Discover mechanical engineering最新文献

Data-driven approaches for predicting mechanical properties and determining processing parameters of selective laser sintered nylon-12 components. 选择性激光烧结尼龙-12构件力学性能预测和工艺参数确定的数据驱动方法。

Discover mechanical engineering Pub Date : 2025-01-01 Epub Date: 2025-03-22 DOI: 10.1007/s44245-025-00094-7

Ruixuan Tu, Candice Majewski, Inna Gitman

{"title":"Data-driven approaches for predicting mechanical properties and determining processing parameters of selective laser sintered nylon-12 components.","authors":"Ruixuan Tu, Candice Majewski, Inna Gitman","doi":"10.1007/s44245-025-00094-7","DOIUrl":"10.1007/s44245-025-00094-7","url":null,"abstract":"In order to allow engineers to make decisions regarding laser settings in selective laser sintering and predict the mechanical properties of materials, conventional material models could provide accurate solutions and recommendations, however, they are potentially expensive and time-consuming. Thus, a number of computational data-driven methodologies have been introduced in this article, as alternatives, to formulate cross-correlations between the processing parameters and mechanical properties of selective laser sintered (SLS) nylon-12 components. Proposed in this article direct-from laser settings to material properties, and inverse-from desired material properties to laser settings, two estimation frameworks have provided accurate estimation results. The accuracy of three proposed data-driven methodologies: fuzzy inference system (FIS), artificial neural networks (ANN) and adaptive neural fuzzy inference system (ANFIS), have been compared and thoroughly analysed, with FIS being the most accurate solution.Supplementary information: The online version contains supplementary material available at 10.1007/s44245-025-00094-7.","PeriodicalId":101405,"journal":{"name":"Discover mechanical engineering","volume":"4 1","pages":"10"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11929718/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143702609","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Creating data-driven products and services in industry 4.0: a case study on companies in the German machine and tool industry 在工业 4.0 中创建数据驱动型产品和服务：德国机械和工具行业企业案例研究

Discover mechanical engineering Pub Date : 2024-04-11 DOI: 10.1007/s44245-024-00039-6

E. Permin, Lina Castillo

引用次数: 0

Optimisation-based strategies to identification of material parameters of hygro-thermo-mechanical problems 基于优化策略的湿热机械问题材料参数识别方法

Discover mechanical engineering Pub Date : 2024-04-10 DOI: 10.1007/s44245-024-00038-7

M. Vaz, P. Zdanski

引用次数: 0

Online tracking of dynamically time-varying inertia using an enhanced SDFT-based estimation methodology 使用基于 SDFT 的增强型估计方法在线跟踪动态时变惯性

Discover mechanical engineering Pub Date : 2024-04-09 DOI: 10.1007/s44245-024-00036-9

D. Ceulemans, Foeke Vanbecelaere, Nick Van Oosterwyck, Jasper De Viaene, Jan Steckel, S. Derammelaere

引用次数: 0

APRTC: advanced precise rapid thermal cycling in blow molding by applying fuzzy controller on thermoelectric devices for cooling and heating applications APRTC：通过在用于冷却和加热的热电设备上应用模糊控制器，在吹塑成型中实现先进的精确快速热循环

Discover mechanical engineering Pub Date : 2024-02-29 DOI: 10.1007/s44245-024-00035-w

Alireza Safaryazdi, Ali Ghaffari

引用次数: 0

The chemical impact of oil fluids in the morphology and thermal properties of the polyamide 11 used in flexible lines 油液对柔性生产线所用聚酰胺 11 的形态和热性能的化学影响

Discover mechanical engineering Pub Date : 2024-01-29 DOI: 10.1007/s44245-024-00032-z

F. Dias, A. G. Veiga, A. P. A. C. P. Gomes, Maria Luiza M. Rocco, M. F. da Costa

引用次数: 0

Enhancing mechanical performance of biodegradable automotive composites with EPO and graphene 用 EPO 和石墨烯提高可生物降解汽车复合材料的机械性能

Discover mechanical engineering Pub Date : 2024-01-22 DOI: 10.1007/s44245-024-00033-y

N. Jiyas, Indu Sasidharan, K. B. Kumar

引用次数: 0

Finite element investigation of cutting speed effects on the machining of Ti6Al4V alloy 切削速度对 Ti6Al4V 合金加工影响的有限元研究

Discover mechanical engineering Pub Date : 2024-01-16 DOI: 10.1007/s44245-024-00031-0

Surinder Pal, Xavier Velay, Waqas Saleem

引用次数: 0

Development and performance assessment of a new opensource Bayesian inference R platform for building energy model calibration. 用于建筑能源模型校准的新开源贝叶斯推理R平台的开发和性能评估。

Discover mechanical engineering Pub Date : 2023-01-01 Epub Date: 2023-10-31 DOI: 10.1007/s44245-023-00027-2

Danlin Hou, Dongxue Zhan, Liangzhu Wang, Ibrahim Galal Hassan, Nurettin Sezer

{"title":"Development and performance assessment of a new opensource Bayesian inference R platform for building energy model calibration.","authors":"Danlin Hou, Dongxue Zhan, Liangzhu Wang, Ibrahim Galal Hassan, Nurettin Sezer","doi":"10.1007/s44245-023-00027-2","DOIUrl":"https://doi.org/10.1007/s44245-023-00027-2","url":null,"abstract":"Many factors contribute to the inherent uncertainty of energy consumption modeling in buildings. It is essential to perform a calibration and sensitivity analysis in order to manage these uncertainties. Despite the availability of several calibration methods, they are often deterministic and lack quantified uncertainties. Moreover, the selection of parameters in building energy modeling for calibration depends on the user's experience. Therefore, a more rigorous selection process is required. This study developed a new automated Bayesian Inference calibration platform running as an R package. A sensitivity analysis module and a Bayesian inference module determine the calibration parameters and uncertainties, respectively. The Meta-model module is developed to replace the building energy model for the Markov Chain Monte Carlo process to save computing time. The proposed platform is successfully demonstrated on a synthetic high-rise office building and a real high-rise residential building in a hot and arid climate. The relationship between the number of calibration parameters, calibration performance, and the accuracy of the Meta-model is further discussed. The developed calibration platform in this study proved to have clear advantages over the existing platforms, with the ability to reasonably estimate building energy performance in a short computing time.","PeriodicalId":101405,"journal":{"name":"Discover mechanical engineering","volume":"2 1","pages":"19"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10627152/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71490971","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0