
Continuing Grant
AF: Small: Sublinear Algorithms for Flows, Matchings, and Routing Problems
AF:小:流、匹配和路由问题的次线性算法
- 批准号:
2008305 - 财政年份:2020
- 资助金额:
$ 28.9万 - 项目类别:
Standard Grant
AF: Small: Sublinear Algorithms for Graph Optimization Problems
AF:小:图优化问题的次线性算法
- 批准号:
1617851 - 财政年份:2016
- 资助金额:
$ 28.9万 - 项目类别:
Standard Grant
AF: EAGER: Small Space Algorithms and Representations for Graph Optimization Problems
AF:EAGER:图优化问题的小空间算法和表示
- 批准号:
1552909 - 财政年份:2015
- 资助金额:
$ 28.9万 - 项目类别:
Standard Grant
AF: Small: Cut, Flow, and Matching Problems in Graphs
AF:小:图中的切割、流动和匹配问题
- 批准号:
1116961 - 财政年份:2011
- 资助金额:
$ 28.9万 - 项目类别:
Standard Grant
III: Medium: Collaborative Research: Optimization with Sparse Priors--Algorithms, Indices, and Economic Incentives
III:媒介:协作研究:稀疏先验优化——算法、指数和经济激励
- 批准号:
0904314 - 财政年份:2009
- 资助金额:
$ 28.9万 - 项目类别:
Continuing Grant
Effectiveness of problem based learning in a materials science course in the engineering curriculum
基于问题的学习在工程课程材料科学课程中的有效性
- 批准号:
0836914 - 财政年份:2009
- 资助金额:
$ 28.9万 - 项目类别:
Standard Grant
Collaborative Research: CT-T: DoS Prevention in Shared Channels
合作研究:CT-T:共享通道中的 DoS 预防
- 批准号:
0524269 - 财政年份:2005
- 资助金额:
$ 28.9万 - 项目类别:
Standard Grant
Acquisition of a Nanomechanical Testing Platform to Establish a User Center for Nanomecanical Characterization Materials
收购纳米力学测试平台,建立纳米力学表征材料用户中心
- 批准号:
0420859 - 财政年份:2004
- 资助金额:
$ 28.9万 - 项目类别:
Standard Grant
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A highly adaptable Manufacturing System for new and existing bicycle, e-bike, cargo bike, and specialist cycle producers.
适用于新的和现有的自行车、电动自行车、货运自行车和专业自行车生产商的高度适应性的制造系统。
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BEIS-Funded Programmes
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