24,020 research outputs found
Mech-ABM Raw and Processed Data
No full textThis file includes the primary data generated from the Mech-ABM which was mostly used in the paper titled "Heterogeneity in The Mechanical Properties of Integrins Determines Mechanotransduction Dynamics in Bone Osteoblasts".These include data in the following formats:CSVXML.PZFX (summaries of the raw data and processed data)As the full Mech-ABM generates a high magnitude of data (in terabytes), thus only samples have been uploaded. For additional raw data contact the authors of the published paper</div
MECH 2700 Robotic Welding
No full textCourse Description:This course was developed by Roane State Community College and The Center for Advanced Automotive Technology (CAAT). In this course students will be introduced to robotic welding systems and learn how to perform basic procedures. Students will learn how to create welding routines, program weld paths, and be able to store and retrieve programs and parameters. Students will learn to program a welding robot through a teach pendant and simulation software, edit programs, set weld schedules and learn basic operator controls and indicators on the teach pendant and operator panel. This course also provides fundamental safety precautions while programming and operating the robotic equipment.Course Contents:Course materials include a 5-page syllabus, 14 PowerPoint lectures, and 15 lesson plans. The syllabus includes a course description, course learning outcomes, a course topics roadmap, and other course related information.&nbsp;The lessons plans include objectives; a list of materials, equipment, and supplies&nbsp;needed; instructional resources; a list of activities and demonstrations; teaching suggestions, and assessment information.&nbsp;Below is a list of the files contained within the .zip attachment. The size of each file is included in parenthesis.&nbsp;MECH2700_Robotic_Welding (35 files, 50 MB)LecturesIntroduction and Safety (Mech 2700 Robotic Welding &nbsp;PPT1 &nbsp;Introduction and Safety.pptx 6.8 MB)Basic Robot Operations (Mech 2700 Robotic Welding &nbsp;PPT2 Basic Robot Operation.pptx 8.1 MB)WeldPRO Software: Teach Pendant Operation (Mech 2700 Robotic Welding &nbsp;PPT3 &nbsp;Teach Pendant Operation.pptx 5.2 MB)WeldPRO Software: Power Up, Jogging, and Initial Setup (Mech 2700 Robotic Welding &nbsp;PPT4 Power up Jogging Initial Set Up.pptx 4.5 MB)WeldPRO Software: Error and Fault Recovery (Mech 2700 Robotic Welding &nbsp;PPT5 &nbsp;Error and Fault Recovery.pptx 1.4 MB)WeldPRO Software: Frames (Mech 2700 Robotic Welding &nbsp;PPT6 &nbsp;Frames.pptx 3.6 MB)WeldPRO Software: Motion Programs (Mech 2700 Robotic Welding &nbsp;PPT7 &nbsp;Motion Programs.pptx 1.5 MB)Motion Instructions (Mech 2700 Robotic Welding &nbsp;PPT8 Motion Instructions.pptx 3.2 MB)Copy and Editing Programs (Mech 2700 Robotic Welding &nbsp;PPT9 Copying and Editing Programs.pptx 2 MB)Branching Instructions (Mech 2700 Robotic Welding &nbsp;PPT10 Branching Instructions.pptx 1.2 MB)Position Registers (Mech 2700 Robotic Welding &nbsp;PPT11 Position Registers.pptx 1.6 MB)Inputs and Outputs (Mech 2700 Robotic Welding &nbsp;PPT12 Inputs and Outputs.pptx 3.4 MB)Macros (Mech 2700 Robotic Welding &nbsp;PPT13 Macros.pptx 1.2 MB)Program Adjust (Mech 2700 Robotic Welding &nbsp;PPT14 Program Adjust.pptx 1 MB)Thumbnails (Thumbs.db 15 KB)Lesson PlansLesson Plan 1 (Lesson Plan Week 1 MECH 2700.docx 186 KB)Lesson Plan 2 (Lesson Plan Week 2 MECH 2700.docx 353 KB)Lesson Plan 3 (Lesson Plan Week 3 MECH 2700.docx 353 KB)Lesson Plan 4 Lesson Plan Week 4 MECH 2700.docx 353 KB)Lesson Plan 5 (Lesson Plan Week 5 MECH 2700.docx 353 KB)Lesson Plan 6 (Lesson Plan Week 6 MECH 2700.docx 353 KB)Lesson Plan 7 (Lesson Plan Week 7 MECH 2700.docx 353 KB)Lesson Plan 8 (Lesson Plan Week 8 MECH 2700.docx 353 KB)Lesson Plan 9 (Lesson Plan Week 9 MECH 2700.docx 353 KB)Lesson Plan 10 (Lesson Plan Week 10 MECH 2700.docx 353 KB)Lesson Plan 11 (Lesson Plan Week 11 MECH 2700.docx 353 KB)Lesson Plan 12 (Lesson Plan Week 12 MECH 2700.docx 353 KB)Lesson Plan 13 (Lesson Plan Week 13 MECH 2700.docx 353 KB)Lesson Plan 14 (Lesson Plan Week 14 MECH 2700.docx 353 KB)Lesson Plan 15 (Lesson Plan Week 15 MECH 2700.docx 353 KB)SyllabusSyllabus, Robotic Welding, MECH 2700 (Syllabus, Robotic Welding, MECH 2700.docx 229 KB
Growth Rates and Variances of Unexploited Wolf Populations in Dynamic Equilibria: Data, R Code, and Supporting Results
No full textThis dataset contains four files. PopulationModels.R is an R script defining functions used to fit density-independent and Ricker population models to associated time series data. With these functions, population measurements can be modeled under three different measurement assumptions: i) measured without error; ii) measured with Poisson error; or iii) measured with log-normal error. MechFieberg.R is a R script that will run all analyses supporting the findings in Mech and Fieberg (2014). MechFieberg.html is a summary of the output expected when running the MechFieberg.R script. Wolfdat.csv is the raw data file containing the wolf home range measurements. The four columns in this data correspond to the year of measurement (YR), and the location of measurement: Denali National Park (Denali), Isle Royale (IsleRoyale), and Superior National Forest (SNF).These files contain data and R code (along with associated output from running the code) supporting all results reported in: Mech, D. and J. Fieberg. 2014. Growth Rates and Variances of Unexploited Wolf Populations in Dynamic Equilibria. Wildlife Society Bulletin. In Mech and Fieberg (2014), we analyzed natural, long-term, wolf-population-density trajectories totaling 130 years of data from three areas: Isle Royale National Park in Lake Superior, Michigan; the east-central Superior National Forest in northeastern Minnesota; and Denali National Park, Alaska. We fit density-independent and Ricker models to each time series, allowing for 3 different assumptions regarding observation error (no error, Poisson or Log-normal observation error). We suggest estimates of the population-dynamic parameters can serve as benchmarks for comparison with those calculated from other wolf populations repopulating other areas.Fieberg, John R; Mech, David. (2014). Growth Rates and Variances of Unexploited Wolf Populations in Dynamic Equilibria: Data, R Code, and Supporting Results. Retrieved from the University Digital Conservancy, http://dx.doi.org/10.13020/D6RP4N
Passive scalar mixing of a turbulent jet emitted into homogeneous, isotropic turbulence
No full textAlthough most jets, whether they be natural or industrial in origin, are emitted into a turbulent environment, almost all previous research on turbulent jets has dealt with jets emitted into quiescent or laminar background flows. The present work extends the work of Khorsandi, Gaskin and Mydlarski, J. Fluid Mech., 2013 – who studied the effect of background turbulence on the velocity field of a turbulent jet emitted into turbulent surroundings – to the study of passive scalar mixing of a jet released into a turbulent flow. To this end, the experiments described herein use planar laser-induced fluorescence to study the mixing of a (high-Schmidt-number) passive scalar within a turbulent jet that is emitted into a quasi-homogeneous, isotropic, zero-mean-flow turbulent background. We examine herein statistics of the jet’s scalar field, and compare them to those of a jet emitted into a quiescent background
Female wolf breeder types in the Superior National Forest, 1972–2013 based on Mech et al. [24] formula<sup>a</sup>.
No full textFemale wolf breeder types in the Superior National Forest, 1972–2013 based on Mech et al. [24] formulaa.</p
Settling of finite-size particles in isotropically forced, homogeneous turbulence: interface-resolved simulations
No full textWe have simulated the gravity-induced settling of finite-size particles in a turbulent background flow which is forced in a statistically-stationary fashion. The simulations are accurately resolving the solid-fluid interface with the aid of an immersed boundary technique [1]. The parameters of the simulation are (apart from background turbulence) identical to those of reference [2], where particle clustering was observed at a Galileo number of 178 and a solid volume fraction of 0.005. In the present case, it is found that a relative turbulence intensity of 0.24 leads to the disappearance of the clusters; as a consequence, the increase in average particle settling velocity found in [2] also vanishes. [1] M. Uhlmann. An immersed boundary method with direct forcing for the simulation of particulate flows. J. Comput. Phys., 209(2):448–476, 2005. [2] M. Uhlmann and T. Doychev. Sedimentation of a dilute suspension of rigid spheres at intermediate Galileo numbers: the effect of clustering upon the particle motion. J. Fluid Mech., 752:310–348, 2014
Numerical simulation of a flow around an unmanned aerial vehicle
No full textIn this present work, a numerical simulation on a flow around an UAV is presented. The CFD is used to obtain evaluations on the coefficients of lift and drag with flow velocity of 20 meters per second for various angles of incidence. The model of Spalart-Allmaras turbulence is used for the investigation of the complex flow around the UAV. The results of the CFD indicate that the complex structure of the flow is well compared with reality.http://dx.doi.org/10.5755/j01.mech.17.2.339Šiame darbe pateikiamas bepilotinių lėktuvų skraidymo skaitmeninis modeliavimas. CFD metodas taikomas kilimo ir stabdymo koeficientams nustatyti esant 20 m/s greičiui ir įvairiems atakos kampams. Kompleksiškai tiriant bepiločio lėktuvo skraidymą buvo panaudotas Spalarto ir Allmaraso turbulentinis modelis. Tyrimo rezultatai parodė, kad apskritai srauto struktūra gerai sutampa su nustatyta eksperimentiškai.http://dx.doi.org/10.5755/j01.mech.17.2.33
Table1_MRI-MECH: mechanics-informed MRI to estimate esophageal health.DOCX
No full textDynamic magnetic resonance imaging (MRI) is a popular medical imaging technique that generates image sequences of the flow of a contrast material inside tissues and organs. However, its application to imaging bolus movement through the esophagus has only been demonstrated in few feasibility studies and is relatively unexplored. In this work, we present a computational framework called mechanics-informed MRI (MRI-MECH) that enhances that capability, thereby increasing the applicability of dynamic MRI for diagnosing esophageal disorders. Pineapple juice was used as the swallowed contrast material for the dynamic MRI, and the MRI image sequence was used as input to the MRI-MECH. The MRI-MECH modeled the esophagus as a flexible one-dimensional tube, and the elastic tube walls followed a linear tube law. Flow through the esophagus was governed by one-dimensional mass and momentum conservation equations. These equations were solved using a physics-informed neural network. The physics-informed neural network minimized the difference between the measurements from the MRI and model predictions and ensured that the physics of the fluid flow problem was always followed. MRI-MECH calculated the fluid velocity and pressure during esophageal transit and estimated the mechanical health of the esophagus by calculating wall stiffness and active relaxation. Additionally, MRI-MECH predicted missing information about the lower esophageal sphincter during the emptying process, demonstrating its applicability to scenarios with missing data or poor image resolution. In addition to potentially improving clinical decisions based on quantitative estimates of the mechanical health of the esophagus, MRI-MECH can also be adapted for application to other medical imaging modalities to enhance their functionality.</p
Putzwolle ist das beste Putzmaterial!! Rud. Horkheimer Söhne, Mech. Putzwollfabrik, Rottenburg a. Neckar
No full textPUTZWOLLE IST DAS BESTE PUTZMATERIAL!! RUD. HORKHEIMER SÖHNE, MECH. PUTZWOLLFABRIK, ROTTENBURG A. NECKAR
Putzwolle ist das beste Putzmaterial!! Rud. Horkheimer Söhne, Mech. Putzwollfabrik, Rottenburg a. Neckar ( -
Rud. Horkheimer Söhne, mech. Putzwollfabrik Rottenburg a. Neckar. Putzwolle ist das beste Putzmaterial!!!
No full textRUD. HORKHEIMER SÖHNE, MECH. PUTZWOLLFABRIK ROTTENBURG A. NECKAR. PUTZWOLLE IST DAS BESTE PUTZMATERIAL!!!
Rud. Horkheimer Söhne, mech. Putzwollfabrik Rottenburg a. Neckar. Putzwolle ist das beste Putzmaterial!!! ( -
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