This paper reports a unified analogy-based computation methodology, together with a concept of multifield, multifunctional sensing, from elasticity to electromagnetic-chemical-thermal fields, via utilizing the similarities of mechanical-electromagnetic-chemical-thermal (MEMCT) field variables, governing equations, and the material properties pertaining to each individual field. Two equivalences are systemized, which are the field-formulation equivalence and surface-value equivalence. Due to similarity, a number of thermal, electromagnetic, or chemical solutions can be obtained from the direct degeneration of existing mechanical solutions by making specified equivalences of 2G↔k0↔ϖ0↔μ0↔β0 with G for shear modulus, k0 for heat conductivity, ϖ0 for dielectric permittivity, μ0 for magnetic permeability, and β0 for chemical diffusivity, as well as by setting Poisson’s ratio ν → 0.5. These specified equivalences enable quick solutions to other fields directly from mechanics formulations, such as those in the forms of the Galerkin vectors and Papkovich-Neuber potentials, and field coupling, by means of analogy. Several examples are given, one is used to demonstrate that the field solutions of a layered half-space with imperfect thermal, electromagnetic, or chemical interfaces can be readily obtained from the elastic solutions involving interfacial imperfections via the obtained formulation equivalence. A set of simple equations are derived to relate surface behaviors of different fields via the obtained surface-value equivalence, on which a concept of multifield sensing is proposed.
{"title":"A Unified Analogy-Based Computation Methodology From Elasticity to Electromagnetic-Chemical-Thermal Fields and a Concept of Multifield Sensing","authors":"Xin Zhang, Q. Wang","doi":"10.1115/1.4053910","DOIUrl":"https://doi.org/10.1115/1.4053910","url":null,"abstract":"\u0000 This paper reports a unified analogy-based computation methodology, together with a concept of multifield, multifunctional sensing, from elasticity to electromagnetic-chemical-thermal fields, via utilizing the similarities of mechanical-electromagnetic-chemical-thermal (MEMCT) field variables, governing equations, and the material properties pertaining to each individual field. Two equivalences are systemized, which are the field-formulation equivalence and surface-value equivalence. Due to similarity, a number of thermal, electromagnetic, or chemical solutions can be obtained from the direct degeneration of existing mechanical solutions by making specified equivalences of 2G↔k0↔ϖ0↔μ0↔β0 with G for shear modulus, k0 for heat conductivity, ϖ0 for dielectric permittivity, μ0 for magnetic permeability, and β0 for chemical diffusivity, as well as by setting Poisson’s ratio ν → 0.5. These specified equivalences enable quick solutions to other fields directly from mechanics formulations, such as those in the forms of the Galerkin vectors and Papkovich-Neuber potentials, and field coupling, by means of analogy. Several examples are given, one is used to demonstrate that the field solutions of a layered half-space with imperfect thermal, electromagnetic, or chemical interfaces can be readily obtained from the elastic solutions involving interfacial imperfections via the obtained formulation equivalence. A set of simple equations are derived to relate surface behaviors of different fields via the obtained surface-value equivalence, on which a concept of multifield sensing is proposed.","PeriodicalId":8652,"journal":{"name":"ASME Open Journal of Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79742498","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}
Modern magnetic nanomaterials are increasingly embracing new technologies including smart coatings, intelligent lubricants, and functional working fluids in energy systems. Motivated by studying the manufacturing magnetofluid dynamics of electroconductive viscous nanofluids, in this work, we analyzed the magnetohydrodynamics (MHD) convection flow and heat transfer of an incompressible viscous nanofluid containing carbon nanotubes (CNTs) past a stretching sheet. Magnetic induction effects are included. Similarity solutions are derived where possible in addition to dual branch solutions. Both single-wall carbon nanotubes (SWCNTs) and multi-wall carbon nanotubes (MWCNTs) are considered taking water and kerosene oil as base fluids. The governing continuity, momentum, magnetic induction, and heat conservation partial differential equations are converted to coupled, nonlinear systems of ordinary differential equations via similarity transformations. The emerging control parameters are shown to be Prandtl number (Pr), nanoparticle volume fraction parameter (φ), inverse magnetic Prandtl number (λ), magnetic body force parameter (β) and stretching rate parameter (A), and the type of carbon nanotube. Numerical solutions to the ordinary differential boundary value problem are conducted with the efficient bvp4c solver in matlab. Validation with earlier studies is included. Computations of reduced skin friction and reduced wall heat transfer rate (Nusselt number) are also comprised in order to identify the critical parameter values for the existence of dual solutions (upper and lower branch) for velocity, temperature, and induced magnetic field functions. Dual solutions are shown to exist for some cases studied. The simulations indicate that when the stretching rate ratio parameter is less than 1, SWCNT nanofluids exhibit higher velocity than MWCNT nanofluids with increasing magnetic parameters for water- and kerosene-oil-based CNT nanofluids. Generally, SWCNT nanofluids achieve enhanced heat transfer performance compared to MWCNT nanofluids. Water-based CNT nanofluids also attain greater flow acceleration compared with kerosene-oil-based CNT nanofluids.
{"title":"Duel Solutions in Hiemenz Flow of an Electro-Conductive Viscous Nanofluid Containing Elliptic Single-/Multi-Wall Carbon Nanotubes With Magnetic Induction Effects","authors":"M. Ferdows, Tahia Tazin, O. Bég, T. Bég","doi":"10.1115/1.4055278","DOIUrl":"https://doi.org/10.1115/1.4055278","url":null,"abstract":"Modern magnetic nanomaterials are increasingly embracing new technologies including smart coatings, intelligent lubricants, and functional working fluids in energy systems. Motivated by studying the manufacturing magnetofluid dynamics of electroconductive viscous nanofluids, in this work, we analyzed the magnetohydrodynamics (MHD) convection flow and heat transfer of an incompressible viscous nanofluid containing carbon nanotubes (CNTs) past a stretching sheet. Magnetic induction effects are included. Similarity solutions are derived where possible in addition to dual branch solutions. Both single-wall carbon nanotubes (SWCNTs) and multi-wall carbon nanotubes (MWCNTs) are considered taking water and kerosene oil as base fluids. The governing continuity, momentum, magnetic induction, and heat conservation partial differential equations are converted to coupled, nonlinear systems of ordinary differential equations via similarity transformations. The emerging control parameters are shown to be Prandtl number (Pr), nanoparticle volume fraction parameter (φ), inverse magnetic Prandtl number (λ), magnetic body force parameter (β) and stretching rate parameter (A), and the type of carbon nanotube. Numerical solutions to the ordinary differential boundary value problem are conducted with the efficient bvp4c solver in matlab. Validation with earlier studies is included. Computations of reduced skin friction and reduced wall heat transfer rate (Nusselt number) are also comprised in order to identify the critical parameter values for the existence of dual solutions (upper and lower branch) for velocity, temperature, and induced magnetic field functions. Dual solutions are shown to exist for some cases studied. The simulations indicate that when the stretching rate ratio parameter is less than 1, SWCNT nanofluids exhibit higher velocity than MWCNT nanofluids with increasing magnetic parameters for water- and kerosene-oil-based CNT nanofluids. Generally, SWCNT nanofluids achieve enhanced heat transfer performance compared to MWCNT nanofluids. Water-based CNT nanofluids also attain greater flow acceleration compared with kerosene-oil-based CNT nanofluids.","PeriodicalId":8652,"journal":{"name":"ASME Open Journal of Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72859564","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}
High-fidelity multidisciplinary design optimization (MDO) promises rigorous balancing of the multidisciplinary trade-offs inherent to aircraft wings. However, collaborations between academia and industry rarely put MDO to the test on practical design problems. In this work, MDO is applied to the design of a regional jet wing to minimize fuel burn. High-fidelity aerostructural analysis is used to model the wing and capture trade-offs between structural weight and aerodynamic performance. A novel approach is used to calculate fuel burn for climb and descent using a low-fidelity model, improving the relevancy of the optimization results for short-haul missions. A wing-only geometry is used to explore the design space and generate a series of Pareto fronts for different geometric parametrizations. Finally, an aerostructural optimization is conducted with a complete wing-body-tail geometry of an Embraer regional jet. The optimizer increases the wingspan and decreases the sweep of the original wing to achieve a 3.6% decrease in fuel burn.
{"title":"Aerostructural Wing Optimization of a Regional Jet Considering Mission Fuel Burn","authors":"Nicolas Bons, J. Martins, F. Odaguil, A. Cuco","doi":"10.1115/1.4055630","DOIUrl":"https://doi.org/10.1115/1.4055630","url":null,"abstract":"High-fidelity multidisciplinary design optimization (MDO) promises rigorous balancing of the multidisciplinary trade-offs inherent to aircraft wings. However, collaborations between academia and industry rarely put MDO to the test on practical design problems. In this work, MDO is applied to the design of a regional jet wing to minimize fuel burn. High-fidelity aerostructural analysis is used to model the wing and capture trade-offs between structural weight and aerodynamic performance. A novel approach is used to calculate fuel burn for climb and descent using a low-fidelity model, improving the relevancy of the optimization results for short-haul missions. A wing-only geometry is used to explore the design space and generate a series of Pareto fronts for different geometric parametrizations. Finally, an aerostructural optimization is conducted with a complete wing-body-tail geometry of an Embraer regional jet. The optimizer increases the wingspan and decreases the sweep of the original wing to achieve a 3.6% decrease in fuel burn.","PeriodicalId":8652,"journal":{"name":"ASME Open Journal of Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89769724","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}
Marcos Zambrano, M. Vergara, José Luis Burgos, Jhonattan Trejo
Even though string musical instruments made of synthetic materials such as carbon fiber reinforced polymer (CFRP) have respected acoustic performance, but a short manufacturing cycle and low product cost, they do not become an alternative to replace high-quality string instruments made of sound woods. For CFRP violins to approach high acoustic performance wood violins, they must exhibit approximately the same bending stiffness. The CFRP is denser, stiffer, and isotropic compared to the orthotropy of wood. In this work, the acoustic behavior of CFRP violins with the same geometry as high-quality wood violins was compared. A numerical modal study was developed by finite element simulations, comparing two violin top plates, one in CFRP and the other in Picea abies (PA) wood. The simulations were developed in the ansys mechanical software, using the Block Lanczos method with a mesh of 38,216 finite volumes, finding modal patterns for both the CFRP model and the PA model. Mathematical models based on solid state physics such as effective masses and maximum vibration amplitude between models were outlined. Both models were validated against experimental studies developed by other authors. It is concluded that for instruments with the same geometry, a sonorous superiority of the wood over the CFRP was evidenced, which leads to further reinforce the unique, enigmatic, and mythical behavior of violins made of sonorous woods such as the Stradivarius violins.
{"title":"Comparison of the Acoustic Performance of Wooden Violins and Carbon Fiber Reinforced Polymer Violins Through a Modal Study by Finite Elements Method and Effective Masses","authors":"Marcos Zambrano, M. Vergara, José Luis Burgos, Jhonattan Trejo","doi":"10.1115/1.4055192","DOIUrl":"https://doi.org/10.1115/1.4055192","url":null,"abstract":"\u0000 Even though string musical instruments made of synthetic materials such as carbon fiber reinforced polymer (CFRP) have respected acoustic performance, but a short manufacturing cycle and low product cost, they do not become an alternative to replace high-quality string instruments made of sound woods. For CFRP violins to approach high acoustic performance wood violins, they must exhibit approximately the same bending stiffness. The CFRP is denser, stiffer, and isotropic compared to the orthotropy of wood. In this work, the acoustic behavior of CFRP violins with the same geometry as high-quality wood violins was compared. A numerical modal study was developed by finite element simulations, comparing two violin top plates, one in CFRP and the other in Picea abies (PA) wood. The simulations were developed in the ansys mechanical software, using the Block Lanczos method with a mesh of 38,216 finite volumes, finding modal patterns for both the CFRP model and the PA model. Mathematical models based on solid state physics such as effective masses and maximum vibration amplitude between models were outlined. Both models were validated against experimental studies developed by other authors. It is concluded that for instruments with the same geometry, a sonorous superiority of the wood over the CFRP was evidenced, which leads to further reinforce the unique, enigmatic, and mythical behavior of violins made of sonorous woods such as the Stradivarius violins.","PeriodicalId":8652,"journal":{"name":"ASME Open Journal of Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74238451","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}
From the use of a pinhole camera placed under a water tank, which was proposed almost 100 years ago, to the application of modern digital cameras mounted with sophisticated fisheye lenses, acquisition methods for capturing hemispherical photographs undergone vigorous research and development. Over the past few decades, such photographs have been extensively used in evaluating energy and environmental aspects in urban contexts. In this review article, the advantages, limitations, and challenges of the various methods of acquiring photographs are described and compared. This involves both the devices themselves and the software tools. Several methods of direct acquisition of hemispheric photographs involving digital cameras, smartphones, the use of drones for photographs at elevations, and the application of thermal imaging technologies are discussed in detail. Indirect methods for generating hemispheric photographs are also discussed, highlighting the use of images from applications such as Google Street View (GSV). Based on a review of technical literature, several applications in energy and the environment that use information from hemispheric photographs as an analysis tool are presented and discussed. Among others, the following are discussed: the quantification of solar radiation potential; the assessment of indicators of local temperature and level of thermal comfort for pedestrians in urban areas; indoor and outdoor daylighting; and air and light pollution. Finally, several potential future research directions for the use of hemispherical photographs in built environments are discussed. These include advances in image processing, use of thermal imaging, solar potential assessment of solar-powered vehicles, applications of drone-mounted hemispherical photography, and fisheye videos.
{"title":"Hemispherical Photographs: A Review of Acquisition Methods and Applications in the Context of Urban Energy and Environment Assessments","authors":"N. Rehman","doi":"10.1115/1.4053418","DOIUrl":"https://doi.org/10.1115/1.4053418","url":null,"abstract":"\u0000 From the use of a pinhole camera placed under a water tank, which was proposed almost 100 years ago, to the application of modern digital cameras mounted with sophisticated fisheye lenses, acquisition methods for capturing hemispherical photographs undergone vigorous research and development. Over the past few decades, such photographs have been extensively used in evaluating energy and environmental aspects in urban contexts. In this review article, the advantages, limitations, and challenges of the various methods of acquiring photographs are described and compared. This involves both the devices themselves and the software tools. Several methods of direct acquisition of hemispheric photographs involving digital cameras, smartphones, the use of drones for photographs at elevations, and the application of thermal imaging technologies are discussed in detail. Indirect methods for generating hemispheric photographs are also discussed, highlighting the use of images from applications such as Google Street View (GSV). Based on a review of technical literature, several applications in energy and the environment that use information from hemispheric photographs as an analysis tool are presented and discussed. Among others, the following are discussed: the quantification of solar radiation potential; the assessment of indicators of local temperature and level of thermal comfort for pedestrians in urban areas; indoor and outdoor daylighting; and air and light pollution. Finally, several potential future research directions for the use of hemispherical photographs in built environments are discussed. These include advances in image processing, use of thermal imaging, solar potential assessment of solar-powered vehicles, applications of drone-mounted hemispherical photography, and fisheye videos.","PeriodicalId":8652,"journal":{"name":"ASME Open Journal of Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81198181","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}
Concentrated solar power presents immense scope for the deployment of small-scale units focusing on diverse applications, including process heat and rural on/off-grid applications. This paper presents the analysis of solar irradiance variation on heat flux and temperature distribution at the dish concentrator receiver. A solar dish concentrator with a 2.8-m aperture diameter and a 0.4-m depth was used for this analysis. The solar ray intersection between a dish concentrator and its receiver, along with the heat flux distribution prediction, was carried out using SolTrace. The effect of flux intensity variation on temperature distribution at the receiver was investigated using comsol multiphysics. The optical analysis considered 10,000 rays, and 91.65% of them were observed to reach the surface of the receiver. For 1000 W/m2 of beam solar radiation, a peak heat flux and maximum temperature at the concentrator’s focal plane are found to be 32.4 MW/m2 and 923 K, respectively. The validation had been done using previously reported results in the literature to verify the correctness of the present simulation results. The effect of beam solar radiation variation on heat flux intensity and the temperature distribution revealed that both heat flux and temperature increase with increasing solar radiation, which points out the influence of design and operating conditions. Apart from PillBox and Gaussian distributions, the effect of slope and specularity errors was characterized, suggesting a greater sensitivity to the former than the latter.
{"title":"Analysis of Solar Irradiance Variation on Heat Flux and Temperature Distribution for a Dish Concentrator Receiver","authors":"E. Bekele, V. Ancha, Tarekegn Limore Binchebo","doi":"10.1115/1.4053963","DOIUrl":"https://doi.org/10.1115/1.4053963","url":null,"abstract":"\u0000 Concentrated solar power presents immense scope for the deployment of small-scale units focusing on diverse applications, including process heat and rural on/off-grid applications. This paper presents the analysis of solar irradiance variation on heat flux and temperature distribution at the dish concentrator receiver. A solar dish concentrator with a 2.8-m aperture diameter and a 0.4-m depth was used for this analysis. The solar ray intersection between a dish concentrator and its receiver, along with the heat flux distribution prediction, was carried out using SolTrace. The effect of flux intensity variation on temperature distribution at the receiver was investigated using comsol multiphysics. The optical analysis considered 10,000 rays, and 91.65% of them were observed to reach the surface of the receiver. For 1000 W/m2 of beam solar radiation, a peak heat flux and maximum temperature at the concentrator’s focal plane are found to be 32.4 MW/m2 and 923 K, respectively. The validation had been done using previously reported results in the literature to verify the correctness of the present simulation results. The effect of beam solar radiation variation on heat flux intensity and the temperature distribution revealed that both heat flux and temperature increase with increasing solar radiation, which points out the influence of design and operating conditions. Apart from PillBox and Gaussian distributions, the effect of slope and specularity errors was characterized, suggesting a greater sensitivity to the former than the latter.","PeriodicalId":8652,"journal":{"name":"ASME Open Journal of Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84224486","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}
Traditional design-for-manufacturability (DFM) strategies focus on efficiency and design simplification and tend to be too restrictive for optimization-based design methods; recent advances in manufacturing technologies have opened up many new and exciting design options, but it is necessary to have a wide design space in order to take advantage of these benefits. A simple but effective approach for restricting the design space to designs that are guaranteed to be manufacturable is needed. However, this should leave intact as much of the design space as possible. Work has been done in this area for some specific domains, but a general method for accomplishing this has not yet been refined. This article presents an exploration of this problem and a developed framework for mapping practical manufacturing knowledge into mathematical manufacturability constraints in mechanical design problem formulations. The steps for completing this mapping and the enforcing of the constraints are discussed and demonstrated. Three case studies (a milled heat exchanger fin, a 3-D printed topologically optimized beam, and a pulley requiring a hybrid additive–subtractive process for production) were completed to demonstrate the concepts; these included problem formulation, generation and enforcement of the manufacturability constraints, and fabrication of the resulting designs with and without explicit manufacturability constraints.
{"title":"Mapping and Enforcement of Minimally Restrictive Manufacturability Constraints in Mechanical Design","authors":"A. Patterson, James T. Allison","doi":"10.1115/1.4054170","DOIUrl":"https://doi.org/10.1115/1.4054170","url":null,"abstract":"Traditional design-for-manufacturability (DFM) strategies focus on efficiency and design simplification and tend to be too restrictive for optimization-based design methods; recent advances in manufacturing technologies have opened up many new and exciting design options, but it is necessary to have a wide design space in order to take advantage of these benefits. A simple but effective approach for restricting the design space to designs that are guaranteed to be manufacturable is needed. However, this should leave intact as much of the design space as possible. Work has been done in this area for some specific domains, but a general method for accomplishing this has not yet been refined. This article presents an exploration of this problem and a developed framework for mapping practical manufacturing knowledge into mathematical manufacturability constraints in mechanical design problem formulations. The steps for completing this mapping and the enforcing of the constraints are discussed and demonstrated. Three case studies (a milled heat exchanger fin, a 3-D printed topologically optimized beam, and a pulley requiring a hybrid additive–subtractive process for production) were completed to demonstrate the concepts; these included problem formulation, generation and enforcement of the manufacturability constraints, and fabrication of the resulting designs with and without explicit manufacturability constraints.","PeriodicalId":8652,"journal":{"name":"ASME Open Journal of Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91484034","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}
We present the analytical solutions of the second-, third-, and fourth-order response moments of a single-degree-of-freedom linear system subjected to a class of non-Gaussian random excitation. The non-Gaussian excitation is a zero-mean stationary stochastic process prescribed by an arbitrary probability density and a power spectrum whose peak is located at zero frequency. The excitation is described by an Itô stochastic differential equation in which the drift and diffusion coefficients are determined from the probability density and spectral density of the excitation. In order to obtain the analytical solutions of the response moments, first, we derive the third- and fourth-order autocorrelation functions of the non-Gaussian excitation using its Markov and detailed balance properties. The third-order correlation function is given by the same expression regardless of the difference in the probability density function of the excitation. On the other hand, the fourth-order correlation function is derived under the assumption that the excitation probability density belongs to the Pearson distribution family, which is one of the widest classes of probability distributions. Then, combining the autocorrelation functions of the excitation and the convolution representation of the response, we obtain the exact solutions of the response moments, and it is shown what kind of components the response moments are composed of. Finally, we investigate the dominant time-varying components of the response moments for several different excitation bandwidths.
{"title":"An Analysis of Transient Response Moments of a Linear System Subjected to Non-Gaussian Random Excitation Using Higher-Order Autocorrelation Functions of Excitation","authors":"H. Fukushima, T. Tsuchida","doi":"10.1115/1.4055079","DOIUrl":"https://doi.org/10.1115/1.4055079","url":null,"abstract":"\u0000 We present the analytical solutions of the second-, third-, and fourth-order response moments of a single-degree-of-freedom linear system subjected to a class of non-Gaussian random excitation. The non-Gaussian excitation is a zero-mean stationary stochastic process prescribed by an arbitrary probability density and a power spectrum whose peak is located at zero frequency. The excitation is described by an Itô stochastic differential equation in which the drift and diffusion coefficients are determined from the probability density and spectral density of the excitation. In order to obtain the analytical solutions of the response moments, first, we derive the third- and fourth-order autocorrelation functions of the non-Gaussian excitation using its Markov and detailed balance properties. The third-order correlation function is given by the same expression regardless of the difference in the probability density function of the excitation. On the other hand, the fourth-order correlation function is derived under the assumption that the excitation probability density belongs to the Pearson distribution family, which is one of the widest classes of probability distributions. Then, combining the autocorrelation functions of the excitation and the convolution representation of the response, we obtain the exact solutions of the response moments, and it is shown what kind of components the response moments are composed of. Finally, we investigate the dominant time-varying components of the response moments for several different excitation bandwidths.","PeriodicalId":8652,"journal":{"name":"ASME Open Journal of Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89149412","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}
Additive manufacturing (AM), also known as three-dimensional (3D) printing, is a disruptive technology that is revolutionizing many industries. It is gaining considerable attention, particularly in the medical field as it renders the possibilities of building new devices or modifying existing devices to match a patient's anatomy and to produce anatomically exact models, supporting health professionals with diagnostics and surgery preparation. In addition, the free-form building capability of AM allows the designer to have a complete control over the internal architecture of the device, along with tailored mechanical properties, such as compression strength, stiffness, and many surface features. As the processes of AM become well-understood, there is more control over the consistency and quality of the printed parts, positioning this technology for medical applications. With more and more medically approved 3D-printed devices entering the market, the purpose of this paper is to give an overview of the regulatory pathway to the Food and Drug Administration approval of a medical device, along with common AM processes used in the medical industry. To conclude, medical devices that are enabled by AM technology and associated companies will be highlighted.
{"title":"Progress of Additive Manufacturing Technology and Its Medical Applications","authors":"A.J.F. Bastin, Xiao Huang","doi":"10.1115/1.4054947","DOIUrl":"https://doi.org/10.1115/1.4054947","url":null,"abstract":"\u0000 Additive manufacturing (AM), also known as three-dimensional (3D) printing, is a disruptive technology that is revolutionizing many industries. It is gaining considerable attention, particularly in the medical field as it renders the possibilities of building new devices or modifying existing devices to match a patient's anatomy and to produce anatomically exact models, supporting health professionals with diagnostics and surgery preparation. In addition, the free-form building capability of AM allows the designer to have a complete control over the internal architecture of the device, along with tailored mechanical properties, such as compression strength, stiffness, and many surface features. As the processes of AM become well-understood, there is more control over the consistency and quality of the printed parts, positioning this technology for medical applications. With more and more medically approved 3D-printed devices entering the market, the purpose of this paper is to give an overview of the regulatory pathway to the Food and Drug Administration approval of a medical device, along with common AM processes used in the medical industry. To conclude, medical devices that are enabled by AM technology and associated companies will be highlighted.","PeriodicalId":8652,"journal":{"name":"ASME Open Journal of Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78500083","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}
Concrete mixture design usually requires labor-intensive and time-consuming work, which involves a significant amount of “trial batching” approaches. Recently, statistical and machine learning methods have demonstrated that a robust model might help reduce the experimental work greatly. Here, we develop the Gaussian process regression model to shed light on the relationship among the contents of cement, blast furnace slag, fly ash, water, superplasticizer, coarse aggregates, fine aggregates, and concrete compressive strength (CCS) at 28 days. A total of 399 concrete mixtures with CCS ranging from 8.54 MPa to 62.94 MPa are examined. The modeling approach is highly stable and accurate, achieving the correlation coefficient, mean absolute error, and root mean square error of 99.85%, 0.3769 (1.09% of the average experimental CCS), and 0.6755 (1.96% of the average experimental CCS), respectively. The model contributes to fast and low-cost CCS estimations.
{"title":"Machine Learning the Concrete Compressive Strength From Mixture Proportions","authors":"Xiaojie Xu, Yun Zhang","doi":"10.1115/1.4055194","DOIUrl":"https://doi.org/10.1115/1.4055194","url":null,"abstract":"\u0000 Concrete mixture design usually requires labor-intensive and time-consuming work, which involves a significant amount of “trial batching” approaches. Recently, statistical and machine learning methods have demonstrated that a robust model might help reduce the experimental work greatly. Here, we develop the Gaussian process regression model to shed light on the relationship among the contents of cement, blast furnace slag, fly ash, water, superplasticizer, coarse aggregates, fine aggregates, and concrete compressive strength (CCS) at 28 days. A total of 399 concrete mixtures with CCS ranging from 8.54 MPa to 62.94 MPa are examined. The modeling approach is highly stable and accurate, achieving the correlation coefficient, mean absolute error, and root mean square error of 99.85%, 0.3769 (1.09% of the average experimental CCS), and 0.6755 (1.96% of the average experimental CCS), respectively. The model contributes to fast and low-cost CCS estimations.","PeriodicalId":8652,"journal":{"name":"ASME Open Journal of Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85079439","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}
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