Discover mechanical engineering最新文献

{"title":"Joint parameter estimation and abrupt change quantification with uncertainty quantification in high degree of freedom dynamical systems via an optimized adaptive unscented Kalman filter.","authors":"Esmaeil Ghorbani, Quentin Dollon, Frederick P Gosselin","doi":"10.1007/s44245-026-00298-5","DOIUrl":"10.1007/s44245-026-00298-5","url":null,"abstract":"<p><p>The Unscented Kalman Filter (UKF) represents a robust method for estimating latent states and parameters within specified nonlinear equations of dynamic systems under noisy sensor data. Nonetheless, adjusting the filter's hyperparameters (HP)s is essential for effective performance and poses difficulties, especially in systems with many parameters and states to identify, or when it is necessary for the filter to both detect and measure anomaly levels in parameters. Building on the authors previous research on introducing a physics-aware objective function to tune the UKF, this study advances the capabilities of the objective function to tune different adaptive variants of the UKF which facilitates virtual sensing, joint state-parameter estimation, damage quantification and uncertainty quantification under partial observation for systems with many degrees of freedom (DoF) as an open-ended question in structural health monitoring field. To validate the framework, a three DoF damped mass-spring system experiencing a sudden change in physical characteristics is used. Subsequently, the filter's precision in estimating parameters and states is evaluated using a ten DoF system with 40 states and unknown parameters, featuring sparsely placed sensors. Furthermore, the Lorenz attractor under partial observation is used as another case study to highlight why and how the physics-aware objective outperforms other commonly used data-driven objective functions. These results demonstrate the potential of the proposed framework for addressing challenging identification problems in dynamical systems such as tracking sudden changes and evaluating the uncertainties linked to both modeling and measurement, particularly those with limited and noisy sensor data.</p>","PeriodicalId":101405,"journal":{"name":"Discover mechanical engineering","volume":"5 1","pages":"147"},"PeriodicalIF":2.9,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13433503/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148674757","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}

{"title":"Modeling and validation of anisotropic thin-film deposition on cylindrical substrates for predictable resistance control in MEMS fabrication.","authors":"Aditya Tummala, Francesca Marturano, Giorgio Bonmassar","doi":"10.1007/s44245-026-00233-8","DOIUrl":"10.1007/s44245-026-00233-8","url":null,"abstract":"<p><p>Precise control of electrical properties in conductive micro-structures is essential for the performance and reliability of micro-electro-mechanical systems (MEMS). However, the nature of anisotropic physical vapor deposition (PVD), such as electron-beam or thermal evaporation on curved or wire-like substrates, complicates the prediction of thin-film morphology and resulting electrical properties. This study develops and validates a geometrically explicit deposition model describing film growth on cylindrical substrates using a generalized pseudo-Lambertian cosine emission profile. Analytical expressions for local film thickness are derived as functions of deposition time, substrate geometry, and source collimation and characterized by a sensitivity analysis. Monte Carlo simulations confirm that the model accurately reproduces the deposition profile observed with simulated data ([Formula: see text]). A closed-form expression for resistance as a function of deposition parameters was also derived, integrating the Fuchs-Sondheimer and Mayadas-Shatzkes (FS-MS) frameworks to account for thin-film electron scattering and grain-boundary effects. Experimental validation was performed via electron-beam evaporation of gold onto cylindrical glass-core wires, with measured resistances spanning [Formula: see text] to [Formula: see text] across films 70 to 3000 nm thick. The FS-MS predicted resistances exhibited a Pearson correlation of [Formula: see text] ([Formula: see text]) with empirical measurements, confirming the model's predictive accuracy. Additionally, this study develops an empirical mathematical model that captures the anisotropic behavior of PVD deposition on cylindrical surfaces, offering a simulation framework that generalizes conventional planar thin-film modeling to complex, three-dimensional microfabrication topographies. The model enables predictive control of thin-film resistivity in MEMS and bio-MEMS structures and, by enabling precise conformal PVD metallization of polymer-based wires with minimal precious-metal loading, offers a pathway to substantially reduce the manufacturing cost of active medical implants that traditionally rely on bulk platinum-iridium conductors. All model and simulation materials have been made available and can be found in Supplementary Materials (Sec. 3).</p><p><strong>Supplementary information: </strong>The online version contains supplementary material available at 10.1007/s44245-026-00233-8.</p>","PeriodicalId":101405,"journal":{"name":"Discover mechanical engineering","volume":"5 1","pages":"74"},"PeriodicalIF":2.9,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13133202/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147825591","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}

{"title":"Hydrodynamic lubrication effects in textured PEEK surfaces for friction reduction.","authors":"Christopher W Harris, Omid Doustdar, Arvin Taghizadeh Tabrizi, Ali M Al-Qahtani, Amir M Hajiyavand, Karl D Dearn","doi":"10.1007/s44245-025-00130-6","DOIUrl":"10.1007/s44245-025-00130-6","url":null,"abstract":"<p><p>The tribology of dimple-shaped textures is investigated within a reciprocating polymeric sliding couple of Invibio poly-ether-ether-ketone (grade 450G). A novel theoretical model was developed for this aim, describing hydrodynamic pressure and frictional force due to surface modifications. Experiments show reduced friction across all textures compared to un-textured surfaces. The parameters of texture depth (5-20 µm) and diameter (50-200 µm) were isolated to analyse the effect of each independently. The diameter showed good agreement with the model; however, depth showed variation at the extremities of the parameters examined. The experimental friction force captured over a single stroke was compared to the instantaneous theoretical friction force, and good agreement was found in the form of the friction trace within the hydrodynamic region of a reciprocating stroke. The texture parameter combination of 50 µm diameter and 20 µm depth showed the most significant reduction in friction at 48.7%.</p><p><strong>Graphical abstract: </strong></p>","PeriodicalId":101405,"journal":{"name":"Discover mechanical engineering","volume":"4 1","pages":"41"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12479708/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145208753","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}

{"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":"<p><p>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 <i>direct</i>-from laser settings to material properties, and <i>inverse</i>-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.</p><p><strong>Supplementary information: </strong>The online version contains supplementary material available at 10.1007/s44245-025-00094-7.</p>","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}

{"title":"Creating data-driven products and services in industry 4.0: a case study on companies in the German machine and tool industry","authors":"E. Permin, Lina Castillo","doi":"10.1007/s44245-024-00039-6","DOIUrl":"https://doi.org/10.1007/s44245-024-00039-6","url":null,"abstract":"","PeriodicalId":101405,"journal":{"name":"Discover mechanical engineering","volume":"8 23","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140713042","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}

{"title":"Optimisation-based strategies to identification of material parameters of hygro-thermo-mechanical problems","authors":"M. Vaz, P. Zdanski","doi":"10.1007/s44245-024-00038-7","DOIUrl":"https://doi.org/10.1007/s44245-024-00038-7","url":null,"abstract":"","PeriodicalId":101405,"journal":{"name":"Discover mechanical engineering","volume":"328 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140719657","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}

{"title":"Online tracking of dynamically time-varying inertia using an enhanced SDFT-based estimation methodology","authors":"D. Ceulemans, Foeke Vanbecelaere, Nick Van Oosterwyck, Jasper De Viaene, Jan Steckel, S. Derammelaere","doi":"10.1007/s44245-024-00036-9","DOIUrl":"https://doi.org/10.1007/s44245-024-00036-9","url":null,"abstract":"","PeriodicalId":101405,"journal":{"name":"Discover mechanical engineering","volume":"26 11","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140726989","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}

{"title":"APRTC: advanced precise rapid thermal cycling in blow molding by applying fuzzy controller on thermoelectric devices for cooling and heating applications","authors":"Alireza Safaryazdi, Ali Ghaffari","doi":"10.1007/s44245-024-00035-w","DOIUrl":"https://doi.org/10.1007/s44245-024-00035-w","url":null,"abstract":"","PeriodicalId":101405,"journal":{"name":"Discover mechanical engineering","volume":"29 7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140414062","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}

{"title":"The chemical impact of oil fluids in the morphology and thermal properties of the polyamide 11 used in flexible lines","authors":"F. Dias, A. G. Veiga, A. P. A. C. P. Gomes, Maria Luiza M. Rocco, M. F. da Costa","doi":"10.1007/s44245-024-00032-z","DOIUrl":"https://doi.org/10.1007/s44245-024-00032-z","url":null,"abstract":"","PeriodicalId":101405,"journal":{"name":"Discover mechanical engineering","volume":"30 1-2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140490378","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}

{"title":"Enhancing mechanical performance of biodegradable automotive composites with EPO and graphene","authors":"N. Jiyas, Indu Sasidharan, K. B. Kumar","doi":"10.1007/s44245-024-00033-y","DOIUrl":"https://doi.org/10.1007/s44245-024-00033-y","url":null,"abstract":"","PeriodicalId":101405,"journal":{"name":"Discover mechanical engineering","volume":"79 10","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139606216","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}