Andrea Fragnito, M. Iasiello, G. M. Mauro, C. Menna
The national and international building stock – representing one of the most intensive energy-consuming sectors worldwide – is characterized by a large share of old constructions, designed without following any energy criteria. This scenario has promoted the rising of powerful technologies, e.g., Additive Manufacturing (AM), which despite its recent rise is leading the innovation process involving both the industrial and civil sectors. 3D printing techniques are going to outperform current production techniques because of their various advantages, i.e., design of complex forms, uniform materials, reduced production steps and costs. The aim of the present work is to combine the accuracy of computer-aided design (CAD) for AM structures with the benefits of the computational thermo-fluid dynamic simulation (CFD) to perform thermal and moisture performance analysis of innovative building walls. Natural convection and radiation problem – involving buoyancy-driven flow in a cavity – is investigated and solved under appropriate boundary conditions defined in a finite element commercial code. After validation with international guidelines and literature data, the model is simulated in Napoli (Italy) under winter design conditions. Moreover, this work provides a comparison between a simplified procedure for the condensation risk detection, i.e., the Glaser method, and an advanced one – based on the steady-state diffusion theory – which considers latent heat effect and capillary transport of moisture liquid. The results show that the radiative heat transfer mechanism has a significant influence on thermal transmittance. On the other hand – with reference to the case study – here we present the discrepancy between the prediction of the condensation effect during the winter months by adopting the present method with respect to the Glaser one.
{"title":"Simultaneous Heat and Moisture Transport in 3D Printed Walls","authors":"Andrea Fragnito, M. Iasiello, G. M. Mauro, C. Menna","doi":"10.11159/htff22.150","DOIUrl":"https://doi.org/10.11159/htff22.150","url":null,"abstract":"The national and international building stock – representing one of the most intensive energy-consuming sectors worldwide – is characterized by a large share of old constructions, designed without following any energy criteria. This scenario has promoted the rising of powerful technologies, e.g., Additive Manufacturing (AM), which despite its recent rise is leading the innovation process involving both the industrial and civil sectors. 3D printing techniques are going to outperform current production techniques because of their various advantages, i.e., design of complex forms, uniform materials, reduced production steps and costs. The aim of the present work is to combine the accuracy of computer-aided design (CAD) for AM structures with the benefits of the computational thermo-fluid dynamic simulation (CFD) to perform thermal and moisture performance analysis of innovative building walls. Natural convection and radiation problem – involving buoyancy-driven flow in a cavity – is investigated and solved under appropriate boundary conditions defined in a finite element commercial code. After validation with international guidelines and literature data, the model is simulated in Napoli (Italy) under winter design conditions. Moreover, this work provides a comparison between a simplified procedure for the condensation risk detection, i.e., the Glaser method, and an advanced one – based on the steady-state diffusion theory – which considers latent heat effect and capillary transport of moisture liquid. The results show that the radiative heat transfer mechanism has a significant influence on thermal transmittance. On the other hand – with reference to the case study – here we present the discrepancy between the prediction of the condensation effect during the winter months by adopting the present method with respect to the Glaser one.","PeriodicalId":385356,"journal":{"name":"Proceedings of the 8th World Congress on Mechanical, Chemical, and Material Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125000685","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}
Yaprak Nisa Oguz, Mustafa Burak Gedikli, Yunus Emre Nehri, Gülcan Toktaş, A. Oral
– In this study, AISI 1040 carbon steel plate and cylindrical parts used as brackets in wind turbine towers were bonded with 3M acrylic adhesive. The static strength values (shear stress, bending stress and equivalent stress) of the adhesion bond were determined by mechanical test setup. Also; since fatigue occurs inside the tower by thermal stresses and pressures, S-N curves are obtained depending on the equivalent stress varying at R=0 stress ratio of the bonded parts under repeated stress. As a result of the experiments, it was found that the adhesion bond has an infinite life under 35 MPa fluctuating equivalent stress.
{"title":"Experimental Investigation of Fatigue Strength in Adhesive Bonds","authors":"Yaprak Nisa Oguz, Mustafa Burak Gedikli, Yunus Emre Nehri, Gülcan Toktaş, A. Oral","doi":"10.11159/icmie22.107","DOIUrl":"https://doi.org/10.11159/icmie22.107","url":null,"abstract":"– In this study, AISI 1040 carbon steel plate and cylindrical parts used as brackets in wind turbine towers were bonded with 3M acrylic adhesive. The static strength values (shear stress, bending stress and equivalent stress) of the adhesion bond were determined by mechanical test setup. Also; since fatigue occurs inside the tower by thermal stresses and pressures, S-N curves are obtained depending on the equivalent stress varying at R=0 stress ratio of the bonded parts under repeated stress. As a result of the experiments, it was found that the adhesion bond has an infinite life under 35 MPa fluctuating equivalent stress.","PeriodicalId":385356,"journal":{"name":"Proceedings of the 8th World Congress on Mechanical, Chemical, and Material Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125074600","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}
– Path planning plays a central role in robot-assisted percutaneous insertion. The main challenge of path planning exists in the motion constraints inherited from the geometry and mechanics of the needle, and the complex anatomic environment of human body. In nonholonomic planning, the classic Rapidly-Exploring Random Trees (RRT) algorithm may fail to provide a continuous and obstacle-avoidable path. To find a feasible path and minimize the damage on soft tissues based on a newly-introduced curvature-controllable steerable needle, we propose a method that utilizes RRT* and quadratic Bezier curve smoothing technique. RRT* with Bezier Curve Smoothing can generate a path composed of smooth piecewise planar curves with continuous connections. Comparisons are employed to show that our method generates shorter and less torturous paths with a higher success rate.
{"title":"Path Planning with Modified RRT* Algorithm for Lung Biopsy","authors":"Yuexi Dong, Kun Wang, Zhen Yang, S. Fok, Han Wang","doi":"10.11159/icmie22.124","DOIUrl":"https://doi.org/10.11159/icmie22.124","url":null,"abstract":"– Path planning plays a central role in robot-assisted percutaneous insertion. The main challenge of path planning exists in the motion constraints inherited from the geometry and mechanics of the needle, and the complex anatomic environment of human body. In nonholonomic planning, the classic Rapidly-Exploring Random Trees (RRT) algorithm may fail to provide a continuous and obstacle-avoidable path. To find a feasible path and minimize the damage on soft tissues based on a newly-introduced curvature-controllable steerable needle, we propose a method that utilizes RRT* and quadratic Bezier curve smoothing technique. RRT* with Bezier Curve Smoothing can generate a path composed of smooth piecewise planar curves with continuous connections. Comparisons are employed to show that our method generates shorter and less torturous paths with a higher success rate.","PeriodicalId":385356,"journal":{"name":"Proceedings of the 8th World Congress on Mechanical, Chemical, and Material Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123243023","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}
– To achieve accurate slug lengths and velocities in slug flow regime, monitoring of the droplet/bubble train is an essential stage which necessitates the use of proper techniques. In most experiments, the traditional measurement apparatus consists of a high-speed camera coupled to a microscope which are employed to characterize such flows in microchannels. However, when using these techniques, optical distortion caused by the curved channel walls can result in large measurement uncertainty which undermines the measurement accuracy. In this regard, this study introduces a novel technique to easily and reliably measure the slug length and velocity. This automated non-intrusive measurement technique allows in-line high-frequency of droplet/bubble detection and related physical properties based on changes in the light intensity caused by a phase shifting in liquid-liquid or liquid-gas flows.
{"title":"High Frequency Flow Measurement Technique for Slug Flow Regimes","authors":"Seyyed Saeed Shojaee Zadeh, V. Egan, P. Walsh","doi":"10.11159/htff22.144","DOIUrl":"https://doi.org/10.11159/htff22.144","url":null,"abstract":"– To achieve accurate slug lengths and velocities in slug flow regime, monitoring of the droplet/bubble train is an essential stage which necessitates the use of proper techniques. In most experiments, the traditional measurement apparatus consists of a high-speed camera coupled to a microscope which are employed to characterize such flows in microchannels. However, when using these techniques, optical distortion caused by the curved channel walls can result in large measurement uncertainty which undermines the measurement accuracy. In this regard, this study introduces a novel technique to easily and reliably measure the slug length and velocity. This automated non-intrusive measurement technique allows in-line high-frequency of droplet/bubble detection and related physical properties based on changes in the light intensity caused by a phase shifting in liquid-liquid or liquid-gas flows.","PeriodicalId":385356,"journal":{"name":"Proceedings of the 8th World Congress on Mechanical, Chemical, and Material Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115517396","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}
Extended Abstract Porous materials like metal and graphitic foams are seeing increased use in heat transfer devices due to their high solid-phase conductivity and area-to-volume ratios. The internal structures of these materials can be extremely complex, but accurate characterization of the foam properties in terms of permeability, inertial losses, interstitial exchange and effective conductivity are critical for being able to consider such materials in design and application. Recent literature exists for characterizing permeable porous materials by conducting pore-level simulations on idealized geometric models [1-2] or geometric models generated by scanning samples of the porous media [3-4]. In such cases, a given geometric structure is discretized and simulations are conducted to obtain direct solutions to the mass, momentum and energy equations under laminar or turbulent flow conditions. These simulations can be used to obtain integral quantities characterizing the resistance to fluid passage, convective exchange and thermal dispersion, all of which are required for analogous simulations conducted using the volume-averaged (porous-continuum) approach. In addition to flow resistance and interstitial heat exchange, accurate information must be provided to characterize the solid phase conduction, which because of the complex shape, is a function of both solid-phase conductivity and a conduction shape factor, which characterizes the departure of the conduction path from being straight and of uniform cross-section [5-6]. In the present study, spherical-void-phase representative elemental volumes developed using the Discrete Element approach described in Dyck & Straatman [7] were produced over the range of porosities 0.70 ≤ ε ≤ 0.85 and for
{"title":"The Impact Of Conduction Shape Factor In Volume Averaged Calculations Of Heat Transfer In Permeable Porous Materials","authors":"A. Straatman, Cole T. Fleet","doi":"10.11159/htff22.124","DOIUrl":"https://doi.org/10.11159/htff22.124","url":null,"abstract":"Extended Abstract Porous materials like metal and graphitic foams are seeing increased use in heat transfer devices due to their high solid-phase conductivity and area-to-volume ratios. The internal structures of these materials can be extremely complex, but accurate characterization of the foam properties in terms of permeability, inertial losses, interstitial exchange and effective conductivity are critical for being able to consider such materials in design and application. Recent literature exists for characterizing permeable porous materials by conducting pore-level simulations on idealized geometric models [1-2] or geometric models generated by scanning samples of the porous media [3-4]. In such cases, a given geometric structure is discretized and simulations are conducted to obtain direct solutions to the mass, momentum and energy equations under laminar or turbulent flow conditions. These simulations can be used to obtain integral quantities characterizing the resistance to fluid passage, convective exchange and thermal dispersion, all of which are required for analogous simulations conducted using the volume-averaged (porous-continuum) approach. In addition to flow resistance and interstitial heat exchange, accurate information must be provided to characterize the solid phase conduction, which because of the complex shape, is a function of both solid-phase conductivity and a conduction shape factor, which characterizes the departure of the conduction path from being straight and of uniform cross-section [5-6]. In the present study, spherical-void-phase representative elemental volumes developed using the Discrete Element approach described in Dyck & Straatman [7] were produced over the range of porosities 0.70 ≤ ε ≤ 0.85 and for","PeriodicalId":385356,"journal":{"name":"Proceedings of the 8th World Congress on Mechanical, Chemical, and Material Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117070803","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}
– Ride comfort has been an important development parameter for transport vehicles starting from early horse carriages with simple leaf spring suspension systems, up to modern vehicles with the state-of-the-art suspension systems. A vehicle without a suspension system will transfer all the disturbances caused by bumps or holes on the road resulting to high acceleration and jerk values at the passenger compartment. Suspension system acts as the cushion of the vehicle when it undergoes road irregularities improving passenger comfort. Softer suspension systems provide better ride comfort via reducing the magnitude of the chassis oscillations however have negative effect on vehicle dynamics considering the fact that they result with loss of traction due to excessive roll motion of the vehicle causing weight transfer from the inner wheels to the outer wheels during cornering manoeuvres. Hence, optimization of suspension system parameters is essential considering both vehicle comfort and dynamics. Similar to all mechanical components, optimization using real hardware is considerably expensive and time consuming. Therefore, model-based optimization is essential to obtain the best performance parameters considering objectives as follows: minimize acceleration magnitude and pitch angle. Within this study a Half Car Model (HCM) for vehicle suspension system is developed in MATLAB / Simulink software and parameters used in the model are tuned for a Sport Utility Vehicle (SUV) using measurements captured via MATLAB Mobile software employed in a mobile phone. A full factorial Design of Experiment (DOE) is developed spanning ± %20 of original values. A regression model is built in Minitab software and it has been showed that optimized parameters result with %3.4 and 9.4% reduction in pitch angle and maximum acceleration values respectively.
{"title":"Optimization of Suspension System Parameters for a SUV","authors":"M. Otkur, Noura Abdullah, Narjes Alshammari, Danah Alkandari, Hanan Thyab, Latifah Alduwaisan","doi":"10.11159/icmie22.137","DOIUrl":"https://doi.org/10.11159/icmie22.137","url":null,"abstract":"– Ride comfort has been an important development parameter for transport vehicles starting from early horse carriages with simple leaf spring suspension systems, up to modern vehicles with the state-of-the-art suspension systems. A vehicle without a suspension system will transfer all the disturbances caused by bumps or holes on the road resulting to high acceleration and jerk values at the passenger compartment. Suspension system acts as the cushion of the vehicle when it undergoes road irregularities improving passenger comfort. Softer suspension systems provide better ride comfort via reducing the magnitude of the chassis oscillations however have negative effect on vehicle dynamics considering the fact that they result with loss of traction due to excessive roll motion of the vehicle causing weight transfer from the inner wheels to the outer wheels during cornering manoeuvres. Hence, optimization of suspension system parameters is essential considering both vehicle comfort and dynamics. Similar to all mechanical components, optimization using real hardware is considerably expensive and time consuming. Therefore, model-based optimization is essential to obtain the best performance parameters considering objectives as follows: minimize acceleration magnitude and pitch angle. Within this study a Half Car Model (HCM) for vehicle suspension system is developed in MATLAB / Simulink software and parameters used in the model are tuned for a Sport Utility Vehicle (SUV) using measurements captured via MATLAB Mobile software employed in a mobile phone. A full factorial Design of Experiment (DOE) is developed spanning ± %20 of original values. A regression model is built in Minitab software and it has been showed that optimized parameters result with %3.4 and 9.4% reduction in pitch angle and maximum acceleration values respectively.","PeriodicalId":385356,"journal":{"name":"Proceedings of the 8th World Congress on Mechanical, Chemical, and Material Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124725896","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}
- Biopolymers have emerged as an appropriate replacement for conventional petrochemical polymers consoling our environmental concern. As an alternative to polyolefin, polylactic acid (PLA) has been identified as a capable biodegradable polymer. Lactide ring opening polymerization (ROP) has been demonstrated to be an efficient polymerization method. A well validated moment based kinetic model for lactide ROP referring with homogeneously well stirred batch reactor using 2-ethylhexanoic acid tin (II) salt as the catalyst and an alcohol as co-catalyst has been utilized to formulate the multi objective optimization problem (MOOP). The MOOP is composed of three conflicting objective functions: minimization of time, minimization of PDI and maximization of number average molecular weight (Mn). Decision variables have been implemented to analyse the process performance with the mass balance equation for objective function ranges as constraints. The optimization problem does not contain a single solution but rather contains several equally important solutions (Pareto front) which are called as non-dominated solutions and this Pareto front is obtained by using non-dominated sorting genetic algorithm-II (NSGA II) developed by Deb, 2001. Some of the Pareto front points showed better outcomes rather than the experimental data. The distinct aspect of modeling and optimization from experimental data can be applied directly in the actual large-scale plants.
{"title":"Kinetic Analysis and Multi Objective Optimization of L-Lactide Polymerization","authors":"Geetu P Paul, Virivinti Nagajyothi","doi":"10.11159/iccpe22.105","DOIUrl":"https://doi.org/10.11159/iccpe22.105","url":null,"abstract":"- Biopolymers have emerged as an appropriate replacement for conventional petrochemical polymers consoling our environmental concern. As an alternative to polyolefin, polylactic acid (PLA) has been identified as a capable biodegradable polymer. Lactide ring opening polymerization (ROP) has been demonstrated to be an efficient polymerization method. A well validated moment based kinetic model for lactide ROP referring with homogeneously well stirred batch reactor using 2-ethylhexanoic acid tin (II) salt as the catalyst and an alcohol as co-catalyst has been utilized to formulate the multi objective optimization problem (MOOP). The MOOP is composed of three conflicting objective functions: minimization of time, minimization of PDI and maximization of number average molecular weight (Mn). Decision variables have been implemented to analyse the process performance with the mass balance equation for objective function ranges as constraints. The optimization problem does not contain a single solution but rather contains several equally important solutions (Pareto front) which are called as non-dominated solutions and this Pareto front is obtained by using non-dominated sorting genetic algorithm-II (NSGA II) developed by Deb, 2001. Some of the Pareto front points showed better outcomes rather than the experimental data. The distinct aspect of modeling and optimization from experimental data can be applied directly in the actual large-scale plants.","PeriodicalId":385356,"journal":{"name":"Proceedings of the 8th World Congress on Mechanical, Chemical, and Material Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123801247","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}
- Bubble Column Reactors (BCR) / Slurry Bubble Column Reactors (SBCR) have many advantageous characteristics as such they are used in numerous industrial applications. This work reviews the Eulerian Computational Fluid Dynamics (CFD) approach when analysing BCR/ SBCRs. Several studies have been reviewed which vary parameters such as the reactor design, superficial gas velocity, pressure, CFD models (drag, turbulence), particle concentration, and phase material to investigate their effects on the reactor’s performance in terms of hydrodynamics or heat transfer. This review indicates that using a Eulerian CFD model can accurately predict the BCR/SBCR’s performance. Key findings include that increasing the superficial gas velocity, column pressure, and gas phase density increases the gas holdup. Gas holdup is unevenly distributed in the BCR where most of the gas holdup is in the centre of the column. Increasing solid particles decreases the bubble breakup rate and gas holdup. Furthermore, it was concluded that increasing the superficial gas velocity increases the average slurry temperature and volumetric heat transfer. However, decreasing the column height increases the slurry temperature and volumetric heat transfer.
{"title":"Eulerian Approach to CFD Analysis of a Bubble Column Reactor – A Review","authors":"M. Abdulrahman, Nibras Nassar","doi":"10.11159/htff22.188","DOIUrl":"https://doi.org/10.11159/htff22.188","url":null,"abstract":"- Bubble Column Reactors (BCR) / Slurry Bubble Column Reactors (SBCR) have many advantageous characteristics as such they are used in numerous industrial applications. This work reviews the Eulerian Computational Fluid Dynamics (CFD) approach when analysing BCR/ SBCRs. Several studies have been reviewed which vary parameters such as the reactor design, superficial gas velocity, pressure, CFD models (drag, turbulence), particle concentration, and phase material to investigate their effects on the reactor’s performance in terms of hydrodynamics or heat transfer. This review indicates that using a Eulerian CFD model can accurately predict the BCR/SBCR’s performance. Key findings include that increasing the superficial gas velocity, column pressure, and gas phase density increases the gas holdup. Gas holdup is unevenly distributed in the BCR where most of the gas holdup is in the centre of the column. Increasing solid particles decreases the bubble breakup rate and gas holdup. Furthermore, it was concluded that increasing the superficial gas velocity increases the average slurry temperature and volumetric heat transfer. However, decreasing the column height increases the slurry temperature and volumetric heat transfer.","PeriodicalId":385356,"journal":{"name":"Proceedings of the 8th World Congress on Mechanical, Chemical, and Material Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114102296","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}
A. Nitsenko, X. Linnik, V. Volodin, N. Burabaeva, F. Tuleutay
- In this paper, the results of studying aimed at tellurium extraction from its compound with copper in the form of oxides by the pyrometallurgical method are presented. Technical copper telluride of Kazakhmys Corporation LLP containing crystalline phases, %: Cu 7 Te 4 – 36.5; Cu 5 Te 3 – 28.5; Cu 2 Te – 12.9; Cu 2.5 SO 4 (OH) 3 ·2H 2 O – 16.2 and Cu 3 (SO 4 )(OH) 4 – 6.0 was used as an object of research. As a result of the physical and chemical research and technological experiments, the fundamental possibility of processing technical copper telluride by oxidative distillation roasting with the extraction of tellurium into a separate product has been shown. Air oxygen was used as an oxidant. It has been established that a pressure decrease at the same temperature entails an increase in the degree of tellurium extraction. However, from a technological point of view, the value of the degree of tellurium extraction (93.0–98.0 %) at all pressures (within 1 hour) is achieved at a temperature of 1100 °C. Increasing the exposure to 3 hours has a minor beneficial effect. The derived condensate is a free-flowing mixture of crystalline phases of tellurium dioxide and tellurium oxysulfate. This condensate is a middling product for further production of elemental tellurium.
本文介绍了用火法从碲与铜的化合物中以氧化物形式提取碲的研究结果。Kazakhmys公司技术碲化铜含晶相，%:Cu 7 Te 4 - 36.5;Cu 5 Te 3 - 28.5;Cu 2 Te - 12.9;以cu2.5 so4 (OH) 3·2h2o - 16.2和cu3 (so4)(OH) 4 - 6.0为研究对象。通过理化研究和工艺试验，论证了氧化蒸馏焙烧，提碲成分离产品加工工艺碲化铜的基本可能性。空气中的氧气被用作氧化剂。已经确定，在相同温度下，压力降低会导致碲的萃取程度增加。然而，从技术的角度来看，在1100℃的温度下，在所有压力下(1小时内)，碲的萃取度(93.0 - 98.0%)的值是可以达到的。将暴露时间增加到3小时会有轻微的有益效果。衍生的冷凝物是二氧化碲和氧化硫酸碲结晶相的自由流动的混合物。这种凝析液是进一步生产单质碲的中间产物。
{"title":"Development of an Oxidizing-Distillation Technology for the Extraction of Tellurium from a Tellurium-Containing Middling","authors":"A. Nitsenko, X. Linnik, V. Volodin, N. Burabaeva, F. Tuleutay","doi":"10.11159/mmme22.128","DOIUrl":"https://doi.org/10.11159/mmme22.128","url":null,"abstract":"- In this paper, the results of studying aimed at tellurium extraction from its compound with copper in the form of oxides by the pyrometallurgical method are presented. Technical copper telluride of Kazakhmys Corporation LLP containing crystalline phases, %: Cu 7 Te 4 – 36.5; Cu 5 Te 3 – 28.5; Cu 2 Te – 12.9; Cu 2.5 SO 4 (OH) 3 ·2H 2 O – 16.2 and Cu 3 (SO 4 )(OH) 4 – 6.0 was used as an object of research. As a result of the physical and chemical research and technological experiments, the fundamental possibility of processing technical copper telluride by oxidative distillation roasting with the extraction of tellurium into a separate product has been shown. Air oxygen was used as an oxidant. It has been established that a pressure decrease at the same temperature entails an increase in the degree of tellurium extraction. However, from a technological point of view, the value of the degree of tellurium extraction (93.0–98.0 %) at all pressures (within 1 hour) is achieved at a temperature of 1100 °C. Increasing the exposure to 3 hours has a minor beneficial effect. The derived condensate is a free-flowing mixture of crystalline phases of tellurium dioxide and tellurium oxysulfate. This condensate is a middling product for further production of elemental tellurium.","PeriodicalId":385356,"journal":{"name":"Proceedings of the 8th World Congress on Mechanical, Chemical, and Material Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127768796","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}
- In the present study, the capabilities of two machine learning (ML) regression methods, support vector regression (SVR) and kernel ridge regression (KRR), to predict heat transfer coefficients (HTCs) in air-cooled heat sinks (HSs) are evaluated. Within the laminar regime, HSs with different geometrical parameters and at five different Reynolds numbers are considered for the simulations. Since the focus of the present study is the proof-of-concept, the ML-based models are developed using limited numbers of input data. The input data are prepared by solving three-dimensional equations of continuity, momentum, and energy inside the channels of HSs. Results indicate that both SVR and KRR predict HTCs with excellent accuracy and within ±1.9% of simulated values. The present study suggests that both SVR and KRR are promising design tools to predict hydrothermal performances of thermal systems using sufficiently large and accurate input data. Such precise ML-based models will be excellent alternatives to expensive experimental and computational efforts that are required to develop physics-based correlations for predicting hydrothermal performances of engineering systems. (Re). Simulations are performed for each a five Re, . The training dataset is selected randomly from 83% of the input data; the remaining data are the testing dataset.
{"title":"Application of Machine Learning to Predict Thermal Performances of Heat Sinks","authors":"Betelhiem N. Mengesha, M. Shaeri, Soroush Sarabi","doi":"10.11159/htff22.138","DOIUrl":"https://doi.org/10.11159/htff22.138","url":null,"abstract":"- In the present study, the capabilities of two machine learning (ML) regression methods, support vector regression (SVR) and kernel ridge regression (KRR), to predict heat transfer coefficients (HTCs) in air-cooled heat sinks (HSs) are evaluated. Within the laminar regime, HSs with different geometrical parameters and at five different Reynolds numbers are considered for the simulations. Since the focus of the present study is the proof-of-concept, the ML-based models are developed using limited numbers of input data. The input data are prepared by solving three-dimensional equations of continuity, momentum, and energy inside the channels of HSs. Results indicate that both SVR and KRR predict HTCs with excellent accuracy and within ±1.9% of simulated values. The present study suggests that both SVR and KRR are promising design tools to predict hydrothermal performances of thermal systems using sufficiently large and accurate input data. Such precise ML-based models will be excellent alternatives to expensive experimental and computational efforts that are required to develop physics-based correlations for predicting hydrothermal performances of engineering systems. (Re). Simulations are performed for each a five Re, . The training dataset is selected randomly from 83% of the input data; the remaining data are the testing dataset.","PeriodicalId":385356,"journal":{"name":"Proceedings of the 8th World Congress on Mechanical, Chemical, and Material Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126512998","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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