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Proposing a computational modeling Framework for Generating Masonry Wall Units, Enhancing the Information Within a BIM

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Operations Research Forum 2024年第2期5卷 52页

作者： McClymonds, Austin D. Asadi, Somayeh Leicht, Robert M. Department of Civil and Environmental Engineering University of Virginia Charlottesville VA United States The Pennsylvania State University University Park PA United States

In recent decades, the construction industry has undergone a technological shift incorporating innovative technologies, such as robotics. However, information requirements must be met to integrate robotics further. Currently, building information models (BIM) contain substantial project information that can be leveraged for robots to create construction tasks, but for some building systems, the level of development (LOD) is inadequate to support these new requirements. Therefore, this study proposes a framework to increase the LOD of building systems by considering location information (X, Y, Z), orientation, material type, and component I.D. The computational modeler, Dynamo, is leveraged to increase the model’s LOD, extract information, and facilitate robotic task execution in the future. A case study is presented for multiple masonry room configurations developed in Autodesk Revit, where masonry units are generated and placed into design locations based on the geometry of the wall system. The case study used concrete masonry units (CMU) and standard brick. The number of partial-sized and full-sized blocks for each configuration was recorded, along with the computational time required to generate the units. It was observed that room configurations with more openings had longer computational times when compared to rooms constructed from the same material. After running the script, the model is reviewed to ensure accuracy and prevent overlaps or gaps in the model. The workflow provides insight into the methods used to interpret model geometry and extract information. © The Author(s) 2024.

关键词： BIM computational modeling Information exchange Masonry construction Robotic construction

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computational modeling of autonomic nerve stimulation: Vagus et al.

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CURRENT OPINION IN BIOMEDICAL ENGINEERING 2024年 32卷 100557页

作者： Grill, Warren M. Pelot, Nicole A. Duke Univ Dept Biomed Engn Durham NC 27708 USA

computational models of electrical stimulation, block and recording of autonomic nerves enable analysis of mechanisms of action underlying neural responses and design of optimized stimulation parameters. We reviewed advances in computational modeling of autonomic nerve stimulation, block, and recording over the past five years, with a focus on vagus nerve stimulation, including both implanted and less invasive approaches. Few models achieved quantitative validation, but integrated computational pipelines increase the reproducibility, reusability, and accessibility of computational modeling. Modelbased optimization enabled design of electrode geometries and stimulation parameters for selective activation (across fiber locations or types). Growing efforts link models of neural activity to downstream physiological responses to represent more directly the therapeutic effects and side effects of stimulation. Thus, computational modeling is an increasingly important tool for analysis and design of bioelectronic therapies.

关键词： computational modeling Vagus nerve stimulation Peripheral nerve stimulation Autonomic nerve stimulation Neural engineering

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computational modeling of animal behavior in T-mazes: Insights from machine learning

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ECOLOGICAL INFORMATICS 2024年 81卷

作者： Turab, Ali Sintunavarat, Wutiphol Ullah, Farhan Zaidi, Shujaat Ali Montoyo, Andres Nescolarde-Selva, Josue-Antonio Northwestern Polytech Univ Sch Software 127 West Youyi Rd Xian 710072 Peoples R China Thammasat Univ Rangsit Ctr Fac Sci & Technol Dept Math & Stat Pathum Thani 12120 Thailand Chiang Mai Univ Fac Sci Dept Comp Sci Chiang Mai Thailand Univ Alicante Dept Software & Comp Syst Alicante Spain Univ Alicante Dept Appl Math Alicante Spain

This study investigates the intricacies of animal decision-making in T-maze environments through a synergistic approach combining computational modeling and machine learning techniques. Focusing on the binary decisionmaking process in T-mazes, we examine how animals navigate choices between two paths. Our research employs a mathematical model tailored to the decision-making behavior of fish, offering analytical insights into their complex behavioral patterns. To complement this, we apply advanced machine learning algorithms, specifically Support Vector Machines (SVM), K-Nearest Neighbors (KNN), and a hybrid approach involving Principal Component Analysis (PCA) for dimensionality reduction followed by SVM for classification to analyze behavioral data from zebrafish and rats. The above techniques result in high predictive accuracies, approximately 98.07% for zebrafish and 98.15% for rats, underscoring the efficacy of computational methods in decoding animal behavior in controlled experiments. This study not only deepens our understanding of animal cognitive processes but also showcases the pivotal role of computational modeling and machine learning in elucidating the dynamics of behavioral science.

关键词： Animal behavior Decision-making T-mazes computational modeling Solution Machine learning methods

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computational modeling studies on microfluidic fuel cell: A prospective review

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RENEWABLE & SUSTAINABLE ENERGY REVIEWS 2024年 191卷

作者： Wu, Baoxin Xu, Xinhai Dong, Guangzhong Zhang, Mingming Luo, Shijing Leung, Dennis Y. C. Wang, Yifei Harbin Inst Technol Sch Mech Engn & Automat Shenzhen Peoples R China Univ Hong Kong Dept Mech Engn Hong Kong Peoples R China

Microfluidic fuel cell (MFC) is a burgeoning category of micro fuel cell technology based on laminar flow electrolytes. The merits of MFC, such as the absence of membrane electrolyte, flexible reactants selection, and high electrolyte conductivity, have been attracting researchers to explore this frontier area over the past two decades. However, realizing practical applications of MFCs remains a tremendous challenge. Many research works have been done to expedite research progress and obtain results reflecting inner mechanism via computational modeling and simulation, the general procedure of which is introduced in this paper. These studies primarily investigate the effects of various geometrical and operational parameters on diverse cell performance metrics, such as open-circuit voltage, current and power densities, and fuel utilization efficiency. However, contradictory outcomes and conclusions may arise due to disparities in the structural and parametric characteristics among different MFC models. In this regard, this review comprehensively summarizes prior computational modeling studies on MFC technology, with specific emphasis on different cell components including microchannels, inlets and outlets, electrodes, etc., as well as effects of different operational conditions encompassing electrolyte input, cell vibration, gas bubbling, and gravity. In addition, other related studies involving paper-based MFCs, cell stacking, and twin models are also introduced. Lastly, the future research perspective on MFC computational modeling is proposed, including potential structural innovations and modeling methods. This review paper shows the big puzzle of MFC modeling, the missing part of which is worthy of further study in the future.

关键词： Microfluidic fuel cell Membraneless fuel cell computational modeling Numerical simulation Cell structure Operational condition

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computational modeling of intraocular drug delivery supplied by porous implants

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DRUG DELIVERY AND TRANSLATIONAL RESEARCH 2021年第5期11卷 2134-2143页

作者： Abootorabi, Seyedalireza Tripathi, Abhimanyu Yu, Huidan Whitney Davila, Lilian P. Indiana Univ Purdue Univ Purdue Sch Engn & Technol Dept Mech & Energy Engn 723 West Michigan St Indianapolis IN 46202 USA Univ Calif Merced Sch Engn Dept Mat Sci & Engn 5200 N Lake Rd Merced CA 95343 USA

New and efficient drug delivery to the posterior part of the eye is a growing health necessity worldwide. Current treatment of eye diseases, such as age-related macular degeneration (AMD), relies on repeated intravitreal injections of drug-containing solutions. Such a drug delivery has major drawbacks including short drug life, significant medical service, and high medical cost. In this study, we explored a new approach to controlled drug delivery by introducing unique porous implants. Our computational modeling contained key physiological and anatomical traits. Incompressible flow in a porous media field, including the sclera, choroid, and retina layers, is governed by Darcy law and the time evolution of the drug concentration was solved via three convection-diffusion equations in the three layers, respectively. The computational model was validated by established results from independent studies and experimental data. Simulations of the IgG1 Fab drug delivery to the posterior eye were performed to evaluate the effectiveness of the porous implants for controlled delivery. Overall, our results indicate that drug therapeutic levels in the posterior eye sustain for eight weeks similarly to those using intravitreal injection. We first evaluated the effects of the porous implants on the drug delivery in the posterior layers. Subsequent simulations were carried out with varying porosity values in a porous episcleral implant. We found that the time evolution of drug concentration is distinctively correlated to drug source location and pore size. A correlation between porosity and fluid properties for selected porous implants was revealed for the first time in this study.

关键词： Drug delivery Posterior eye computational modeling Age-related macular degeneration Transcleral delivery

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computational modeling and Parametric Analysis of SMA Hybrid Composite Plates under Thermal Environment

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SENSORS 2023年第3期23卷 1344-1344页

作者： Li, Wei Stachiv, Ivo Czech Acad Sci Inst Phys Na Slovance 2 Prague 18200 Czech Republic

This paper presents a coupled thermoelastic finite element formulation for static and dynamic analysis of composite laminated plates with embedded active shape memory alloy (SMA) wires, which accounts for both the phase transformation and the nonlinearity effects of SMA wires. The equations of motion are obtained by using Hamilton's principle and first-order shear deformation theory (FSDT). Furthermore, based on Brinson's one-dimensional phase transformation constitutive law, a novel coupled thermoelastic finite element model that enables analysis of the SMA hybrid composite (SMAHC) plate is developed. The accuracy and efficiency of the developed computational model for analysis of SMAHC plates are reinforced by comparing theoretical predictions with data available from the literature. The results of the numerical examples also show the ability of the proposed model to predict the thermal-mechanical behavior of SMAHC plates in accordance with SMA's hysteresis behavior. In addition, based on the proposed model, the influence of temperature as well as SMA volume fraction, pre-strain value, boundary condition and layup sequence on the static bending and free vibration behavior of the SMAHC plates is investigated in detail. The results of parametric analysis show that the variations of both static deflection and natural frequency of the SMAHC plate over temperature exhibit a nonmonotonic behavior.

关键词： shape memory alloys SMA first-order deformation theory composite laminated structures FEM computational modeling

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computational modeling AND ENERGY ABSORPTION BEHAVIOR OF THIN-WALLED TUBES WITH THE KRESLING ORIGAMI PATTERN

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JOURNAL OF THE INTERNATIONAL ASSOCIATION FOR SHELL AND SPATIAL STRUCTURES 2021年第2期62卷 71-81页

作者： Li, Jiaqiang Chen, Yao Feng, Xiaodong Feng, Jian Sareh, Pooya Southeast Univ Sch Civil Engn Nanjing Peoples R China Southeast Univ Key Lab Concrete & Prestressed Concrete Struct Minist Educ Nanjing Peoples R China Southeast Univ Natl Prestress Engn Res Ctr Nanjing Peoples R China Shaoxing Univ Coll Civil Engn Shaoxing Peoples R China Zhejiang Univ Coll Civil Engn & Architecture Hangzhou Peoples R China Univ Liverpool Sch Engn Creat Design Engn Lab Cdel Dept Mech Mat & Aerosp Engn Liverpool Merseyside England

Origami structures have been widely used in various engineering fields due to their desirable properties such as geometric transformability and high specific energy absorption. Based on the Kresling origami pattern, this study proposes a type of thin-walled origami tube the structural configuration of which is found by a mixed-integer linear programming model. Using finite element analysis, a reasonable configuration of a thin-walled tube with the Kresling pattern is firstly analyzed. Then, the influences of different material properties, the rotation angle of the upper and lower sections of the tube unit, and cross-sectional shapes on the energy absorption behavior of the thin-walled tubes under axial compression are evaluated. The results show that the symmetric thin-walled tube with the Kresling pattern is a reasonable choice for energy absorption purposes. Compared with thin-walled prismatic tubes, the thin-walled tube with the Kresling pattern substantially reduces the initial peak force and the average crushing force, without significantly reducing its energy absorption capacity;moreover, it enters the plastic energy dissipation stage ahead of time, giving it a superior energy absorption performance. Besides, the material properties, rotation angle, and cross-sectional shape have considerable influences on its energy absorption performance. The results provide a basis for the application of the Kresling origami pattern in the design of thin-walled energy-absorbing structures.

关键词： origami tube Kresling pattern computational modeling structural configuration specific energy absorption

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Spatial distribution and computational modeling for mapping of tuberculosis in Pakistan

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JOURNAL OF PUBLIC HEALTH 2023年第2期45卷 338-346页

作者： Khaliq, Aasia Ashraf, Uzma Chaudhry, Muhammad N. Shahid, Saher Sajid, Muhammad A. Javed, Maryam Lahore Univ Management Sci LUMS Dept Life Sci Lahore Pakistan Lahore Sch Econ LSE Dept Environm Sci & Policy Lahore Pakistan Univ Punjab Sch Biol Sci SBS Lahore Pakistan Majan Univ Coll Fdn Dept Muscat 113 Oman

Background Tuberculosis (TB) like many other infectious diseases has a strong relationship with climatic parameters. Methods The present study has been carried out on the newly diagnosed sputum smear-positive pulmonary TB cases reported to National TB Control Program across Pakistan from 2007 to 2020. In this study, spatial and temporal distribution of the disease was observed through detailed district wise mapping and clustered regions were also identified. Potential risk factors associated with this disease depending upon population and climatic variables, i.e. temperature and precipitation were also identified. Results Nationwide, the incidence rate of TB was observed to be rising from 7.03% to 11.91% in the years 2007-2018, which then started to decline. However, a declining trend was observed after 2018-2020. The most populous provinces, Punjab and Sindh, have reported maximum number of cases and showed a temporal association as the climatic temperature of these two provinces is higher with comparison to other provinces. Machine learning algorithms Maxent, Support Vector Machine (SVM), Environmental Distance (ED) and Climate Space Model (CSM) predict high risk of the disease with14.02%, 24.75%, 34.81% and 43.89% area, respectively. Conclusion SVM has a higher significant probability of prediction in the diseased area with a 1.86 partial receiver-operating characteristics (ROC) value as compared with other models.

关键词： ANN computational modeling ecological niche modeling Geographical Information System spatial distribution tuberculosis

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computational modeling of the Effects of the Science Writing Heuristic on Student Critical Thinking in Science Using Machine Learning

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JOURNAL OF SCIENCE EDUCATION AND TECHNOLOGY 2021年第2期30卷 283-297页

作者： Lamb, Richard Hand, Brian Kavner, Amanda East Carolina Univ Neurocognit Sci Lab Coll Educ 128 Rivers Bldg Greenville NC 27858 USA

This study is intended to provide an example of computational modeling (CM) experiment using machine learning algorithms. Specific outcomes modeled in this study are the predicted influences associated with the Science Writing Heuristic (SWH) and associated with the completion of question items for the Cornell Critical Thinking Test. The Student Task and Cognition Model in this study uses cognitive data from a large-scale randomized control study. Results of the computational model experiment provide for the possibility to increase student success via targeted cognitive retraining of specific cognitive attributes via the SWH. This study also illustrates that computational modeling using machine learning algorithms (MLA) is a significant resource for testing educational interventions, informs specific hypotheses, and assists in the design and development of future research designs in science education research.

关键词： Machine learning computational modeling Cognition Critical thinking

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computational modeling toward full chain of polypropylene production: From molecular to industrial scale

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CHEMICAL ENGINEERING SCIENCE 2023年第1期269卷

作者： Yan, Wei-Cheng Dong, Tao Zhou, Yin-Ning Luo, Zheng-Hong Jiangsu Univ Sch Chem & Chem Engn Dept Chem Engn Zhenjiang 212013 Jiangsu Peoples R China Shanghai Jiao Tong Univ Sch Chem & Chem Engn Dept Chem Engn State Key Lab Met Matrix Composites Shanghai 200240 Peoples R China

Since polypropylene was synthesized in 1954, tremendous breakthroughs have been achieved in trans-ferring polypropylene from a discovery in the laboratory to an indispensable industrial product. One of the most difficult issue in polypropylene production is the precise control of the synthesis process to tai-lor the microstructure and the end-use properties, which needs deep understanding of the quantitative relationships among process, polymer structures and properties. However, semi-empirical correlations and experimental measurements are not able to capture the complex multi-scale characteristics of propylene polymerization process. In recent years, mathematical models have been intensively devel-oped to quantitatively link the microstructure of polymer to final macroscopic properties at multi-scales. This review provides an overview of progress in computational modeling of polypropylene pro-duction from the perspectives of science and engineering aspects covering synthesis, structure-property relationship, reactor design, processing, composites, and applications. The developed mathematical mod -els at various scales from molecular scale, particle scale and reactor scale toward plant scale throughout the full chain of production process are elaborated. The coupling strategies of models among different scales will be presented. In addition, model-based determination of quantitative relationships among process, apparatus, structure, and property for polypropylene are fully discussed including the recently developed emerging numerical approaches such as machine learning assisted modeling.(c) 2023 Elsevier Ltd. All rights reserved.

关键词： Polymerization engineering computational modeling Multi-scale modeling Polypropylene

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