Inline Non-Destructive Material Property Testing; The Future of Manufacturing

2021 ◽  
Author(s):  
David M. Wright ◽  
Dan C. Ward
Keyword(s):  
Alloy Composition ◽  
Property Testing ◽  
Data Driven ◽  
Testing Method ◽  
Future State ◽  
Medical Markets ◽  
Test Instrumentation ◽  
Proper Material ◽  
Non Destructive

Abstract Across all industries, material specifications are tightening beyond previously understood process capabilities. Slight shifts in material grade, microstructure, heat treatment, or alloy composition can significantly impact long term material integrity. This study examines the feasibility of non-contact, 100% inline magneto-inductive testing on material/components destined for the automotive, aerospace, agricultural, and medical markets to ensure proper material quality standards. To test the hypothesis that material grade, carbon content, density, and alloy composition can be accurately tested in real time during production, an experiment was conducted utilizing magneto-inductive test instrumentation and encircling coil. Throughout this experiment, and proposed future state of manufacturing, 100% of material was tested. Results yielded clear confirmation in accordance with the hypothesis. This data driven subjective approach provided the ability to accurately, efficiently, and autonomously verify proper material grade had been used for the designated product. Ensuring proper material composition and material properties without slowing production using this testing method should be considered when improved quality is desired.

A Comparative Study on Infrared Thermography during Ultrasonic Fatigue Testing of Cast Steel 42CrMo4 and Cast Aluminium Alloy AlSi7Mg

2013 ◽  
Vol 592-593 ◽  
pp. 501-504 ◽  
Author(s):  
Dominik Krewerth ◽  
Anja Weidner ◽  
Horst Biermann
Keyword(s):  
Aluminium Alloy ◽  
Infrared Thermography ◽  
Fatigue Testing ◽  
Cast Steel ◽  
Material Testing ◽  
Initiation Point ◽  
Testing Method ◽  
Cast Aluminium ◽  
Ultrasonic Fatigue ◽  
Non Destructive

The present paper illustrates a comparison of infrared thermography during ultrasonic fatigue testing of cast steel 42CrMo4 and cast aluminium alloy AlSi7Mg. Against the background of different material properties (e.g. mechanical properties as well as thermal properties) the benefit of this non-destructive material testing method in terms of determining the crack initiation point and time during fatigue testing as well as crack propagation is evaluated and discussed. Moreover, correlations between fractography and infrared thermography are performed for both materials.

Superplastic Forming and Pressure Welding of Multilayer Cellular Structures

2012 ◽  
Vol 735 ◽  
pp. 409-414 ◽  
Author(s):  
Rinat V. Safiullin
Keyword(s):  
Titanium Alloy ◽  
Solid State ◽  
Fatigue Testing ◽  
Superplastic Forming ◽  
Cellular Structures ◽  
Pressure Welding ◽  
Joint Formation ◽  
Academy Of Sciences ◽  
Non Destructive

The paper describes the results of long-term investigations on the development of the technology of superplastic forming and pressure welding (SPF/PW) conducted at the Institute for Metals Superplasticity Problems, Russian Academy of Sciences for producing standard articles of aero-space engineering, such as hollow blades, wing and shell panels. The process of solid state joint formation in titanium alloy sheets during SPF was studied. Different investigation techniques were developed. The results of the mechanical and fatigue testing as well as non-destructive inspection of hollow blades are presented. The prospects of the development of the SPF/PW technology are considered and the latest results are discussed.

scholarly journals Data driven global weather predictions at high resolutions

2021 ◽  
Author(s):  
John Taylor ◽  
Pablo Larraonndo ◽  
Bronis de Supinski
Keyword(s):  
High Resolution ◽  
Graphics Processing Units ◽  
Weather Forecasting ◽  
Weather Prediction ◽  
Atmospheric Science ◽  
Data Driven ◽  
Research And Innovation ◽  
Future State ◽  
Graphics Processing ◽  
Quantities Of Interest

Abstract Society has benefited enormously from the continuous advancement in numerical weather prediction that has occurred over many decades driven by a combination of outstanding scientific, computational and technological breakthroughs. Here we demonstrate that data driven methods are now positioned to contribute to the next wave of major advances in atmospheric science. We show that data driven models can predict important meteorological quantities of interest to society such as global high resolution precipitation fields (0.25 degrees) and can deliver accurate forecasts of the future state of the atmosphere without prior knowledge of the laws of physics and chemistry. We also show how these data driven methods can be scaled to run on super-computers with up to 1024 modern graphics processing units (GPU) and beyond resulting in rapid training of data driven models, thus supporting a cycle of rapid research and innovation. Taken together, these two results illustrate the significant potential of data driven methods to advance atmospheric science and operational weather forecasting.

scholarly journals Comparison and assessment of large-scale surface temperature in climate model simulations

2019 ◽  
Vol 5 (1) ◽  
pp. 67-85
Author(s):  
Raquel Barata ◽  
Raquel Prado ◽  
Bruno Sansó
Keyword(s):  
Surface Temperature ◽  
Seasonal Changes ◽  
Large Scale ◽  
Climate Model ◽  
Internal Variability ◽  
Temperature Variability ◽  
Data Driven ◽  
Model Simulations ◽  
Climate Model Simulations

Abstract. We present a data-driven approach to assess and compare the behavior of large-scale spatial averages of surface temperature in climate model simulations and in observational products. We rely on univariate and multivariate dynamic linear model (DLM) techniques to estimate both long-term and seasonal changes in temperature. The residuals from the DLM analyses capture the internal variability of the climate system and exhibit complex temporal autocorrelation structure. To characterize this internal variability, we explore the structure of these residuals using univariate and multivariate autoregressive (AR) models. As a proof of concept that can easily be extended to other climate models, we apply our approach to one particular climate model (MIROC5). Our results illustrate model versus data differences in both long-term and seasonal changes in temperature. Despite differences in the underlying factors contributing to variability, the different types of simulation yield very similar spectral estimates of internal temperature variability. In general, we find that there is no evidence that the MIROC5 model systematically underestimates the amplitude of observed surface temperature variability on multi-decadal timescales – a finding that has considerable relevance regarding efforts to identify anthropogenic “fingerprints” in observational surface temperature data. Our methodology and results present a novel approach to obtaining data-driven estimates of climate variability for purposes of model evaluation.

scholarly journals Hippocampal sharp wave-ripples and the associated sequence replay emerge from structured synaptic interactions in a network model of area CA3

2021 ◽  
Author(s):  
Andras Ecker ◽  
Bence Bagi ◽  
Eszter Vertes ◽  
Orsolya Steinbach-Nemeth ◽  
Maria Rita Karlocai ◽  
...  
Keyword(s):  
Place Cells ◽  
Data Driven ◽  
Long Term Memory ◽  
Term Memory ◽  
Cellular Adaptation ◽  
Sharp Wave ◽  
Synaptic Interactions ◽  
Area Ca3 ◽  
Reversed Order

Hippocampal place cells are activated sequentially as an animal explores its environment. These activity sequences are internally recreated ("replayed"), either in the same or reversed order, during bursts of activity (sharp wave-ripples; SWRs) that occur in sleep and awake rest. SWR-associated replay is thought to be critical for the creation and maintenance of long-term memory. We sought to identify the cellular and network mechanisms of SWRs and replay by constructing and simulating a data-driven model of area CA3 of the hippocampus. Our results show that the structure of recurrent excitatory interactions established during learning not only determines the content of replay, but is essential for the generation of the SWRs as well. We find that bidirectional replay requires the interplay of the experimentally confirmed, temporally symmetric plasticity rule, and cellular adaptation. Our model provides a unifying framework for diverse phenomena involving hippocampal plasticity, representations, and dynamics.

scholarly journals Photoacoustic spectroscopy allows to make correlations between blood p450 cytochrome and glycemia in type 1 experimental diabetes

2021 ◽  
Vol 2090 (1) ◽  
pp. 012152
Author(s):  
L I Olvera ◽  
G C Villanueva ◽  
E Romero ◽  
A Cruz
Keyword(s):  
Photoacoustic Spectroscopy ◽  
Diabetes Complications ◽  
Venous Blood ◽  
Future Studies ◽  
Patients With Diabetes ◽  
Male Wistar Rats ◽  
Experimental Type ◽  
Non Destructive

Abstract Diabetes is the eight-cause death worldwide. The cause of death of patients with diabetes is mostly the long-term complications, that are not easy to detect opportunely. In previous studies, we applied photoacoustic spectroscopy (PAS), a non-destructive technique, to detect several components of blood. The goal of the study was to apply the phase-resolved method (PRM), on blood optical absorption spectra obtained by PAS, to analyse blood components in experimental type 1 diabetes. Diabetes was produced in male Wistar rats through the administrations of streptozotocin (STZ). Venous blood samples were obtained one, two, four and eight weeks after STZ. PRM applied to spectra allowed to detect p450 cytochrome. There was a significant and positive correlation between glycaemia and p450 cytochrome (p=0.001). Since p450 cytochrome participates in detoxification function, results indicate that glycaemia could affect detoxification. It will be important in future studies to study the implications of those results on the development of diabetes complications. The novelty of the study was to use PAS to find out if there was any correlation between spectroscopy variables and glycaemia. It is concluded that PRM applied to PAS is a suitable technology to study p450 cytochrome in diabetes.

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