Methane released from coal during underground mining operations imposes a significant threat to the workers safety and consequently limits production. This paper introduces a method for the monitoring of methane emissions that are released during longwall coal mining operations. Furthermore, it describes the methodology used to test and develop the system’s response characteristics for improved measurement accuracy. The Methane Watchdog System (MWS) is a multi-nodal network of sensors currently under development to improve the safety and productivity during mining operations. The MWS consists of 10 compact sampling units designed to be integrated within the current roof support equipment of mines. Each unit contains an array of sensors to continuously monitor the environmental conditions which include methane concentration, temperature, pressure, and relative humidity. Reduced one-dimensional (1-D) modeling studies provided a useful tool to simulate the longwall mining environment. From the 1-D studies, multiple scenarios were constructed to generate temporal methane distributions that were the result of ventilation and production patterns. Model results were extracted from the proposed MWS sampling locations and used to demonstrate its usefulness and effectiveness within the laboratory setting. The resulting outputs from the system were then used to develop a signal reconstruction technique, which effectively sharpened response times and improved real time measurement accuracy.
{"title":"Improving Real-Time Methane Monitoring in Longwall Coal Mines Through System Response Characterization of a Multi-Nodal Methane Detection Network","authors":"B. Cappellini","doi":"10.33915/ETD.8333","DOIUrl":"https://doi.org/10.33915/ETD.8333","url":null,"abstract":"\u0000 Methane released from coal during underground mining operations imposes a significant threat to the workers safety and consequently limits production. This paper introduces a method for the monitoring of methane emissions that are released during longwall coal mining operations. Furthermore, it describes the methodology used to test and develop the system’s response characteristics for improved measurement accuracy. The Methane Watchdog System (MWS) is a multi-nodal network of sensors currently under development to improve the safety and productivity during mining operations. The MWS consists of 10 compact sampling units designed to be integrated within the current roof support equipment of mines. Each unit contains an array of sensors to continuously monitor the environmental conditions which include methane concentration, temperature, pressure, and relative humidity. Reduced one-dimensional (1-D) modeling studies provided a useful tool to simulate the longwall mining environment. From the 1-D studies, multiple scenarios were constructed to generate temporal methane distributions that were the result of ventilation and production patterns. Model results were extracted from the proposed MWS sampling locations and used to demonstrate its usefulness and effectiveness within the laboratory setting. The resulting outputs from the system were then used to develop a signal reconstruction technique, which effectively sharpened response times and improved real time measurement accuracy.","PeriodicalId":146533,"journal":{"name":"Volume 13: Safety Engineering, Risk, and Reliability Analysis; Research Posters","volume":"104 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132902172","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}
This research presents a new multiobjective fuzzy-based metaheuristic (MOFBMH) for aircraft wing design, which considers the uncertain structural design based on a fuzzy set model. Usually, the objective of this kind of design problem is to minimize weight of the composite wing with failure possibility constraints rather than converting it to multiobjective optimization with a fuzzy variable vector for material properties and loading conditions. The proposed technique is established in the form of multiobjective optimization, which sets the possibilistic safety index (PSI) as an objective function along with structural weight. This technique can explore a possible reliability solution set in one optimization run, which is advantageous. The present technique is one of the posteriori-techniques that start with finding all solutions and choosing it later. Two design examples are used to demonstrate the present technique i.e.simple cantilever beam and composite aeroelastic wing design problems.The results show the proposed technique can explore all possible structures, which are more conservative, and realizable.
{"title":"Multiobjective Reliability-Based Design of an Aircraft Wing Using a Fuzzy-Based Metaheuristic","authors":"Seksan Winyangkul, Suwin Sleesongsom, Sujin Bureerat","doi":"10.1115/imece2021-71001","DOIUrl":"https://doi.org/10.1115/imece2021-71001","url":null,"abstract":"\u0000 This research presents a new multiobjective fuzzy-based metaheuristic (MOFBMH) for aircraft wing design, which considers the uncertain structural design based on a fuzzy set model. Usually, the objective of this kind of design problem is to minimize weight of the composite wing with failure possibility constraints rather than converting it to multiobjective optimization with a fuzzy variable vector for material properties and loading conditions. The proposed technique is established in the form of multiobjective optimization, which sets the possibilistic safety index (PSI) as an objective function along with structural weight. This technique can explore a possible reliability solution set in one optimization run, which is advantageous. The present technique is one of the posteriori-techniques that start with finding all solutions and choosing it later. Two design examples are used to demonstrate the present technique i.e.simple cantilever beam and composite aeroelastic wing design problems.The results show the proposed technique can explore all possible structures, which are more conservative, and realizable.","PeriodicalId":146533,"journal":{"name":"Volume 13: Safety Engineering, Risk, and Reliability Analysis; Research Posters","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123776283","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}
Avitus Titus Mwelinde, Hongyu Jin, Jamal Banzi, Hongya Fu, Zhenyu Han
Spindle bearing is one of the machine elements in the spindle that is mostly vulnerable to failure. Its failure may result into total machine tool breakdown and other associated catastrophic consequences. An early identification of the failure is emphasized for reducing extreme damages of the machine tools. This study develops a novel hybrid algorithm combining the Zero Resonator Frequency Filter (ZRFF) and the Discrete Wavelet Packet Transform (DWPT) for early spindle bearing fault detection and diagnosis. The integrated method uses the ZRFF as the first level of de-noising the vibration signals and the DWPT for clear extraction of crucial periodic impulse features that are not easily visible from the first de-noising. The obtained frequency spectrum gives a dominant peak line which corresponds to the fault frequency of interest. An optimum wavelet decomposition level is also determined using the minimum Shannon entropy criteria. The experimental datasets from Case Western Reserve University (CWRU) and simulated signal were used to test the validity of the proposed algorithm. The proposed algorithm had superior performance in terms of computational efficiency (45s) and high classification accuracy of the bearings faults when compared with other methods.
{"title":"Spindle Bearings Fault Diagnosis Technique Based on Integration of Zero Resonator Frequency Filter and Discrete Wavelet Packet Transform","authors":"Avitus Titus Mwelinde, Hongyu Jin, Jamal Banzi, Hongya Fu, Zhenyu Han","doi":"10.1115/imece2021-73194","DOIUrl":"https://doi.org/10.1115/imece2021-73194","url":null,"abstract":"\u0000 Spindle bearing is one of the machine elements in the spindle that is mostly vulnerable to failure. Its failure may result into total machine tool breakdown and other associated catastrophic consequences. An early identification of the failure is emphasized for reducing extreme damages of the machine tools. This study develops a novel hybrid algorithm combining the Zero Resonator Frequency Filter (ZRFF) and the Discrete Wavelet Packet Transform (DWPT) for early spindle bearing fault detection and diagnosis. The integrated method uses the ZRFF as the first level of de-noising the vibration signals and the DWPT for clear extraction of crucial periodic impulse features that are not easily visible from the first de-noising. The obtained frequency spectrum gives a dominant peak line which corresponds to the fault frequency of interest. An optimum wavelet decomposition level is also determined using the minimum Shannon entropy criteria. The experimental datasets from Case Western Reserve University (CWRU) and simulated signal were used to test the validity of the proposed algorithm. The proposed algorithm had superior performance in terms of computational efficiency (45s) and high classification accuracy of the bearings faults when compared with other methods.","PeriodicalId":146533,"journal":{"name":"Volume 13: Safety Engineering, Risk, and Reliability Analysis; Research Posters","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126168543","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 front matter for this proceedings is available by clicking on the PDF icon.
通过点击PDF图标可获得本次会议的主题。
{"title":"IMECE2021 Front Matter","authors":"","doi":"10.1115/imece2021-fm13","DOIUrl":"https://doi.org/10.1115/imece2021-fm13","url":null,"abstract":"\u0000 The front matter for this proceedings is available by clicking on the PDF icon.","PeriodicalId":146533,"journal":{"name":"Volume 13: Safety Engineering, Risk, and Reliability Analysis; Research Posters","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130268730","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}
Matthew Quigley, Jason Klebba, B. Jawad, Liping Liu
Funded by an Undergraduate Program Equipment Grant from ASHARE, five undergraduate students in Mechanical Engineering were tasked to design and build a heat-exchanger demonstration kit as a teaching aid for classroom usage. The students were allotted one semester for design and one semester for assembly. The team researched existing products, performed theoretical calculations, and further identified their constraints with student surveys. The team also consulted several faculty members who are teaching Heat Transfer and Thermal Science Lab to get their input in order to provide a design and construction that best serves the teaching purpose. The final product is a rolling display board (approximately 4 feet wide and 5 feet tall) featuring a concentric tube heat exchanger prominently. An LCD screen allows students to see real-time temperature readings at four predetermined locations. Flow meters output the individual fluid flow rate of the coolant contained in two discrete piping loops. The fluid in these loops can operate in either parallel or counter-flow modes with the flip of a switch. Provisions were made to ensure sustainability and environmental consciousness, such as serviceable components and non-toxic coolant. The project concluded on time and under budget. This teaching kit is expected to help implementing active collaborative learning (ACL) activities in the classroom.
{"title":"Senior Capstone Project: A Classroom Heat Exchanger Demonstration Kit","authors":"Matthew Quigley, Jason Klebba, B. Jawad, Liping Liu","doi":"10.1115/imece2021-70833","DOIUrl":"https://doi.org/10.1115/imece2021-70833","url":null,"abstract":"\u0000 Funded by an Undergraduate Program Equipment Grant from ASHARE, five undergraduate students in Mechanical Engineering were tasked to design and build a heat-exchanger demonstration kit as a teaching aid for classroom usage. The students were allotted one semester for design and one semester for assembly. The team researched existing products, performed theoretical calculations, and further identified their constraints with student surveys. The team also consulted several faculty members who are teaching Heat Transfer and Thermal Science Lab to get their input in order to provide a design and construction that best serves the teaching purpose. The final product is a rolling display board (approximately 4 feet wide and 5 feet tall) featuring a concentric tube heat exchanger prominently. An LCD screen allows students to see real-time temperature readings at four predetermined locations. Flow meters output the individual fluid flow rate of the coolant contained in two discrete piping loops. The fluid in these loops can operate in either parallel or counter-flow modes with the flip of a switch. Provisions were made to ensure sustainability and environmental consciousness, such as serviceable components and non-toxic coolant. The project concluded on time and under budget. This teaching kit is expected to help implementing active collaborative learning (ACL) activities in the classroom.","PeriodicalId":146533,"journal":{"name":"Volume 13: Safety Engineering, Risk, and Reliability Analysis; Research Posters","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117274253","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 applicability of ML components in safety-critical systems will significantly depend on whether it will be possible to provide a comprehensive proof of their safety. Three research questions (RQ) are answered in order to provide a starting point for future activities towards the risk assessment of safety-critical systems containing ML components. First, special emphasis was placed on the design of a literature search strategy in order to enable quantitative insights into a representative set of publications (RQ1). Taxonomy analysis, bibliographic data visualization and compiled findings of reviews were therefore combined. A categorization of identified methods towards improving, ensuring and assessing safe machine learning was developed (RQ2). Then, a comparison was made with those methods for safety-critical software that are recommended by the functional safety standard IEC 61508 (RQ3). The comparison and quantification of research activity revealed imbalances within separate research areas. The conclusion is drawn that for the safety assessment of ML systems a comprehensive toolbox of combined methods needs to be converged from procedures within existing safety standards and the broad spectrum of methods proposed by current scientific publications.
{"title":"An Overview of the Research Landscape in the Field of Safe Machine Learning","authors":"George J. Siedel, Stefan Voß, S. Vock","doi":"10.1115/imece2021-69390","DOIUrl":"https://doi.org/10.1115/imece2021-69390","url":null,"abstract":"\u0000 The applicability of ML components in safety-critical systems will significantly depend on whether it will be possible to provide a comprehensive proof of their safety. Three research questions (RQ) are answered in order to provide a starting point for future activities towards the risk assessment of safety-critical systems containing ML components. First, special emphasis was placed on the design of a literature search strategy in order to enable quantitative insights into a representative set of publications (RQ1). Taxonomy analysis, bibliographic data visualization and compiled findings of reviews were therefore combined. A categorization of identified methods towards improving, ensuring and assessing safe machine learning was developed (RQ2). Then, a comparison was made with those methods for safety-critical software that are recommended by the functional safety standard IEC 61508 (RQ3). The comparison and quantification of research activity revealed imbalances within separate research areas. The conclusion is drawn that for the safety assessment of ML systems a comprehensive toolbox of combined methods needs to be converged from procedures within existing safety standards and the broad spectrum of methods proposed by current scientific publications.","PeriodicalId":146533,"journal":{"name":"Volume 13: Safety Engineering, Risk, and Reliability Analysis; Research Posters","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115519795","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}
F. Karpat, A. Dirik, O. Kalay, Celalettin Yüce, Oğuz Doğan, Burak Korcuklu
Gears are critical power transmission elements used in various industries. However, varying working speeds and sudden load changes may cause root cracks, pitting, or missing tooth failures. The asymmetric tooth profile offers higher load-carrying capacity, long life, and the ability to lessen vibration than the standard (symmetric) profile spur gears. Gearbox faults that cannot be detected early may lead the entire system to stop or serious damage to the machine. In this regard, Deep Learning (DL) algorithms have started to be utilized for gear early fault diagnosis. This study aims to determine the root crack for both symmetric and asymmetric involute spur gears with a DL-based approach. To this end, single tooth stiffness of the gears was obtained with ANSYS software for healthy and cracked gears (50–100%), and then the time-varying mesh stiffness (TVMS) was calculated. A six-degrees-offreedom dynamic model was developed by deriving the equations of motion of a single-stage spur gear mechanism. The vibration responses were collected for the healthy state, 50% and 100% crack degrees for both symmetric and asymmetric tooth profiles. Furthermore, the white Gaussian noise was added to the vibration data to complicate the early crack diagnosis task. The main contribution of this paper is that it adapts the DL-based approaches used for early fault diagnosis in standard profile involute spur gears to the asymmetric tooth concept for the first time. The proposed method can eliminate the need for large amounts of training data from costly physical experiments. Therefore, maintenance strategies can be improved by early crack detection.
{"title":"Fault Diagnosis With Deep Learning for Standard and Asymmetric Involute Spur Gears","authors":"F. Karpat, A. Dirik, O. Kalay, Celalettin Yüce, Oğuz Doğan, Burak Korcuklu","doi":"10.1115/imece2021-73702","DOIUrl":"https://doi.org/10.1115/imece2021-73702","url":null,"abstract":"\u0000 Gears are critical power transmission elements used in various industries. However, varying working speeds and sudden load changes may cause root cracks, pitting, or missing tooth failures. The asymmetric tooth profile offers higher load-carrying capacity, long life, and the ability to lessen vibration than the standard (symmetric) profile spur gears. Gearbox faults that cannot be detected early may lead the entire system to stop or serious damage to the machine. In this regard, Deep Learning (DL) algorithms have started to be utilized for gear early fault diagnosis. This study aims to determine the root crack for both symmetric and asymmetric involute spur gears with a DL-based approach. To this end, single tooth stiffness of the gears was obtained with ANSYS software for healthy and cracked gears (50–100%), and then the time-varying mesh stiffness (TVMS) was calculated. A six-degrees-offreedom dynamic model was developed by deriving the equations of motion of a single-stage spur gear mechanism. The vibration responses were collected for the healthy state, 50% and 100% crack degrees for both symmetric and asymmetric tooth profiles. Furthermore, the white Gaussian noise was added to the vibration data to complicate the early crack diagnosis task. The main contribution of this paper is that it adapts the DL-based approaches used for early fault diagnosis in standard profile involute spur gears to the asymmetric tooth concept for the first time. The proposed method can eliminate the need for large amounts of training data from costly physical experiments. Therefore, maintenance strategies can be improved by early crack detection.","PeriodicalId":146533,"journal":{"name":"Volume 13: Safety Engineering, Risk, and Reliability Analysis; Research Posters","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123664638","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}
Today, Probabilistic Risk Assessment (PRA) plays a vital role in assuring mission success for robotic and crewed missions alike. Current-day PRA techniques integrate multimodal, often black-box analyses to build comprehensive risk profiles. This paper describes a review and verification study of the “Nuclear Risk Assessment for the Mars 2020 Mission Environmental Impact Statement” (N-PRA)[1]. Sandia National Labs conducted the N-PRA for NASA’s Jet Propulsion Laboratory (JPL). More specifically, we have verified the source term calculations associated with the release of radionuclides from a Multi-Mission Radiothermoelectic Generator (MMRTG) power source for a limited set of accident scenarios in the case of an accidental re-entry into Earth Orbit with an Earth impacting trajectory. We achieve this by using analytical methods[2] historically implemented for the Cassini Mission PRA[3] for a failed planetary swingby gravity-assist. Our results are within 28% to 56% of the referenced study. Limitations in our methodology are attributed to a lack of modern simulation-based tools and deterministic methods for modeling complex physical phenomena. The results are interpreted and compared with the values presented by the initial authors, along with comments for improving our current methodology.
{"title":"Verification Study of the Nuclear PRA for the Mars 2020 Mission Following Accidental Orbital Re-Entry","authors":"Arjun Earthperson, M. Diaconeasa","doi":"10.1115/imece2021-71359","DOIUrl":"https://doi.org/10.1115/imece2021-71359","url":null,"abstract":"\u0000 Today, Probabilistic Risk Assessment (PRA) plays a vital role in assuring mission success for robotic and crewed missions alike. Current-day PRA techniques integrate multimodal, often black-box analyses to build comprehensive risk profiles. This paper describes a review and verification study of the “Nuclear Risk Assessment for the Mars 2020 Mission Environmental Impact Statement” (N-PRA)[1]. Sandia National Labs conducted the N-PRA for NASA’s Jet Propulsion Laboratory (JPL). More specifically, we have verified the source term calculations associated with the release of radionuclides from a Multi-Mission Radiothermoelectic Generator (MMRTG) power source for a limited set of accident scenarios in the case of an accidental re-entry into Earth Orbit with an Earth impacting trajectory.\u0000 We achieve this by using analytical methods[2] historically implemented for the Cassini Mission PRA[3] for a failed planetary swingby gravity-assist. Our results are within 28% to 56% of the referenced study. Limitations in our methodology are attributed to a lack of modern simulation-based tools and deterministic methods for modeling complex physical phenomena. The results are interpreted and compared with the values presented by the initial authors, along with comments for improving our current methodology.","PeriodicalId":146533,"journal":{"name":"Volume 13: Safety Engineering, Risk, and Reliability Analysis; Research Posters","volume":"114 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116491618","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 existing code procedures for glassy polymers are in ASME Safety Standard for Pressure Vessels for Human Occupancy (PVHO-1). The current service spans hostile conditions in the North Sea to controlled medical environments. These procedures are based on an empirical method and do not use material properties. The system is locked into specific shapes and cannot be adjusted to account for yield strength, ultimate strength, and other material considerations. An ASME task group is developing a Design By Analysis (DBA) methodology in order to allow for optimization in current service and innovation in other service. This paper presents the attempt to develop design margins as part of an overall risk assessment process that considers material properties, service conditions, and other factors not currently incorporated in the existing design method. Historical work used to develop the current system are analyzed using modern methods to attempt to quantifiably determine the existing design margins. The challenge is the empirical method implicitly relies on polymer manufacturers to greatly exceed the code. This, coupled with different modes of failure, results in no direct manner to compare PVHOs to conventional ASME pressure vessels design margins.
{"title":"Attempting To Establish Design Margins for Glassy Polymers In Critical Structural Service","authors":"Bart Kemper, Kaylie Kling Williams","doi":"10.1115/imece2021-71836","DOIUrl":"https://doi.org/10.1115/imece2021-71836","url":null,"abstract":"\u0000 The existing code procedures for glassy polymers are in ASME Safety Standard for Pressure Vessels for Human Occupancy (PVHO-1). The current service spans hostile conditions in the North Sea to controlled medical environments. These procedures are based on an empirical method and do not use material properties. The system is locked into specific shapes and cannot be adjusted to account for yield strength, ultimate strength, and other material considerations. An ASME task group is developing a Design By Analysis (DBA) methodology in order to allow for optimization in current service and innovation in other service. This paper presents the attempt to develop design margins as part of an overall risk assessment process that considers material properties, service conditions, and other factors not currently incorporated in the existing design method. Historical work used to develop the current system are analyzed using modern methods to attempt to quantifiably determine the existing design margins. The challenge is the empirical method implicitly relies on polymer manufacturers to greatly exceed the code. This, coupled with different modes of failure, results in no direct manner to compare PVHOs to conventional ASME pressure vessels design margins.","PeriodicalId":146533,"journal":{"name":"Volume 13: Safety Engineering, Risk, and Reliability Analysis; Research Posters","volume":"93 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126378829","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}
J. Brown, M. Clifford, J. Magaña, Mohd. Salman, D. Tran
At present, the world is undergoing a pandemic spawning from the advent of a new coronavirus outbreak known as COVID-19. As a result, hospital staff, paramedics, first responders, and the general world population have been forced to wear personal protective equipment (PPE) and take special measures to prevent catching the virus. Furthermore, because of this necessity, increasing demand on the PPE supply chain has generated many shortages, especially seen in masks designed to stop the inhalation of COVID-19 particles in the air. This inspired our group to design something that could help make PPE more accessible and affordable for the average person. The proposed is an almost entirely 3D printed design to help keep costs down and make it simplistic, such that anyone with a 3D printer has the potential to duplicate it. We hope that with the design, we can help combat the shortage and keep more people safe from COVID-19.
{"title":"Modular Printed Powered Air Purifying Respirator","authors":"J. Brown, M. Clifford, J. Magaña, Mohd. Salman, D. Tran","doi":"10.1115/imece2021-69333","DOIUrl":"https://doi.org/10.1115/imece2021-69333","url":null,"abstract":"\u0000 At present, the world is undergoing a pandemic spawning from the advent of a new coronavirus outbreak known as COVID-19. As a result, hospital staff, paramedics, first responders, and the general world population have been forced to wear personal protective equipment (PPE) and take special measures to prevent catching the virus. Furthermore, because of this necessity, increasing demand on the PPE supply chain has generated many shortages, especially seen in masks designed to stop the inhalation of COVID-19 particles in the air. This inspired our group to design something that could help make PPE more accessible and affordable for the average person. The proposed is an almost entirely 3D printed design to help keep costs down and make it simplistic, such that anyone with a 3D printer has the potential to duplicate it. We hope that with the design, we can help combat the shortage and keep more people safe from COVID-19.","PeriodicalId":146533,"journal":{"name":"Volume 13: Safety Engineering, Risk, and Reliability Analysis; Research Posters","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126901123","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}