Abstract Mechanical engineers have an important role in contributing to a more sustainable future. However, the extent that sustainability is currently being integrated into mechanical engineering (ME) curricula is unclear. This research characterized sustainability integration in undergraduate ME courses at 100 universities. Criterion-based selection resulted in a range of institution types and geographic locations (including institutions outside the United States); 93 of the 100 programs were accredited by the Engineering Accreditation Commission (EAC) of ABET. For 90 institutions, the data came from the Association for the Advancement of Sustainability for Higher Education (AASHE) Sustainability Tracking, Assessment & Rating System (STARS). Course catalog information was used for ten additional schools, in addition to comparing catalog data to STARS for ten institutions. Overall, sustainability topics were found in at least one elective or required undergraduate ME course at 83 institutions; only 43 institutions included sustainability in at least one required ME course; 16 institutions offered ten or more ME courses that integrated sustainability topics. Courses with sustainability integration at the greatest number of institutions were thermodynamics, engineering design, introduction to engineering, and heat transfer. Few of these courses appeared to integrate all three sustainability pillars (environmental, social, and economic). Leading institutions for sustainability integrations across the curriculum were identified. This work offers a picture of sustainability incorporation in undergraduate mechanical engineering programs, with the hope of catalyzing greater and more visible sustainability integration in the future.
{"title":"Sustainability in Mechanical Engineering Undergraduate Courses at 100 Universities","authors":"Joan K. Tisdale, Angela R. Bielefeldt","doi":"10.1115/1.4063387","DOIUrl":"https://doi.org/10.1115/1.4063387","url":null,"abstract":"Abstract Mechanical engineers have an important role in contributing to a more sustainable future. However, the extent that sustainability is currently being integrated into mechanical engineering (ME) curricula is unclear. This research characterized sustainability integration in undergraduate ME courses at 100 universities. Criterion-based selection resulted in a range of institution types and geographic locations (including institutions outside the United States); 93 of the 100 programs were accredited by the Engineering Accreditation Commission (EAC) of ABET. For 90 institutions, the data came from the Association for the Advancement of Sustainability for Higher Education (AASHE) Sustainability Tracking, Assessment & Rating System (STARS). Course catalog information was used for ten additional schools, in addition to comparing catalog data to STARS for ten institutions. Overall, sustainability topics were found in at least one elective or required undergraduate ME course at 83 institutions; only 43 institutions included sustainability in at least one required ME course; 16 institutions offered ten or more ME courses that integrated sustainability topics. Courses with sustainability integration at the greatest number of institutions were thermodynamics, engineering design, introduction to engineering, and heat transfer. Few of these courses appeared to integrate all three sustainability pillars (environmental, social, and economic). Leading institutions for sustainability integrations across the curriculum were identified. This work offers a picture of sustainability incorporation in undergraduate mechanical engineering programs, with the hope of catalyzing greater and more visible sustainability integration in the future.","PeriodicalId":8652,"journal":{"name":"ASME Open Journal of Engineering","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":"135838413","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}
Abstract A major advantage of the screw theory is that translations and rotations are treated simultaneously, which can provide greater insight into the vibration phenomena, such as vibration centers and axes. The present study describes how these concepts are extended into beam theory. The stiffness matrix of a beam was derived by incorporating different types of vibrations, such as extension, compression, torsion, and bending, at the same time, which was then used to obtain the equations of motion, including nonstandard forms of boundary conditions. We then presented an analytical method to solve these equations by focusing on two distinct examples, namely the cantilever and robot link. In the first numerical example, the mode shapes of the beam could be regarded as rotations about the vibration centers or axes of the rigid bodies in a discrete system. In the second example, the analytical solutions of mode shapes and natural frequencies of a robot link, for which the revolute joints at both sides are not parallel, were presented to demonstrate the utility of the screw theory. We demonstrated that the screw approach could accurately describe the vibrations of both discrete and continuous systems and that the geometric meaning of the vibration modes of discrete systems can be extended into continuous systems.
{"title":"A Screw Approach to Vibration Analysis of Beam Structures With Nonstandard Conditions","authors":"Yeong Geol Lee, Duck-Hee Lee","doi":"10.1115/1.4063461","DOIUrl":"https://doi.org/10.1115/1.4063461","url":null,"abstract":"Abstract A major advantage of the screw theory is that translations and rotations are treated simultaneously, which can provide greater insight into the vibration phenomena, such as vibration centers and axes. The present study describes how these concepts are extended into beam theory. The stiffness matrix of a beam was derived by incorporating different types of vibrations, such as extension, compression, torsion, and bending, at the same time, which was then used to obtain the equations of motion, including nonstandard forms of boundary conditions. We then presented an analytical method to solve these equations by focusing on two distinct examples, namely the cantilever and robot link. In the first numerical example, the mode shapes of the beam could be regarded as rotations about the vibration centers or axes of the rigid bodies in a discrete system. In the second example, the analytical solutions of mode shapes and natural frequencies of a robot link, for which the revolute joints at both sides are not parallel, were presented to demonstrate the utility of the screw theory. We demonstrated that the screw approach could accurately describe the vibrations of both discrete and continuous systems and that the geometric meaning of the vibration modes of discrete systems can be extended into continuous systems.","PeriodicalId":8652,"journal":{"name":"ASME Open Journal of Engineering","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":"136368215","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}
Severe service control valves or better, high-pressure reducing valves can see inlet pressures in excess of 4000 psi. Such valves are found in industries ranging from gas or petroleum wells, to chemical plants and steam-producing power plants (Goodwin, “Specifying Control Valves for Severe Service Conditions”, INTECH FOCUS, November (2022), p. 20). Such valves convert high levels of kinetic energy through a process of conversion of sound-producing turbulence to a reduced pressure level. Less desired by-products such as conversion are sound pressure levels that can exceed 120 decibels, a sound that is comparable to standing next to a jet plane taking off. Part of this energy conversion manifests itself as mechanical vibration which can cause undesirable high pipe acceleration which, over time, could severely damage piping (Almasi. “Flow Induced Vibrations in Piping Systems”. P.I. PROCESS INSTRUMENTATION, July, 2020; Blake, 1986, “Mechanics of Flow Induced Sound and Vibrato,” Vol. II, Complex Flow-Structure Interactions, Academic Press, Orlando, FL). Proposed here is an easy computer programmable method to check the sound and acceleration levels associated with noisy valves. It is believed such a paper harmonizing all aspects of aerodynamic valve noise, such as sound pressure, sound power, vibration, and acceleration can be of value. The purpose of this paper is to explain how such acceleration levels are estimated. There are four steps involved: (1) calculate the sound pressure level (SPL) from given process data, (2) convert sound pressure level into sound power level (Lwi), and (3) find the associated maximum pipe internal peak frequency (fp). (4) Based on the sound power level and the peak frequency of the sound, calculate the acceleration of the pipe (in m/second2).
{"title":"Method to Establish Sound and Acceleration Levels of High Pressure Reducing Valves","authors":"H. Baumann","doi":"10.1115/1.4062346","DOIUrl":"https://doi.org/10.1115/1.4062346","url":null,"abstract":"\u0000 Severe service control valves or better, high-pressure reducing valves can see inlet pressures in excess of 4000 psi. Such valves are found in industries ranging from gas or petroleum wells, to chemical plants and steam-producing power plants (Goodwin, “Specifying Control Valves for Severe Service Conditions”, INTECH FOCUS, November (2022), p. 20). Such valves convert high levels of kinetic energy through a process of conversion of sound-producing turbulence to a reduced pressure level. Less desired by-products such as conversion are sound pressure levels that can exceed 120 decibels, a sound that is comparable to standing next to a jet plane taking off. Part of this energy conversion manifests itself as mechanical vibration which can cause undesirable high pipe acceleration which, over time, could severely damage piping (Almasi. “Flow Induced Vibrations in Piping Systems”. P.I. PROCESS INSTRUMENTATION, July, 2020; Blake, 1986, “Mechanics of Flow Induced Sound and Vibrato,” Vol. II, Complex Flow-Structure Interactions, Academic Press, Orlando, FL). Proposed here is an easy computer programmable method to check the sound and acceleration levels associated with noisy valves. It is believed such a paper harmonizing all aspects of aerodynamic valve noise, such as sound pressure, sound power, vibration, and acceleration can be of value. The purpose of this paper is to explain how such acceleration levels are estimated. There are four steps involved: (1) calculate the sound pressure level (SPL) from given process data, (2) convert sound pressure level into sound power level (Lwi), and (3) find the associated maximum pipe internal peak frequency (fp). (4) Based on the sound power level and the peak frequency of the sound, calculate the acceleration of the pipe (in m/second2).","PeriodicalId":8652,"journal":{"name":"ASME Open Journal of Engineering","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":"80181668","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}
Clark Roubicek, Guangjun Gao, Hui Li, M. Stephen, S. Magleby, L. Howell
Deployable origami-based arrays can offer many benefits for a wide variety of engineering applications. However, alignment in the deployed state is a primary challenge of these arrays; in optical systems, local (single panel) and global (entire array) misalignment can drastically reduce performance. The objective of this work is to compare the relative sensitivities of different degrees-of-freedom (DOFs) of misalignment in deployable origami-based optical arrays and specify which have the greatest effect on performance. To accomplish this, we suggest a practice for defining local and global misalignment in deployable origami-based arrays, we simulate misalignment perturbations and record the resulting power output, and we use compensation techniques to restore as much lost power as possible. We use a deployable LiDAR telescope based on the hexagonal twist origami pattern as a case study, though the conclusions could be extended to other origami-based systems. From simulation, we find that the DOFs which are the most sensitive to misalignment and for which compensation is not effective are the local decenter X (467% power loss per mm misalignment), local decenter Y (463% power loss per mm misalignment), local tilt (357% power loss per degree misalignment), and local tip (265% power loss per degree misalignment) misalignments. These results could help minimize the need for compensation or position sensing and help optical systems designers to know which DOFs should be carefully controlled to maximize energy output.
{"title":"Effects of Panel Misalignment in a Deployable Origami-Based Optical Array","authors":"Clark Roubicek, Guangjun Gao, Hui Li, M. Stephen, S. Magleby, L. Howell","doi":"10.1115/1.4056475","DOIUrl":"https://doi.org/10.1115/1.4056475","url":null,"abstract":"\u0000 Deployable origami-based arrays can offer many benefits for a wide variety of engineering applications. However, alignment in the deployed state is a primary challenge of these arrays; in optical systems, local (single panel) and global (entire array) misalignment can drastically reduce performance. The objective of this work is to compare the relative sensitivities of different degrees-of-freedom (DOFs) of misalignment in deployable origami-based optical arrays and specify which have the greatest effect on performance. To accomplish this, we suggest a practice for defining local and global misalignment in deployable origami-based arrays, we simulate misalignment perturbations and record the resulting power output, and we use compensation techniques to restore as much lost power as possible. We use a deployable LiDAR telescope based on the hexagonal twist origami pattern as a case study, though the conclusions could be extended to other origami-based systems. From simulation, we find that the DOFs which are the most sensitive to misalignment and for which compensation is not effective are the local decenter X (467% power loss per mm misalignment), local decenter Y (463% power loss per mm misalignment), local tilt (357% power loss per degree misalignment), and local tip (265% power loss per degree misalignment) misalignments. These results could help minimize the need for compensation or position sensing and help optical systems designers to know which DOFs should be carefully controlled to maximize energy output.","PeriodicalId":8652,"journal":{"name":"ASME Open Journal of Engineering","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":"74989149","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}
Nadezda Avanessova, James Land, Alistair Lee, I. Lazakis, C. Thomson
Turbine ratings in the past decade have grown unexpectedly fast. In 2021, Siemens Gamesa and GE revealed their new 14 MW turbine models, and it is predicted that this is not yet the rating limit that turbines can reach. Increased turbine ratings can also be achieved by putting two turbines on a single foundation. This study analyzes how operation and maintenance (O&M) would differ if a floating wind farm had twin 10 MW turbines installed on each substructure, instead of a single 14 MW turbine. This study demonstrates how the strategic O&M simulation tool compass can be used to perform this comparison. Assumptions regarding the O&M of twin turbines were estimated with the major floating twin turbine developer Hexicon AB. This study analyzed four cases—a case with 35 twin 10 MW turbines, and three cases with 50 single 14 MW turbines—to understand the potential effect of increased consumable costs, spare part lead times, and maintenance durations. All cases had the same wind farm capacity of 700 MW. The results show that O&M for cases with single turbines is at least 4.5% more expensive than the case with twin turbines. The case with twin turbines also resulted in a higher availability than any other case. Additionally, results showed that operational expenditure (OPEX) for the cases with single turbines is at least 6.0% higher in scenarios with single turbines than in the twin turbine scenario. The biggest cost contributors to the difference between scenarios were craft costs, particularly cable laying vessels and tugs. Due to the higher number of cables required for the scenario with single turbines, there is more frequent mobilization of cable vessels for cable repairs.
{"title":"Comparison of Operation and Maintenance of Floating 14 MW Turbines and Twin 10 MW Turbines","authors":"Nadezda Avanessova, James Land, Alistair Lee, I. Lazakis, C. Thomson","doi":"10.1115/1.4062413","DOIUrl":"https://doi.org/10.1115/1.4062413","url":null,"abstract":"\u0000 Turbine ratings in the past decade have grown unexpectedly fast. In 2021, Siemens Gamesa and GE revealed their new 14 MW turbine models, and it is predicted that this is not yet the rating limit that turbines can reach. Increased turbine ratings can also be achieved by putting two turbines on a single foundation. This study analyzes how operation and maintenance (O&M) would differ if a floating wind farm had twin 10 MW turbines installed on each substructure, instead of a single 14 MW turbine. This study demonstrates how the strategic O&M simulation tool compass can be used to perform this comparison. Assumptions regarding the O&M of twin turbines were estimated with the major floating twin turbine developer Hexicon AB. This study analyzed four cases—a case with 35 twin 10 MW turbines, and three cases with 50 single 14 MW turbines—to understand the potential effect of increased consumable costs, spare part lead times, and maintenance durations. All cases had the same wind farm capacity of 700 MW. The results show that O&M for cases with single turbines is at least 4.5% more expensive than the case with twin turbines. The case with twin turbines also resulted in a higher availability than any other case. Additionally, results showed that operational expenditure (OPEX) for the cases with single turbines is at least 6.0% higher in scenarios with single turbines than in the twin turbine scenario. The biggest cost contributors to the difference between scenarios were craft costs, particularly cable laying vessels and tugs. Due to the higher number of cables required for the scenario with single turbines, there is more frequent mobilization of cable vessels for cable repairs.","PeriodicalId":8652,"journal":{"name":"ASME Open Journal of Engineering","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":"79601572","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}
The objective of this study was to assess the effects of small, incremental additions to wheelchair frame mass (0 kg, +2 kg, and +4 kg) on the mechanical propulsion characteristics in both straight and curvilinear maneuvers. A robotic propulsion system was used to propel a manual wheelchair over a smooth tiled surface following rectilinear ("Straight") and curvilinear ("Slalom") trajectories. Three unique loading conditions were tested. Propulsion costs and system rolling resistance estimations were empirically collected using the robotic wheelchair tester. Propulsion cost values were equivalent across all loading conditions over the Slalom trajectory. In the Straight trajectory, adding 2 kg on the axle had equivalent propulsion cost to the unloaded configuration. Adding 4 kg on axle was comparable, but not equivalent, to the unloaded configuration with small (≤4.1%) increases in propulsion cost. This study demonstrates that small (0-4 kg) changes to the frame mass have no meaningful impacts on the propulsion characteristics of the manual wheelchair system. Differences in propulsion cost and rolling resistance were detectable but contextually insignificant.
{"title":"Effects of Incremental Changes to Frame Mass on Manual Wheelchair Propulsion Cost.","authors":"Jacob Misch, Stephen Sprigle","doi":"10.1115/1.4062696","DOIUrl":"10.1115/1.4062696","url":null,"abstract":"<p><p>The objective of this study was to assess the effects of small, incremental additions to wheelchair frame mass (0 kg, +2 kg, and +4 kg) on the mechanical propulsion characteristics in both straight and curvilinear maneuvers. A robotic propulsion system was used to propel a manual wheelchair over a smooth tiled surface following rectilinear (\"Straight\") and curvilinear (\"Slalom\") trajectories. Three unique loading conditions were tested. Propulsion costs and system rolling resistance estimations were empirically collected using the robotic wheelchair tester. Propulsion cost values were equivalent across all loading conditions over the Slalom trajectory. In the Straight trajectory, adding 2 kg on the axle had equivalent propulsion cost to the unloaded configuration. Adding 4 kg on axle was comparable, but not equivalent, to the unloaded configuration with small (≤4.1%) increases in propulsion cost. This study demonstrates that small (0-4 kg) changes to the frame mass have no meaningful impacts on the propulsion characteristics of the manual wheelchair system. Differences in propulsion cost and rolling resistance were detectable but contextually insignificant.</p>","PeriodicalId":8652,"journal":{"name":"ASME Open Journal of Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10961999/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88905564","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}
Md Tanvir Ahad, T. Hartog, Amin G. Alhashim, M. Marshall, Z. Siddique
Electroencephalogram (EEG) alpha power (8–13 Hz) is a characteristic of various creative task conditions and is involved in creative ideation. Alpha power varies as a function of creativity-related task demands. This study investigated the event-related potentials (ERPs), alpha power activation, and potential machine learning (ML) to classify the neural responses of engineering students involved with creativity task. All participants performed a modified alternate uses task (AUT), in which participants categorized functions (or uses) for everyday objects as either creative, nonsense, or common. At first, this study investigated the fundamental ERPs over central and parietooccipital temporal areas. The bio-responses to understand creativity in engineering students demonstrates that nonsensical and creative stimuli elicit larger N400 amplitudes (−1.107 mV and −0.755 mV, respectively) than common uses (0.0859 mV) on the 300–500 ms window. N400 effect was observed on 300–500 ms window from the grand average waveforms of each electrode of interest. ANOVA analysis identified a significant main effect: decreased alpha power during creative ideation, especially over (O1/2, P7/8) parietooccipital temporal area. Machine learning is used to classify the specific temporal area data’s neural responses (creative, nonsense, and common). A k-nearest neighbors (kNN) classifier was used, and results were evaluated in terms of accuracy, precision, recall, and F1- score using the collected datasets from the participants. With an overall 99.92% accuracy and area under the curve at 0.9995, the kNN classifier successfully classified the participants’ neural responses. These results have great potential for broader adaptation of machine learning techniques in creativity research.
{"title":"Electroencephalogram Experimentation to Understand Creativity of Mechanical Engineering Students","authors":"Md Tanvir Ahad, T. Hartog, Amin G. Alhashim, M. Marshall, Z. Siddique","doi":"10.1115/1.4056473","DOIUrl":"https://doi.org/10.1115/1.4056473","url":null,"abstract":"\u0000 Electroencephalogram (EEG) alpha power (8–13 Hz) is a characteristic of various creative task conditions and is involved in creative ideation. Alpha power varies as a function of creativity-related task demands. This study investigated the event-related potentials (ERPs), alpha power activation, and potential machine learning (ML) to classify the neural responses of engineering students involved with creativity task. All participants performed a modified alternate uses task (AUT), in which participants categorized functions (or uses) for everyday objects as either creative, nonsense, or common. At first, this study investigated the fundamental ERPs over central and parietooccipital temporal areas. The bio-responses to understand creativity in engineering students demonstrates that nonsensical and creative stimuli elicit larger N400 amplitudes (−1.107 mV and −0.755 mV, respectively) than common uses (0.0859 mV) on the 300–500 ms window. N400 effect was observed on 300–500 ms window from the grand average waveforms of each electrode of interest. ANOVA analysis identified a significant main effect: decreased alpha power during creative ideation, especially over (O1/2, P7/8) parietooccipital temporal area. Machine learning is used to classify the specific temporal area data’s neural responses (creative, nonsense, and common). A k-nearest neighbors (kNN) classifier was used, and results were evaluated in terms of accuracy, precision, recall, and F1- score using the collected datasets from the participants. With an overall 99.92% accuracy and area under the curve at 0.9995, the kNN classifier successfully classified the participants’ neural responses. These results have great potential for broader adaptation of machine learning techniques in creativity research.","PeriodicalId":8652,"journal":{"name":"ASME Open Journal of Engineering","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":"75589703","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}
Alternative materials such as geopolymers appear to have potential advantages compared to Portland cement. However, the application of geopolymers for all sections of the well is still a major challenge due to the difference in temperature ranges. To that end, the classification of the granite-based geopolymer mix designs requires a thorough investigation of various properties at a range of different operational temperatures. In this study, three mix designs are presented for different well sections at temperatures ranging from 5 °C to 60 °C. The mix designs for low temperatures (<50 °C) were tuned by adding CaO to the dry solid blend. Workability, rheology, short-term compressive strength, and X-ray diffraction (XRD) analysis were conducted to conclude the performance of the mix designs under study. Results highlight the presence of Ca content (wt%) in mix designs and its role in enhancing material performance at low operational temperatures. The study reveals a promising future application of the granite-based geopolymer for well construction and abandonment at varying depths with recommendations for further improving the performance by the addition of chemical admixtures. In addition, the relation between temperature and Ca content was highlighted, and more investigations into the kinetics governing these two parameters were recommended.
{"title":"Temperature-Dependent Classification of Geopolymers Derived From Granite Designed for Well Cementing Applications","authors":"Fawzi Chamssine, M. N. Agista, M. Khalifeh","doi":"10.1115/1.4063027","DOIUrl":"https://doi.org/10.1115/1.4063027","url":null,"abstract":"\u0000 Alternative materials such as geopolymers appear to have potential advantages compared to Portland cement. However, the application of geopolymers for all sections of the well is still a major challenge due to the difference in temperature ranges. To that end, the classification of the granite-based geopolymer mix designs requires a thorough investigation of various properties at a range of different operational temperatures. In this study, three mix designs are presented for different well sections at temperatures ranging from 5 °C to 60 °C. The mix designs for low temperatures (<50 °C) were tuned by adding CaO to the dry solid blend. Workability, rheology, short-term compressive strength, and X-ray diffraction (XRD) analysis were conducted to conclude the performance of the mix designs under study. Results highlight the presence of Ca content (wt%) in mix designs and its role in enhancing material performance at low operational temperatures. The study reveals a promising future application of the granite-based geopolymer for well construction and abandonment at varying depths with recommendations for further improving the performance by the addition of chemical admixtures. In addition, the relation between temperature and Ca content was highlighted, and more investigations into the kinetics governing these two parameters were recommended.","PeriodicalId":8652,"journal":{"name":"ASME Open Journal of Engineering","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":"75189460","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}
Apurva Patel, Joshua Ortiz, J. Summers, James L. Mathieson
While fundamentals of DFMA (design for manufacturing and assembly) are widely accepted and used in the engineering community, many CAD environments lack tools that address manufacturing concerns by providing rapid feedback about costs resulting from design choices. This article presents an experiment-based testing and validation of a rapid feedback tool that provides users history-based prediction of manufacturing time based on the current state of the design. A between-subject experiment is designed to evaluate the impact of the tool on design outcomes based on modeling time, part mass, and manufacturing time. Participants in the study included mechanical engineering graduate and undergraduate students with at least one semester of experience using solidworks. The experiment included three modeling activities and three tool conditions. Participants completed up to three sessions with different experimental conditions. Analysis of the data collected shows that the use of the design tool results in a small but nonsignificant increase in modeling time. Moreover, the use of the tool results in reduced part mass on average (both between subjects and within subjects). Tool use reduced manufacturing time in open-ended activities, but increased manufacturing time when activities focus more on mass reduction. Participant feedback suggests that the tool helped guide their material removal actions by showing the impact on manufacturing time. Finally, potential improvements and future expansions of the tool are discussed.
{"title":"Validation Study of a Computer-Aided Design Augmentation Tool for Cost Estimation","authors":"Apurva Patel, Joshua Ortiz, J. Summers, James L. Mathieson","doi":"10.1115/1.4062110","DOIUrl":"https://doi.org/10.1115/1.4062110","url":null,"abstract":"\u0000 While fundamentals of DFMA (design for manufacturing and assembly) are widely accepted and used in the engineering community, many CAD environments lack tools that address manufacturing concerns by providing rapid feedback about costs resulting from design choices. This article presents an experiment-based testing and validation of a rapid feedback tool that provides users history-based prediction of manufacturing time based on the current state of the design. A between-subject experiment is designed to evaluate the impact of the tool on design outcomes based on modeling time, part mass, and manufacturing time. Participants in the study included mechanical engineering graduate and undergraduate students with at least one semester of experience using solidworks. The experiment included three modeling activities and three tool conditions. Participants completed up to three sessions with different experimental conditions. Analysis of the data collected shows that the use of the design tool results in a small but nonsignificant increase in modeling time. Moreover, the use of the tool results in reduced part mass on average (both between subjects and within subjects). Tool use reduced manufacturing time in open-ended activities, but increased manufacturing time when activities focus more on mass reduction. Participant feedback suggests that the tool helped guide their material removal actions by showing the impact on manufacturing time. Finally, potential improvements and future expansions of the tool are discussed.","PeriodicalId":8652,"journal":{"name":"ASME Open Journal of Engineering","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":"77207129","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}
Propane (C3H8) and hydrogen (H2) are regarded as alternative fuels that are favorable to the environment. Hydrogen gas's low energy density, storage, and transportation are the main issues with using it as an alternative fuel. Addition of hydrogen gas in the combustion of propane will also improve flame stability, broaden lean flammability limits, and reduces pollutant emissions. Thus, utilizing propane and hydrogen mixtures as fuel is a good choice. Laminar burning speed is a fundamental property of a combustible mixture and can be used to provide information regarding the mixture’s reactivity, exothermicity, and diffusivity. In this study, power-law correlation and machine learning methods were used to create models that predict the laminar burning speed of propane/hydrogen/air mixtures at various states. Two machine learning models are artificial neural network (ANN) and support vector machine (SVM). The data were generated by using CANTRA code and a chemical kinetic mechanism. For a wide variety of input values, the models were able to determine the laminar burning speed with great accuracy. The ANN model yields the best performance. The main advantage of these models is the noticeably faster computing time when compared to chemical reaction mechanisms.
{"title":"Prediction of Laminar Burning Speed of Propane/Hydrogen/Air Mixtures Using Power-Law Correlation and Two Machine Learning Models","authors":"Zhenyu Lu, H. Metghalchi","doi":"10.1115/1.4062745","DOIUrl":"https://doi.org/10.1115/1.4062745","url":null,"abstract":"\u0000 Propane (C3H8) and hydrogen (H2) are regarded as alternative fuels that are favorable to the environment. Hydrogen gas's low energy density, storage, and transportation are the main issues with using it as an alternative fuel. Addition of hydrogen gas in the combustion of propane will also improve flame stability, broaden lean flammability limits, and reduces pollutant emissions. Thus, utilizing propane and hydrogen mixtures as fuel is a good choice. Laminar burning speed is a fundamental property of a combustible mixture and can be used to provide information regarding the mixture’s reactivity, exothermicity, and diffusivity. In this study, power-law correlation and machine learning methods were used to create models that predict the laminar burning speed of propane/hydrogen/air mixtures at various states. Two machine learning models are artificial neural network (ANN) and support vector machine (SVM). The data were generated by using CANTRA code and a chemical kinetic mechanism. For a wide variety of input values, the models were able to determine the laminar burning speed with great accuracy. The ANN model yields the best performance. The main advantage of these models is the noticeably faster computing time when compared to chemical reaction mechanisms.","PeriodicalId":8652,"journal":{"name":"ASME Open Journal of Engineering","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":"84288700","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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