scholarly journals Automated High-Pressure Atline Analysis of Photo-High-P,T Vitamin D3 Microfluidic Synthesis

2021 ◽  
Vol 3 ◽  
Author(s):  
Marc Escribà-Gelonch ◽  
Nghiep Nam Tran ◽  
Volker Hessel
Keyword(s):  
High Performance ◽  
Process Analytical Technology ◽  
Control Process ◽  
Process Intensification ◽  
Flow Chemistry ◽  
Critical Parameters ◽  
Primary Responsibility ◽  
Feasible Option ◽  
Relevant Topic ◽  
Pressure Independent

Process analytical technology has become a relevant topic in both industry and academia as a mechanism to control process quality by measuring critical parameters; being mainly applied in pharmaceutical industry. An emerging topic is process monitoring with subsequent process automation in flow chemistry using inline, online and atline analyzers. Flow chemistry often deliberately and favorably uses harsh conditions (termed Novel Process Windows) to achieve process intensification which raises the need for sampling under these conditions. This demands for setting in place a stabilization of the sample before exposing it to the processing. Ignoring this may result in being unable to use inline/online analytics and posing the need for a separation step before quantitative analysis, leaving atline analysis as the only feasible option. That means that sampling and connected operations need also to be automated. This is where this study sets in, and this is enabled by a modified high-performance liquid chromatography (HPLC) autosampler coupled to the photo-high-p,T flow synthesis of vitamin D3. It shows that sampling variables, such as decompression speed, can be even more critical in terms of variability of results than process variables such as concentration, pressure, and temperature. The modification enabled the autosampler fully automated and unattended sampling from the reactor and enabled pressure independent measurements with 89% accuracy, >95% reproducibility, and >96% repeatability, stating decompression speed as the primary responsibility for measurements’ uncertainty.

Fuzzy control of coagulation reaction through streaming current monitoring

1997 ◽  
Vol 36 (4) ◽  
pp. 127-134 ◽  
Author(s):  
J. C. Liu ◽  
M. D. Wu
Keyword(s):  
Fuzzy Logic Controller ◽  
Treatment Plant ◽  
Control Process ◽  
Water Treatment Plant ◽  
Critical Parameters ◽  
Flow Mode ◽  
Raw Water ◽  
Streaming Current ◽  
On Line ◽  
Current Monitoring

A fuzzy logic controller (FLC) incorporating the streaming current detector (SDC) was utilized in the automatic control of the coagulation reaction. Kaolinite was used to prepare synthetic raw water, and ferric chloride was used as the coagulant. The control set point was decided at a streaming current (SC) of −0.05 and pH of 8.0 from jar tests, zeta potential and streaming current measurements. A bench-scale water treatment plant with rapid mix, flocculation, and sedimentation units, operated in a continuous-flow mode, was utilized to simulate the reaction. Two critical parameters affecting the coagulation reaction, i.e., pH and streaming current, were chosen as process outputs; while coagulant dose and base dose were chosen as control process inputs. They were on-line monitored and transduced through a FLC. With raw water of initial turbidity of 110 NTU, residual turbidity of lower than 10 NTU before filtration was obtained. Results show that this combination functions satisfactorily for coagulation control.

Application of High Performance Electro-Hydraulic Synchronous Servo System on NC Broaching Machine

2013 ◽  
Vol 721 ◽  
pp. 497-500
Author(s):  
Guo Jin Chen ◽  
Jing Ni ◽  
Ting Ting Liu ◽  
Ming Xu
Keyword(s):  
High Performance ◽  
Control Process ◽  
Servo System ◽  
Numerical Control ◽  
Servo Drive ◽  
Loop Control ◽  
Performance Accuracy ◽  
Drive Control ◽  
Hydraulic Servo ◽  
Output Quantity

Aiming at the lower performance, accuracy and efficiency of the existing motion control process for the traditional broaching machine, the paper studies the high-performance dual-hydraulic synchronous servo drive control technology. The synchronous electro-hydraulic servo system forms the closed loop control by the detection and feedback of the output quantity. It eliminates and restrains largely the influence of the adverse factors to obtain the high-precision synchronous driving performance. The numerical control system based on the real-time error compensation and the intelligent control to the auxiliary machinery is developed. It is used for the CNC broaching machine to make the steady-state synchronous displacement error of the double cylinders be ≤ 0.5mm.

scholarly journals Synthesis of an Addition-Crosslinkable, Silicon-Modified Polyolefin via Reactive Extrusion Monitored by In-Line Raman Spectroscopy

Polymers ◽  
2021 ◽  
Vol 13 (8) ◽  
pp. 1246
Author(s):  
Steffen Ulitzsch ◽  
Tim Bäuerle ◽  
Mona Stefanakis ◽  
Marc Brecht ◽  
Thomas Chassé ◽  
...  
Keyword(s):  
Raman Spectroscopy ◽  
High Performance ◽  
Process Analytical Technology ◽  
Statistical Design ◽  
Reactive Extrusion ◽  
Statistical Design Of Experiments ◽  
Grafting Efficiency ◽  
Grafting Reaction ◽  
Central Composite Experimental Design ◽  
Process Factors

We present the modification of ethylene-propylene rubber (EPM) with vinyltetra-methydisiloxane (VTMDS) via reactive extrusion to create a new silicone-based material with the potential for high-performance applications in the automotive, industrial and biomedical sectors. The radical-initiated modification is achieved with a peroxide catalyst starting the grafting reaction. The preparation process of the VTMDS-grafted EPM was systematically investigated using process analytical technology (in-line Raman spectroscopy) and the statistical design of experiments (DoE). By applying an orthogonal factorial array based on a face-centered central composite experimental design, the identification, quantification and mathematical modeling of the effects of the process factors on the grafting result were undertaken. Based on response surface models, process windows were defined that yield high grafting degrees and good grafting efficiency in terms of grafting agent utilization. To control the grafting process in terms of grafting degree and grafting efficiency, the chemical changes taking place during the modification procedure in the extruder were observed in real-time using a spectroscopic in-line Raman probe which was directly inserted into the extruder. Successful grafting of the EPM was validated in the final product by 1H-NMR and FTIR spectroscopy.

scholarly journals Parametric Analysis on Seismic Performance of Hybrid Precast Concrete Beam-Column Joint

2020 ◽  
Vol 2020 ◽  
pp. 1-16
Author(s):  
H.-K. Choi ◽  
Grzegorz Golewski
Keyword(s):  
High Performance ◽  
Precast Concrete ◽  
Plastic Hinge ◽  
Cement Composite ◽  
Fe Analysis ◽  
Experimental Results ◽  
Critical Parameters ◽  
Detailed Model ◽  
Plate Length ◽  
Bolt Stress

In this paper, a nonlinear finite element (FE) analysis of high-performance hybrid system (HPHS) beam-column connections is presented. The detailed experimental results of the ten half-scale hybrid connections with limited seismic detailing have been discussed in a different paper. However, due to the inherent complexity of HPHS beam-column joints and the unique features of the tested specimens, the experimental study was not comprehensive enough. The new connection (HPHS) detail suggested in this study is characterized by ductile connection, steel connectors, and engineered cementitious composite (ECC) which is a kind of high-performance fiber reinforced cement composite with multiple fine cracks (HPFRCCs). Therefore, in this paper, FE analysis results are compared with experimental results from the cycle tests of the two specimens (RC and PC) to assess model accuracy, and detailed model descriptions are presented, including the determination of stiffness and strength. The critical parameters influencing the joint’s behavior are the axial load on column, beam connection steel plate length, inner bolt stress contribution, and plastic hinge area.

scholarly journals Fiber Bragg grating modeling, simulation and characteristics with different grating lengths

2007 ◽  
Vol 3 (2) ◽  
Author(s):  
Ho Sze Phing ◽  
Jalil Ali ◽  
Rosly Abdul Rahman ◽  
Bashir Ahmed Tahir
Keyword(s):  
Fiber Bragg Grating ◽  
Matrix Method ◽  
High Performance ◽  
Fiber Bragg Grating Sensor ◽  
Critical Parameters ◽  
Bragg Grating ◽  
Fiber Gratings ◽  
Coupled Mode ◽  
High Performance Fiber ◽  
Bragg Grating Sensor

In this paper we perform a simulation of fiber Bragg grating sensor with different grating lengths. It is shown that the grating length represents as one of the critical parameters in contributing to a high performance fiber Bragg grating sensor. The simulated fiber gratings with different lengths were analyzed and designed by calculating reflection and transmission spectra, and the bandwidth. Such simulations are based on solving coupled mode equations that describe the interaction of guided modes. The coupled mode equations are solved by the Transfer Matrix Method (a fundamental matrix method).

KI:STE Project − AI Strategy for Earth System Data

2021 ◽  
Author(s):  
Scarlet Stadtler ◽  
Julia Kowalski ◽  
Markus Abel ◽  
Ribana Roscher ◽  
Susanne Crewell ◽  
...  
Keyword(s):  
High Performance ◽  
Rapid Development ◽  
Environmental Data ◽  
Earth System ◽  
Strongly Coupled ◽  
Learning Platform ◽  
System Data ◽  
Relevant Topic ◽  
Spatio Temporal ◽  
Algorithmic Approaches

<p>Artificial intelligence (AI) methods currently experience rapid development and are also used more and more frequently in environmental and Earth system sciences. To date however, this is often done in the context of isolated rather than systematic solutions. In particular, for researchers there is often a discrepancy between the requirements of a solid and technically sound environmental data analysis and the availability of modern AI methods such as deep learning. Their systematic use is not yet established in environmental and Earth system sciences.</p><p>The recently started KI:STE project bridges this gap with a dedicated strategy that combines both, the development of AI applications and a strong training and network concept, thereby covering  different relevant aspects of environmental and Earth system research. It creates the technical prerequisites to make high-performance AI applications on environmental data portable for future users and to establish environmental AI as a key technology. </p><p>Specifically, within KI:STE an AI-platform is envisioned which unifies machine learning (ML) workflows designed to study five core Earth system topics: cloud variability, hydrology, earth surface processes, vegetation health and air quality. All of them are strongly coupled and will profit from ML, e.g. to extend locally available information into global maps, or the track the interplay of spatio-temporal variability on different scales along process cascades. Besides being already connected across disciplines in the classical sense, KI:STE aims to furthermore bridge between these different topics by jointly addressing cutting edge ML research questions beyond pure algorithmic approaches. In particular, we will put emphasize on an explainable AI approach, which itself is a yet to be explored highly relevant topic within the Earth system sciences. It has the potential to connect the interdisciplinary work on yet another level.</p><p>KI:STE will also launch an e-learning platform in order to support the usage of the AI-platform as well as to communicate the knowledge to adequately use ML techniques within the different Earth system science domains.</p>

Critical Parameters for Fuzzy Data Mining

2015 ◽  
pp. 1-18
Author(s):  
Sinchan Bhattacharya ◽  
Vishal Bhatnagar
Keyword(s):  
Data Mining ◽  
Fuzzy Sets ◽  
High Performance ◽  
Rough Set Theory ◽  
Inductive Logic ◽  
Critical Parameters ◽  
Maximum Efficiency ◽  
Fuzzy Data ◽  
Use Of Data ◽  
Performance Computing

Research on data mining is increasing at an incessant rate and to improve its effectiveness other techniques have been applied such as fuzzy sets, rough set theory, knowledge representation, inductive logic programming, or high-performance computing. Fuzzy logic due to its proficiency in handling uncertainty has gained its importance in a variety of applications in combination with the use of data mining techniques. In this chapter we take this association a notch further by examining the parameters which allow fuzzy sets and data mining to be combined into what has come to be known as fuzzy data mining. Analyzing and understanding these critical parameters is the main purpose of this chapter, so as to acquire maximum efficiency in applying the same which impelled the authors to work extensively and find out the crucial parameters essential to the application of fuzzy data mining.

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