Engineered Science最新文献_第2页

Thermal Performance Improvement of Forced-Air Cooling System Combined with Liquid Spray for Densely Packed Batteries of Electric Vehicle 电动汽车密装电池强制风冷结合液体喷雾系统的热性能改善

Engineered Science Pub Date : 2023-01-01 DOI: 10.30919/es886

P. Saechan, I. Dhuchakallaya, F. A. M. Saat

引用次数: 4

Overview of Mechanical Characterization of Bone using Nanoindentation Technique and Its Applications 纳米压痕技术在骨力学表征中的应用综述

Engineered Science Pub Date : 2023-01-01 DOI: 10.30919/es8d820

V. Managuli, Yashwant Sing Bothra, S. S, P. Gaur, Prasanna Lokadolalu Chandracharya

引用次数: 2

On the Development of a Passive Shape Memory Alloy- Based Cooling System – Part II: Design Justification 基于被动形状记忆合金的冷却系统的研制——第二部分:设计论证

Engineered Science Pub Date : 2023-01-01 DOI: 10.30919/es928

A. Riccio, A. Sellitto, A. Caraviello, Ugo Riccio, A. Torluccio, Luca Pacini, R. Mohr

引用次数: 0

The effects of Fe addition for enhanced thermoelectric performance in p-type CuAlO2 添加铁对p型CuAlO2热电性能的影响

Engineered Science Pub Date : 2023-01-01 DOI: 10.30919/es8d822

Yining Feng, J. Joo, Na Lu

引用次数: 4

Office Building Envelope Design Optimization by Modified Competitive Search Algorithm for Energy Saving 基于改进竞争搜索算法的办公楼围护结构节能优化

Engineered Science Pub Date : 2023-01-01 DOI: 10.30919/es953

T. Jearsiripongkul, M. Karbasforoushha, M. Khajehzadeh, S. Keawsawasvong, C. Thongchom

{"title":"Office Building Envelope Design Optimization by Modified Competitive Search Algorithm for Energy Saving","authors":"T. Jearsiripongkul, M. Karbasforoushha, M. Khajehzadeh, S. Keawsawasvong, C. Thongchom","doi":"10.30919/es953","DOIUrl":"https://doi.org/10.30919/es953","url":null,"abstract":"35 Building envelopes for green buildings should be designed with low energy consumption and low 36 construction costs. A modified competitive search algorithm is used for the optimization of the office 37 building design due to the long runtime of simulation tools such as EnergyPlus and TRNSYS. For the 38 minimization of the cost of construction at the needed energy conservation, the envelope configuration, 39 such as window numbers, walls, glass curtain walls, etc., is optimized. Comparing the proposed algorithm 40 with some others, the cost decreased for the optimum design of the building structure at the needed energy 41 load value. The number of iterations is also reduced by the proposed approach. Moreover, the overall area 42 of the window is increased, which has resulted in the natural ventilation being more proper. Since the ratio 43 of the glass curtain wall is increased, it can result that the indoor lighting being better. Per unit area of the 44 envelope, the value of the energy load is smaller and the total cost is lower for the proposed method in 45 comparison with other algorithms, considering that the opening rate of the window is much the same. The 46 total cost decreased by 37.1% in comparison with the initial design. It can be observed that the MCSA is 47 more efficient than the other compared methods in energy saving of the building in this paper. 48","PeriodicalId":36059,"journal":{"name":"Engineered Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87576014","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Prediction of Undrained Lateral Capacity of Free-Head Rectangular Pile in Clay Using Finite Element Limit Analysis and Artificial Neural Network 基于有限元极限分析和人工神经网络的粘土中自由承台矩形桩不排水侧承载力预测

Engineered Science Pub Date : 2023-01-01 DOI: 10.30919/es923

Suttikarn Panomchaivath, Wittaya Jitchaijaroen, Rungkhun Banyong, S. Keawsawasvong, Sayan Sirimontree, P. Jamsawang

{"title":"Prediction of Undrained Lateral Capacity of Free-Head Rectangular Pile in Clay Using Finite Element Limit Analysis and Artificial Neural Network","authors":"Suttikarn Panomchaivath, Wittaya Jitchaijaroen, Rungkhun Banyong, S. Keawsawasvong, Sayan Sirimontree, P. Jamsawang","doi":"10.30919/es923","DOIUrl":"https://doi.org/10.30919/es923","url":null,"abstract":": This paper is dedicated to investigating the undrained lateral capacity of rigid free-head rectangular/square piles in cohesive soil. The study utilizes the three-dimensional Finite Element Limit Analysis (FELA) framework to analyze and assess the pile's ability to withstand lateral loads. Both upper bound (UB) and lower bound (LB) FELA techniques are employed in the analysis process. The findings emphasize the importance of understanding the behavior and failure mechanisms exhibited by the surrounding soil around the pile. The analysis employs dimensionless approaches to obtain the normalized load factor, which represents the outcomes of the solution. The results obtained from the analysis demonstrate that the lateral load capacity of the soil is influenced by several key factors, including the pile's length-width ratio, the height-width ratio, the eccentricity of the lateral load, and the overburden stress where the discussion regarding the effects of all parameters is provided in the manuscript. The study also delves into the examination and understanding of the failure mechanisms exhibited by the soil in the context of lateral loaded piles. Based on the numerical outcome, the artificial neural network (ANN), which is one of soft-computing techniques, is utilized to establish a surrogate model for predicting the lateral capacity of rectangular piles. By considering these factors in the design process, engineers can make informed decisions that effectively optimize pile performance and ensure the long-term stability of structures.","PeriodicalId":36059,"journal":{"name":"Engineered Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88539076","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Modelling and Prediction of Machining Forces During End Milling of Glass Fibre Reinforced Polymer Composites Using Regression Analysis and Artificial Neural Networks 基于回归分析和人工神经网络的玻璃纤维增强聚合物复合材料立铣削加工力建模与预测

Engineered Science Pub Date : 2023-01-01 DOI: 10.30919/es8d869

J. M P, B. Harinesh, U. Arunachalam

引用次数: 2

Flexible Carbon Nanotubes/Polystyrene Membranous Composites Toward Ultraweakly and Frequency-Stable Negative Permittivity at kHz Region 柔性碳纳米管/聚苯乙烯膜复合材料在kHz区域的超弱和频率稳定的负介电常数

Engineered Science Pub Date : 2023-01-01 DOI: 10.30919/es920

Xinxue Tang, Zheng Zhang, D. J. P. Kumar, Yunpeng Qu, Peitao Xie, Gemeng Liang, Jiaqi Wang, Qingqing Yang, X. Qi, Zhanhu Guo

引用次数: 6

Machine-learning-based, online estimation of ceramic’s microstructure upon the laser spot brightness during laser sintering 基于机器学习的激光烧结过程中光斑亮度对陶瓷微观结构的在线估计

Engineered Science Pub Date : 2023-01-01 DOI: 10.30919/es8d855

Jianan Tang, Siddhartha Sarkar, Hua Huang, Xiao Geng, J. Tong, Lionel Vargas-Gonzalez, Nicholas Ku, Dongsheng Li, Hai Xiao, Fei Peng