Search

Your search keyword '"Yang, Lang"' showing total 1,498 results
Start Over Author "Yang, Lang"
1,498 results on '"Yang, Lang"'

3. Multidimensional water level and water quality response to severe drought in Xingyun Lake

Author

Junxu Chen, Jia Xu, Qi Yi, Jiabin Peng, Yang Lang, Liang Emlyn Yang, and Jihui Zhang

Subjects
Severe drought, Water level, Water quality, Statistics test, Synthesized methodology, Science (General), Q1-390, Social sciences (General), H1-99
Abstract

Drought stress has a significant impact on the quality and quantity of lake water. Understanding this impact is crucial for preventing water security risks and pollution recovery. However, there is a lack of systemic understanding of how drought affects water quality and quantity, and how they change in multiple dimensions. This manuscript established a synthesized methodology with the principles to judge the applicability and three steps of application to detect the change in water quality and water level under severe drought in Xingyun Lake, China. Results show that (1) The water level and water quality of Xingyun Lake have a synchronous and evident response to drought during 2009–2014. The rainfall during 2008–2015 declined by 22.9 % to normal, and the inundated area and lake water depth in 2012 decreased by 10.50 % from 2002 to 1.38 m to the average depth, respectively. The pollution index climbed above 1.21 after 2008, fluctuating around 1.42. (2) Under drought, the water quality indicators significantly changed in the terms of the overall feature, trend, eigenvalue, and morphological characteristics. The water quality indicators of Set2008-2015 are significantly different from set2000-2007 and not in the groups of set1994-2000. The morphological characteristics of water quality indicators in set2008-2015 differs significantly from that in set2000-2007 shown by the minimum, maximum, median, quartiles, and extreme values. (3) Although NH3–N showed no significant change, the water quality deteriorated in the physical, chemical, and biological aspects. The TP, IMN, and BOD5 changed more evidently than DO and NH3–N. (4) Water quality grade and indicator concentration deteriorated significantly and sharply under severe drought and are threatened deeply by TP and TN. The synthesized methodology is scientifically constructed and canbe employed in the characteristics cognition of water quality and water level to severe drought in and out of this research. And the intervention time and various regulating measures for pollution degradation and water quality recovery canbe constructed based on the multi-dimensional analysis of water quality change under drought evolution.

Published
2024
Full Text
View/download PDF

9. The Effects of Campus Shootings on School Finance and Student Composition

Author

Yang, Lang and Gopalan, Maithreyi

Abstract

Between 1999 and 2018, 210 shootings have occurred on public school campuses in the United States. The increased need for security and student support may crowd out instructional resources post-shooting. Shootings may also cause students, especially those from socioeconomically advantaged backgrounds, to move away, leading to declines in enrollment. Both changes in the budget allocation and the student composition could exert a negative impact on achievement. First, we examine the effects of campus shootings on public school districts' revenue, expenditure, debt, and staffing using a long panel of district-year data. Results from event study and difference-in-differences analyses indicate that shootings increase per-pupil spending by $248, which is funded primarily through increased federal transfers. Most spending increases occur in noninstructional functions, such as pupil support services, and capital projects, but they do not crowd out instructional spending. Using school-level data, we show that shootings are followed by a decline in enrollment, driven almost exclusively by reductions in students who do not receive free or reduced-price lunch. Private schools in the area also experience enrollment drop. In sum, despite the increased intergovernmental transfers, campus shootings reduce the desirability of the community and lead to the exit of relatively well-off families.

Published
2023
Full Text
View/download PDF

11. Precision Non-Alcoholic Fatty Liver Disease (NAFLD) Diagnosis: Leveraging Ensemble Machine Learning and Gender Insights for Cost-Effective Detection

Author

Azadeh Alizargar, Yang-Lang Chang, Mohammad Alkhaleefah, and Tan-Hsu Tan

Subjects
machine learning techniques, NAFLD, ensemble model, HSI, AUC, SMOTEENN, Technology, Biology (General), QH301-705.5
Abstract

Non-Alcoholic Fatty Liver Disease (NAFLD) is characterized by the accumulation of excess fat in the liver. If left undiagnosed and untreated during the early stages, NAFLD can progress to more severe conditions such as inflammation, liver fibrosis, cirrhosis, and even liver failure. In this study, machine learning techniques were employed to predict NAFLD using affordable and accessible laboratory test data, while the conventional technique hepatic steatosis index (HSI)was calculated for comparison. Six algorithms (random forest, K-nearest Neighbors, Logistic Regression, Support Vector Machine, extreme gradient boosting, decision tree), along with an ensemble model, were utilized for dataset analysis. The objective was to develop a cost-effective tool for enabling early diagnosis, leading to better management of the condition. The issue of imbalanced data was addressed using the Synthetic Minority Oversampling Technique Edited Nearest Neighbors (SMOTEENN). Various evaluation metrics including the F1 score, precision, accuracy, recall, confusion matrix, the mean absolute error (MAE), receiver operating characteristics (ROC), and area under the curve (AUC) were employed to assess the suitability of each technique for disease prediction. Experimental results using the National Health and Nutrition Examination Survey (NHANES) dataset demonstrated that the ensemble model achieved the highest accuracy (0.99) and AUC (1.00) compared to the machine learning techniques that we used and HSI. These findings indicate that the ensemble model holds potential as a beneficial tool for healthcare professionals to predict NAFLD, leveraging accessible and cost-effective laboratory test data.

Published
2024
Full Text
View/download PDF

17. Knee Point‐Based Multiobjective Optimization for the Numerical Weather Prediction Model in the Greater Beijing Area

Author

Heng Wang, Hongsu Mo, Zhenhua Di, Rui Liu, Yang Lang, and Qingyun Duan

Subjects
Geophysics. Cosmic physics, QC801-809
Abstract

Abstract Determination of the optimal parameter values in numerical weather prediction (NWP) models has a significant impact on predictions. Here, we propose a knee point‐based multiobjective optimization (KMO) method to find an optimal solution of the NWP model parameters. We apply it to optimize the Weather Research and Forecasting (WRF) model's summer precipitation and temperature simulations for the Greater Beijing area. The results showed that it required fewer than 125 samples (i.e., 25 times the number of dimensions of the parameter space) to obtain the WRF model's optimal parameter values. The optimal parameters determined by KMO outperform the default parameters in WRF simulations for summer precipitation and temperature prediction in the Greater Beijing area, across all periods (calibration, validation, and testing). Additionally, clear physical interpretations are provided to explain why the optimal parameters lead to improved precipitation and temperature forecasting. Overall, the proposed method is effective and efficient to improve NWP.

Published
2023
Full Text
View/download PDF

31. Influencing Factors of Hospital Costs for Pituitary Tumor Under DRG Payment

Author

YANG Lang, WEI Junji, YIN Rui, WEN Junxian, CHANG Jianbo, CHEN Yihao, ZHANG Xiao, ZHANG Guojie, LI Chunhou, MA Wenbin, and WANG Renzhi

Subjects
diagnosis related groups, hospital costs, pituitary tumor, Medicine
Abstract

Objective To analyze the influencing factors of hospitalization expenses of patients treated in the KC19 group by the neurosurgery department of a tertiary hospital in Beijing, and provide reference for the refinement of diagnosis related groups(DRG). Methods The medical records of 3809 patients from January 1, 2017 to November 30, 2021 were reviewed, and relevant influencing factors were determined using descriptive statistics, univariate analysis, and multivariate linear regression. Results Among the 3809 patients included in this study, the average total hospitalization cost was 36 166.82 yuan, and the average hospital stay was 9.42 days. Neuroendoscopy accounted for 35.2%, while major complications or comorbidities (MCC) and complications or comorbidity (CC) accounted for 40%. Univariate analysis found that hospitalization costs were associated with gender, length of hospital stay, number of other diagnoses, number of surgical procedures, use of neuroendoscopy, and the presence of MCC or CC. Multivariate analysis found that the main influencing factors were the length of hospital stay, followed by the number of other diagnoses, the number of surgical operations, whether neuroendoscopy was used, whether there was MCC or CC, and gender. Conclusion In the follow-up fine grouping of KC19, the above influencing factors should be considered, and the use of neuroendoscopy and the presence of MCC or CC should be included in the grouping criteria.

Published
2023
Full Text
View/download PDF

34. The third Intensive Care Bundle with Blood Pressure Reduction in Acute Cerebral Haemorrhage Trial (INTERACT3): an international, stepped wedge cluster randomised controlled trial

Author

Robinson, Thompson, Miranda, J. Jaime, Anderson, Craig S., You, Chao, Song, Lili, Parry-Jones, Adrian, Sprigg, Nikola, Durrans, Sophie, Harris, Caroline, Bamford, Ann, Smith, Olivia, Herbert, Robert, Chen, Christopher, Whiteley, William, Hu, Rong, Billot, Laurent, Li, Qiang, Mysore, Jayanthi, Hu, Xin, Zhang, Yao, Liu, Feifeng, Sakamoto, Yuki, You, Shoujiang, Han, Qiao, Crutzen, Bernard, Li, Yunke, Cheung, Emily, Jan, Stephen, Liu, Hueiming, Ouyang, Menglu, Sun, Lingli, Chu, Honglin, Anjum, Anila, Gonzalez Mc Cawley, Francisca, Del Rio, Alejandra, Rimoli, Bruna, Cerantola, Rodrigo, Jeevarajah, Thanushanthan, Kannangara, Madhushani, Joseph, Andrene, Nanayakkara, Chamath, Chen, Xiaoying, Malavera, Alejandra, Zhang, Chunmiao, Yang, Zhao, Li, Brook, Meng, Zhuo, Liu, Leibo, Ning, Yi, Dong, Le, Armenis, Manuela, Lim, Joyce, Monaghan, Helen, Ma, Lu, Li, Xi, Luo, Rui, Cheng, Guojuan, Dong, Yilin, Liu, Ziqin, Wang, Shuihong, Zhang, Ying, Cheng, Jipeng, Shi, Hui, Li, Wenjing, Mou, Langming, Yi, Ping, Chen, Chen, Chen, Xue, Weerawardena, Shalomi, Ellawala, Poornima, Ranasinghe, Enalee, Rodrigo, Chrishmi, Wahab, Kolawala, Adeniyi, Sunday, Pandian, Jeyaraj, Khanna, Megha, Muñoz Venturelli, Paula, González, Francisca, Urrutia Goldsack, Francisca, Wasay, Mohammad, Begum, Dilshad, Pontes-Neto, Octavio, Camilo, Millene, Dias, Francisco, Vincenzi, Octavio, Moro, Carla, Santos, Renata, Texeira, Nara, Longo, Alexandre, Liberato, Rafaela, Martins, Sheila, Pille, Arthur, Chwal, Bruna, Silva, Isabel, Titton, Natacha, Weiss, Gustavo, Mora, Daissy, Ouriques, Magda, Carbonera, Leonardo, Bazan, Rodrigo, Modolo, Gabriel, Winckler, Fernanda, Miranda, Luana, Souza, Juli, Rojo, Alexis, Uslar, Wilhelm, Medel, Lorena, Lopez, Javiera, Herrero, Diego, Lavados, Pablo, Vargas Latorre, Barbara, Conejan, Nathalie, Esparza, Tomas, Sotomayor, Patricio, Wenger, Denisse, Gigoux, Juan Pablo, Letelier, Aldo, Acevedo, Lilian, Moya, Vivianne, Figueroa, Cristian, Vallejos, Nicol, Guerrero, Rodrigo, Velasquez, Mauricio, Vallejos, Jose, Pallauta, Kimerly, Santibanez, Tamara, Queirolo, Angelo, Lobos, Andrea, Jiang, Yongming, Li, Weimin, Huang, Wei, Luo, Ke, Liu, Gangying, Tang, Guanghai, Yang, Guang, Jiang, Hongtao, Zhang, Xu, Jing, Hongyan, Zhu, Sheng, Pu, Bo, Lv, Dong, Kang, Hui, Hu, Qiuping, She, Xiaochun, Jiang, Xiaoming, Chen, Yanli, Yang, Shenghua, He, Jianjun, Li, Zongping, Cheng, Gang, Huang, Hailin, Wang, Xiaoyi, Lin, Jianqiong, Chen, Minhui, Yang, Chenghao, Ding, Hao, Deng, Yunliang, Luo, Fei, Zhang, Rongjun, Wang, Xiaofeng, Zhang, Hongbing, Yang, Xiaoliang, Zhang, Yang, Yang, Chengyi, He, Yu, Liu, Feng, Wang, Rongjie, Zhang, Yuhui, Xin, Xiaodong, Feng, Bin, Hao, Wanru, Song, Chang, Guo, Yun, Jiang, Dehua, Chen, Jie, Tang, Changtong, Zhu, Hongliang, Li, Xin, Cui, Jin, Xu, Haidong, Li, Boyang, Tang, Fusheng, Li, Yuanbin, Gao, Min, Yang, Bo, Xu, Xuejun, Deng, Bing, Zheng, Yi, Ge, Yuanhong, Chen, Keyu, Liu, Yang, Li, Xinshen, Zhong, Tingting, Xu, Jianfeng, Zhang, Hai, Wang, Jiyue, Zhu, Jianxin, Sun, Hanyu, Yu, Fuhua, Zhang, Xueguang, Xu, Jianguo, Zhang, Mingsen, Wang, Bin, Ma, Yiming, Jiang, Donglin, Zhou, Jun, Liu, Cong, Nie, Wenhong, Li, Mingguo, Tian, Tao, Li, Yong, He, Mingfang, Tu, Xiaolong, Wu, Zhengjun, Liu, Hong, Zhong, Dongsheng, Jiang, Rongcai, Sun, Jian, Tian, Ye, Wei, Yingsheng, An, Shuo, Wei, Pingbo, Luo, Le, Lin, Bin, Liu, Gang, Wen, Yan, Cai, Qiang, Chen, Qianxue, Lei, Pan, Li, Zhiyang, Zhang, Meifang, He, Jiaquan, Chen, Yan, Liu, Jun, Liu, Xinghai, Li, Junyan, Chen, Min, Wang, Jing, Zhou, Bingzhi, Ye, Baichun, Zhang, Jiancheng, Zhang, Manyuan, Pan, Xuming, Yu, Xiaoxiang, Xu, Jian, Xiao, Qingbao, Wang, Yuefei, Tao, Liang, Shi, Lin, Zheng, Niandong, You, Guoliang, Lei, Bo, Chen, Shu, Wu, Honggang, Hu, Jin, Zhao, Jianlan, Yu, Jian, Yuan, Qiang, Du, Zhuoying, Tang, Xielin, Li, Qianke, Liu, Shenghua, Yang, Feilong, Xiao, Kui, Luo, Chao, Wang, Guang, Che, Xudong, Teng, Zhipeng, Wan, Wenwu, Li, Jun, Liu, Yu, Fan, Mingbo, Zhang, Tao, Cai, Lun, Ma, Yuan, Ma, Zhifeng, Li, Bin, He, Linlin, Li, Jinghui, Zhang, Weibing, Zhang, Shuxin, Zhang, Hongzhen, Dai, Yingguang, Lei, Jun, Mao, Lei, Huang, Yiyang, Zhou, Zhi, Chen, Ping, Chen, Fang, Wei, Pan, Li, Tiangui, Chen, Honglin, Zeng, Mengfei, Mou, Kejie, Xue, Jun, Jiang, Yong, Tang, Xiaoping, Chen, Tao, Zhang, Yalan, Xu, Yanbing, Gu, Yuchen, Chen, Lei, Zhao, Yujun, Yang, Bin, Kuai, Peng, Wang, Xi, Yang, Yuwang, Hu, Xueling, Zhang, Huitian, Yang, Yintao, Wang, Weifeng, Zhang, Junyi, Cheng, Wei, Zhang, Xiaoxue, Ma, Xiaowen, He, Qin, Zhang, Li, Gao, Rong, Liu, Huixiang, Ye, Jingwei, Xu, Ping, Wu, Xin, Yuan, Yuan, Zou, Peng, Zhang, Zhen, Cheng, Jiyong, Zhou, Zhangming, Zeng, Yijun, Liang, Zhang, Du, Deming, Yu, Shui, Cao, Yongjun, Xu, Jiaping, Huang, Zhichao, Chen, Dongqin, Xiao, Wenfeng, Zhu, Li, Yuan, Miao, Wang, Yuhai, Shi, Dongliang, Hu, Xu, Xiang, Dingchao, Shi, Like, Wang, Hongqin, Yang, Liu, Miao, Wang, Hu, Yiyi, Zhao, Yuchun, Hu, Xi, Zhou, Weiduo, Sun, Chao, Tang, Dong, Yao, Kun, You, Jin, Chen, Shishi, Yao, Jianmin, Li, Huanmei, Liu, Jinmei, Bai, Ailin, Yi, Yong, Deng, Qingshan, Luo, Peng, Wang, Han, Jiang, Jingcheng, Yang, Qingwei, He, Shunpo, Wang, Jun, Chen, Yu, He, Hua, Deng, Yuyang, Cao, Zhikai, Yi, Xuxia, Luo, Jinbiao, Luo, Shuang, Gong, Min, Liu, Li, Gao, Xuejun, Liu, Jia, Wu, Li'e, Zhang, Jia, Sun, Hongying, Li, Xinhui, Jia, Lu, Wu, Jianbing, Zhang, Jie, Zhang, Huajun, Du, Chunfu, Li, Shun, Yang, Xiaobin, He, Jie, Liao, Lei, Zhou, Gezhi, Dong, Wentao, Chen, Yunxiang, Lin, Xiaofeng, Shui, Xujian, Zhang, Peng, Zhao, Yuan, Yang, Hongli, Zhao, Wenbin, Zhang, Xiaoyi, Chen, Jincao, Wu, Qian, Dai, Xuan, Tang, Baogui, Wang, Yinjuan, Liu, Tao, Zhang, Haixia, Duan, Faliang, Luo, Ming, Jiao, Qingfang, Lei, Guoliang, Wang, Dong, Song, Chunwang, Tan, Haopeng, Ye, Feng, Qin, Xinghu, Liang, Xiaolong, Liu, Junling, Yang, Lang, Yang, Jie, Lin, Yapeng, Yang, Qian, Ma, Xuntai, Qi, Yinkuang, Pan, Baogen, Jiang, Caixia, Ye, Zhanying, Dong, Ce, Yue, Xiongfei, Yang, Xiaopeng, Maimaitiyiming, Tuoheti, Dong, Jun, Wu, Yonggang, Gao, Feng, Zhao, Deqiang, Zhang, Xinghai, Wang, PengJun, Jiang, Hongbo, Li, Jianping, Zhang, Wei, Chen, Jing, Tong, Haibo, Wang, Yonghong, Qiao, Kaipeng, Guo, Fuyou, Zhang, Mingchu, Hu, Yan, Feng, Mengzhao, Song, Dengpan, Zuo, Yi, Chen, Shangjun, Qian, Chao, Li, Baoming, Ma, Jingku, Zhang, Sunfu, Kong, Bin, Dong, Xingyu, Fang, Sheng, Lu, Bin, Li, Yang, Yang, Yongling, Yu, Hong, Sun, Huaiyu, Wang, Yue, Wang, Weimin, Li, Tong, Li, Shengli, Xu, Zhiming, Wang, Yongyi, Dong, Qiang, Tang, Yuping, Chu, Heling, Lu, Ying, Wang, Zhong, Sun, Xiaoou, Zhao, Jianhua, Yang, Shuaifeng, Qian, Xiying, Saroja, Aralikatte Onkarappa, Naik k, Ravishankar, Chindhi, Sandip, Pampaniya, Nakul, Amaresh, Kurubara, Iype, Thomas, R, Dileep, Rajan, Reeja, Panicker, Praveen, Das, Rupjyoti, Choudhury, Nupur, Gohain, Pankaja, Webster, Jemin, Pakma, Biyol, Sangi, Lalbiak, Sebastian, Ivy, Aggrawal, Gaurav, Raj, Komal, Rajoura, Deepankshi, Singh, Sulena, Aggrawal, Varun, Narang, Amit, Arauz, Antonio, Cano-Nigenda, Vanesa, López-Mena, Diego, Valdez-Ruvalcaba, Héctor, Toledo-Treviño, Roberto, Obiako, Reginald, Abubakar, Sani, Emeka, Oguike, Olayemi, Balogun, Lois, Melika, Philip, Ibinaiye, Comfort O, Olurishe, Okubadejo, Njideka, Agabi, Osigwe, Ojo, Oluwadamilola, Wahab, Kolawole, Bello, Abiodun, Ibukun, Oyinloye, Sanayaolu, Olufemi, Jimoh, Abdulraheem, Waheed, Shahid, Kamal, Dr.Ayeesha, Shoaib, Raja Farhat, Orooj, Fizza, Majid, Sadaf, Zehra, Taskeen, Khan, Abdus Salam, Shanker, Ravi, Syed, Nadir Ali, Ahmad, Nashwa, Abanto, Carlos, Valencia, Ana, Barrientos, Danny, Ramirez, Jorge, Calle, Pilar, Palliyeguruge, Dilum, Muthucumarana, Sumudu, Ratnayaka, Shiroma, Ganihiarachchi, Dilhara, Bandaranayake, Arundathi, Somaratne, S.D.B, Narayana, Saumya, Gallage, Sithara, Senanayake, Bimsara, Samarasiri, Udari, Luke, Dunya, Sivapathasundaram, Mythily, Sahadevan, Vithoosan, Rasmi, Amani, Deshaka, Yuran, Fernando, Nilukshi, Munasinghe, Aruna, Rathnapriya, Kapilanga, Nissanka, A.S, Karunathilake, Kanchana, Gayan, Isuru, Wijenayake, Kaminda, Gunasekara, Hasitha, Vidyarathne, Jagath, Keshavaraj, Ajantha, Janarthanan, Kanagasabapathy, Gerald Jeevathasan, Arhivalaky, Sivamainthan, Sivaram, John Priyanth, Mathyamuthan, John Priyanth, Abirami, Rajendiran, Thambippillai, Alwis, Sanjeewa, Gunasekare, Nushara, Liyanarachchi, Vasundara, Dissanayake, Athula, Uluwattage, Wimalasiri Mewa, Ratnayake, Gimhani, Rajinee, Charika, Jayawardana, Sakura, Peiris, Janaka, Wicramasinghe, Ranjith, Fernando, Chamila, Abbas, Jessie, Withanage, Nethmini, Bandara, Makaranda, Mai, Duy Ton, Nguyen, Van Chi, Dao, Viet Phuong, Vuong, Xuan Trung, Nguyen, Tien Dung, Dinh, Trung Hieu, Phan, Ha Quan, Bui, Quoc Viet, Phung, Dinh Tho, Pham, Quang Tho, Pham, Dinh Dai, Do, Duc Thuan, Dang, Phuc Duc, Dang, Minh Duc, Nguyen, Dang Hai, Nguyen, Thi Phuong Nga, Nguyen, Quoc Huy, Pham, Quoc Dai, Chau, Quoc Vinh, Tai, Vinh Thy Van, Le, Tran Vinh, Le, Cong Tri, Tran, Ha Mai Khuong, Nguyen, Huu Khanh, Ngyen, Hoang Minh Thao, Vo, Duc Chien, Nguyen, Thai My Phuong, Tran, Trung Thanh, Vo, Thi Hanh Vi, Cao, Hao Nhien, Nguyen, Ba Thang, Le, Thi Ngoc Suong, La, Thien Duc, Pham, Chi Duc, Thai, Huy, Muñoz-Venturelli, Paula, de Silva, Asita, Thang, Nguyen Huy, Wahab, Kolawole W, Pandian, Jeyaraj D, Pontes-Neto, Octavio M, Shi, Haiping, Wang, Xia, Zhao, Yang, Li, Hao, Liu, Yi, Jiang, Yan, Wu, Bo, Liu, Ming, and Anderson, Craig S

Published
2023
Full Text
View/download PDF

46. Numerical study on existing RC circular section members under unequal impact collision

Author

Liu Yanhui, Khalil Al-Bukhaiti, Zhao Shichun, Hussein Abas, Xu Nan, Yang Lang, Yan Xing Yu, and Han Daguang

Subjects
Medicine, Science
Abstract

Abstract Traffic accidents and derailed train-related incidents have occurred more often than ever in recent years, resulting in some economic damage and casualties. Reinforced concrete (RC) constructions often involve derailed train and vehicle accidents. Rarely are such side collisions studied in previous studies. To do this, high-fidelity simulation-based finite-element (FE) models are created in this paper to accurately simulate the collision of circular RC members with a derailed train. The reinforced concrete member structure is common in high-speed railway stations. The impact energy of the impact body is significant, causing structural member failure. It analyses the dynamic behavior of reinforced concrete members under unequal span impact loads. Numerical implementations of impact issues are discussed from the perspective of geometric, contact, and material properties. The reliability and precision of the ABAQUS code to solve impact issues are verified by comparing failure modes, impact, and deflection time history experimental outputs. By analysing the impact response characteristics, used the control variables to study the failure process and mode (including the characteristics of impact and reaction forces, deflection time history curve, impact force–deflection curve, and bearing reaction force–deflection curve). The reinforcement ratio, impact velocity, concrete strength, and slenderness ratio significantly affect shear crack pattern and development. Changes in impact velocity and slenderness ratio also affect member failure modes.

Published
2022
Full Text
View/download PDF

47. Experimental Study on Existing RC Circular Members Under Unequal Lateral Impact Train Collision

Author

Khalil AL-Bukhaiti, Liu Yanhui, Zhao Shichun, Hussein Abas, Xu Nan, Yang Lang, Yan Xing Yu, and Han Daguang

Subjects
impact duration, shear crack, impact test, failure mode, energy absorbed, locomotive train, Systems of building construction. Including fireproof construction, concrete construction, TH1000-1725
Abstract

Abstract With the fast growth of high-speed rail in recent years, derailment has become the first hidden danger of high-speed rail transportation. The high-speed train passes near the station building. So the train may derail and hit the station building. Building a high-speed railway station usually uses a reinforced concrete structure. As a result of high impact energy on the impact body, the reinforced concrete (RC) member may fail; the impact point is near the member's foot; the structural member's constraint can be considered fixed support. This paper investigates the dynamic behavior of four types of circular reinforced concrete members under unequal lateral impact loads. The RC member's failure mechanism and dynamic response addressed the significance of unequal lateral impact load. The usual circular reinforced concrete members are used as the model to perform the drop-weight impact test. The specimens' crack pattern, failure mechanism, impact, deflection, and strain time–history curves are obtained. Findings show that between the impact point and the adjacent support, shear fractures occur that fail in shear mode. Shear cracks are based on impact velocity, longitudinal reinforcement ratio, and stirrup ratio. One type is more destructive to members and nodes. A shear fracture occurs when a longitudinal reinforcement fractures towards the closer support. The effects of impact velocity, longitudinal reinforcement ratio, and stirrup ratio on the dynamic impact response are studied. The experimental results may help improve structural member impact resistance. The critical section (right side) computed the static shear resistance using shear force, whereas the maximum external load resistance determines static bending moment resistance. Understanding how circular members fail to be subjected to unequal lateral impact loads provides insight into circular RC members' impact design and damage evaluation.

Published
2022
Full Text
View/download PDF

49. Establishing an Agenda for Public Budgeting and Finance Research

Author

McDonald, Bruce, primary, Larson, Sarah, additional, Maher, Craig, additional, Kavanagh, Shayne, additional, Hunter, Kenneth, additional, Goodman, Christopher, additional, Minkowitz, Honey, additional, McCandless, Sean, additional, Afshan, Saman, additional, Jordan, Meagan, additional, Abbott, Michaela, additional, Afonso, Whitney, additional, Alibašić, Haris, additional, Allen, Joanne, additional, Allore, John, additional, Altizer, Laura, additional, Amador, Ralph, additional, An, Brian, additional, Andonoska, Ljubinka, additional, Anguelov, Lachezar, additional, Arapis, Theodore, additional, Arcand, Carolyn, additional, Atisa, George, additional, Bailey, Lonce, additional, Baker, Celeste, additional, Barnett, Brian, additional, Barsky, Christina, additional, Bartle, John, additional, Beck, David, additional, Beckett-Camarata, Jane, additional, Bednarczuk, Michael, additional, Beeninga, Toy, additional, Bellamy, Terry, additional, Bilmes, L. J., additional, Block, Carol, additional, Boyd, David, additional, Boyd, Kaelan, additional, Brien, Spencer, additional, Bronner, Kevin, additional, Brook, Douglas, additional, Brown, Marlon, additional, Brunjes, Benjamin, additional, Brunner, Eric, additional, Bunch, Beverly, additional, Calabrese, Thad, additional, Carr, Douglas, additional, Casciato, Michelle, additional, Certain, Crystal, additional, Charles, Cleopatra, additional, Chen, Can, additional, Chen, Gang, additional, Cherney, Debby, additional, Christian, Cary, additional, Clark, Benjamin, additional, Corbin, Shane, additional, Costie, Daniel, additional, Cournoyer, Jason, additional, Crosby, Andrew, additional, Cummins, Jeff, additional, Davis, Stephanie, additional, Decker, J. W., additional, DeShazo, Jessica, additional, Dimand, Ana Maria, additional, Donahue, Amy, additional, Douglas, James, additional, Dutcher, Janet, additional, Dzigbede, Komla, additional, Eger, Robert, additional, Ely, Todd, additional, Ermasova, Natalia, additional, Farmer, Liz, additional, Farmer, Lucianna, additional, Faulk, Dagney, additional, Finley, Drew, additional, Flink, Carla, additional, Ford, Michael, additional, Foth, Daniel, additional, Franklin, Aimee, additional, Franks, Mike, additional, Fudge, Marc, additional, Funderburg, Richard, additional, Gabrini, Carl, additional, Gadow, Bryan, additional, Gentry, David, additional, Godlewski, Chris, additional, Gooding, Suzanne, additional, Grandage, Andrew, additional, Greer, Robert, additional, Griffith, Christian, additional, Grogan, Amanda, additional, Hackbart, Merl, additional, Hatcher, William, additional, Hattery, Michael, additional, Hayes, Michael, additional, Hebert, Kellie, additional, Hendrick, Rebecca, additional, Hill, Edward, additional, Hiscocks, Susan, additional, Ho, Alfred, additional, Hoang, Trang, additional, Holbrook, Ellenore, additional, Hoppe, Mike, additional, Hou, Yilin, additional, Hudson, John, additional, Hudspeth, Nancy, additional, Huffman, Jackie, additional, Ivonchyk, Mikhail, additional, Jolley, G. Jason, additional, Jones, Peter, additional, Juffras, Jason, additional, Justice, Jonathan, additional, Kass, Amanda, additional, Kerns, Heidi, additional, Kim, Junghack, additional, Kim, Saerim, additional, Korn, Lynn, additional, Kriz, Arwi, additional, Krupa, Olha, additional, Lampman, Jennifer, additional, Landers, Jim, additional, Lane, Keith, additional, Lee, Jekyung, additional, Lee, Keith, additional, Lee, Sooho, additional, Leight, Matthew, additional, Leiser, Stephanie, additional, Moreta, Agustin, additional, Levine, Helisse, additional, Levitas, Tony, additional, Lim, Sungdae, additional, Lofton, Michelle, additional, Lozano-Rojas, Felipe, additional, Luby, Martin, additional, Lukongo, Onyumbe, additional, Mace, Jennifer, additional, Mahar, Kaitrin, additional, Martin, Joseph, additional, Matkin, David, additional, Mau, Rusty, additional, McAdoo, Arche, additional, McCann, Anthony, additional, Mead, Dean, additional, Medlin, Kirk, additional, Menifield, Charles, additional, Merritt, Justin, additional, Metro, John, additional, Meyers, Roy, additional, Mitchell, David, additional, Moeller, Thomas, additional, Mohr, Zachary, additional, Moldogaziev, Temirlan, additional, Morehead, Bryant, additional, Morrill, Chris, additional, Mughan, Sian, additional, Munro, Joyce, additional, Neubauer, Bruce, additional, Neuman, Melissa, additional, Nguyen-Hoang, Phuong, additional, Nicole, Marc, additional, Nordin, James, additional, Nukpezah, Julius, additional, O'Brien, Susan, additional, Oland, Amy, additional, Osteen, Julie, additional, Overholser, Amber, additional, Overton, Michael, additional, Park, Sungho, additional, Paschal, Jordan, additional, Pathak, Rahul, additional, Phaup, Marvin, additional, Pierson, Kawika, additional, Pope, Wendy, additional, Propheter, Geoffrey, additional, Redburn, Steve, additional, Reder, Lesley, additional, Reed, David, additional, Reitano, Vincent, additional, Riddle, Sam, additional, Rivenbark, William, additional, Rodriguez, Alejandro, additional, Romito, Mark, additional, Ross, Justin, additional, Rubin, Irene, additional, Sadler, Nicholas, additional, Sarpy, Nicholas, additional, Schafer, Josephine, additional, Schuhmann, Robert, additional, Searing, Elizabeth, additional, Sekwat, Alex, additional, Shybalkina, Iuliia, additional, Singla, Akheil, additional, Smith, Alex, additional, Smith, Christy, additional, Smith, Zachary, additional, Snow, Douglas, additional, Stanisevski, Dragan, additional, Stehle, Jon, additional, Stokan, Eric, additional, Stone, Samuel, additional, Swindell, David, additional, Taylor, Charles, additional, Taylor, Lori, additional, Vu, Tran, additional, Toland, Jay, additional, Topinka, John, additional, Trammell, Evelyn, additional, Trogen, Paul, additional, Van Eenoo, Ed, additional, Wadle, Elizabeth, additional, Wallace, Sally, additional, Wang, Shu, additional, Wassmer, Rob, additional, Weinstein, Paul, additional, Wells, Amy, additional, Wheeler, Laura, additional, Williams, Daniel, additional, Willoughby, Katherine, additional, Wilson, Darrin, additional, Winfree, Paul, additional, Wojda, Sharon, additional, Wooldridge, Blue, additional, Worsham, Paige, additional, Wright, Kristina, additional, Wynn, Stefen, additional, Xiao, Yan, additional, Xu, H., additional, Yang, Lang, additional, Yusuf, Wie, additional, Zemrani, Aziza, additional, Zhao, Zhirong, additional, and Zielke, Nancy, additional

Published
2024
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results