scholarly journals Modeling the Effect of Tramp Oil Contamination on Selective Component Depletion in Metalworking Fluid Systems

2003 ◽  
Vol 125 (1) ◽  
pp. 85-94 ◽  
Author(s):  
Joseph J. Eppert ◽  
N. Rajagopalan ◽  
Richard E. DeVor ◽  
Shiv G. Kapoor
Keyword(s):  
Partition Coefficient ◽  
Mass Balance ◽  
Machining Process ◽  
Physical Interaction ◽  
Industrial Case Study ◽  
Fluid Systems ◽  
Metalworking Fluid ◽  
Water Partition Coefficient ◽  
Useful Life

Functional component depletion and physical interaction of contaminants with the machining process are thought to be the primary determinants of metalworking fluid useful life. An oil/water partition coefficient and mass balance based model is derived that is capable of accounting for the effect of tramp oil induced extraction of metalworking fluid components. After developing general expressions for the predictive model, the magnitude of extraction for a synthetic metalworking fluid is investigated. The model is then used to predict system concentrations over time in the presence of such metalworking fluid contaminants and is verified via laboratory experimentation and an industrial case study. The partition coefficient/mass balance modeling procedure is further utilized to determine the amounts and frequency required for tankside addition of metalworking fluid components, while accounting for depletion by the tramp oil mechanism.

scholarly journals The Effect of Chip Adsorption on Selective Depletion From a Multi-Component Synthetic Metalworking Fluid

2003 ◽  
Vol 125 (4) ◽  
pp. 703-708 ◽  
Author(s):  
Joseph J. Eppert ◽  
Richard E. DeVor ◽  
Shiv G. Kapoor ◽  
N. Rajagopalan
Keyword(s):  
Langmuir Isotherm ◽  
Metal Cutting ◽  
Adsorption Mechanism ◽  
Experimental Measurements ◽  
Industrial Case Study ◽  
Particulate Contamination ◽  
Fluid Systems ◽  
Metalworking Fluid ◽  
Selective Depletion

Certain components found in metalworking fluid formulations are known to be prone to selective depletion via adsorption onto the surfaces of particulate generated during metal cutting operations. The characteristics of adsorption for a multi-component synthetic metalworking fluid are investigated in order to determine the affect that machining particulate contamination has on component depletion from this fluid. Experimental measurements indicate that the corrosion inhibiting component of the formulation is especially prone to depletion via the adsorption mechanism. A Langmuir isotherm/mass balance based predictive model is developed to determine the effect of chip adsorption on depletion from industrial metalworking fluid systems and is experimentally verified. An industrial case study is applied to further investigate selective component depletion via the adsorption mechanism.

scholarly journals QSPR modelling of the octanol/water partition coefficient of organometallic substances by optimal SMILES-based descriptors

2009 ◽  
Vol 7 (4) ◽  
pp. 846-856 ◽  
Author(s):  
Andrey Toropov ◽  
Alla Toropova ◽  
Emilio Benfenati
Keyword(s):  
Partition Coefficient ◽  
Organometallic Compounds ◽  
Applicability Domain ◽  
Training Set ◽  
Input Line ◽  
Test Set ◽  
Water Partition Coefficient ◽  
Definition Of

AbstractUsually, QSPR is not used to model organometallic compounds. We have modeled the octanol/water partition coefficient for organometallic compounds of Na, K, Ca, Cu, Fe, Zn, Ni, As, and Hg by optimal descriptors calculated with simplified molecular input line entry system (SMILES) notations. The best model is characterized by the following statistics: n=54, r2=0.9807, s=0.677, F=2636 (training set); n=26, r2=0.9693, s=0.969, F=759 (test set). Empirical criteria for the definition of the applicability domain for these models are discussed.

Hybrid remaining useful life prediction method. A case study on railway D-cables

2021 ◽  
pp. 107746
Author(s):  
Yu Zang ◽  
Wei Shangguan ◽  
Baigen Cai ◽  
Huasheng Wang ◽  
Michael. G. Pecht
Keyword(s):  
Life Prediction ◽  
Prediction Method ◽  
Remaining Useful Life ◽  
Useful Life

scholarly journals On systematically building a controlled natural language for functional requirements

2021 ◽  
Vol 26 (4) ◽  
Author(s):  
Alvaro Veizaga ◽  
Mauricio Alferez ◽  
Damiano Torre ◽  
Mehrdad Sabetzadeh ◽  
Lionel Briand
Keyword(s):  
Information System ◽  
Natural Language ◽  
Qualitative Methodology ◽  
Case Study Research ◽  
Empirical Evaluation ◽  
Functional Requirements ◽  
Industrial Case Study ◽  
Requirements Specifications ◽  
Financial Domain

AbstractNatural language (NL) is pervasive in software requirements specifications (SRSs). However, despite its popularity and widespread use, NL is highly prone to quality issues such as vagueness, ambiguity, and incompleteness. Controlled natural languages (CNLs) have been proposed as a way to prevent quality problems in requirements documents, while maintaining the flexibility to write and communicate requirements in an intuitive and universally understood manner. In collaboration with an industrial partner from the financial domain, we systematically develop and evaluate a CNL, named Rimay, intended at helping analysts write functional requirements. We rely on Grounded Theory for building Rimay and follow well-known guidelines for conducting and reporting industrial case study research. Our main contributions are: (1) a qualitative methodology to systematically define a CNL for functional requirements; this methodology is intended to be general for use across information-system domains, (2) a CNL grammar to represent functional requirements; this grammar is derived from our experience in the financial domain, but should be applicable, possibly with adaptations, to other information-system domains, and (3) an empirical evaluation of our CNL (Rimay) through an industrial case study. Our contributions draw on 15 representative SRSs, collectively containing 3215 NL requirements statements from the financial domain. Our evaluation shows that Rimay is expressive enough to capture, on average, 88% (405 out of 460) of the NL requirements statements in four previously unseen SRSs from the financial domain.

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