Effect of ultrasonic welding process parameters on seam strength of PVC-coated hybrid textiles for weather protection

Using a lapped seam, PVC-coated hybrid textiles with uniform thickness were bonded by continuous ultrasonic welding and conventional joining method with the help of hot air tape welding technique for weather protection purposes. Three fundamental sewing parameters at two distinct levels and three primary welding parameters at three levels based on 6 and 12 mm welding widths were used. To consider the effect of welding and sewing parameters on seam strength, full factorial designs of experiments were designed, fabricated, and tested. The thermal behavior and possibility of chemical conversion in the welding zone under the influence of ultrasonic vibrations were examined. Variation in width of heat-affected zone of weld seam was measured. The seam strength of ultrasonic weld seam compared with that of conventional seams, and superior seam strength yielding parametric levels were assessed. The parametric influence of both joining techniques on seam quality and their tendencies in the relationship were analyzed statistically. The weld seam strength (1256.392 and 2116.93 N/50 mm) was optimized numerically and identified its trend with the variation of the weld seam. The discovered relationship led to the conclusion that the variation in the weld seam can be used to estimate the tensile strength of the weld seam through the developed effective numerical model as a non-destructive testing method, and its outcome was successful as a destructive testing method. The result shows that the ultrasonic weld seam provided a higher tensile strength ( > 75%) than the conventional seam for both evaluated welding widths and obtained statistically significant results.

Bounding the Solution Space of Complex Systems in Terms of Non-Numeric and\or Uncontrollable Scenario Variables

This paper describes an approach to blend several qualitative and quantitative methods to establish the boundaries of complex systems in terms of uncontrollable, non-numeric variables. Decision makers increasingly encounter layered, multidimensional, interconnected issues that contain unknown unknowns, vast uncertainties, and ill-defined lines of demarcation between the beginning and the end of the problem. The inexactness of boundaries in a systems problem is a result of not knowing important variables, existence of uncontrollable variables, and near-uncountable significant interactions among the variables. Furthermore, complexities and systems challenges arise from unexpected emergent behavior(s) that are often the primary concerns of systems engineers. The ability to investigate uncontrollable variables and their interactions with the system of interest is a critical step for bounding the system problem and defining the solution space. Thus, this paper focuses on developing a means for systematically examining these variables. By incorporating scenario-based computer simulations, scenario discretization, and customized designs of experiments, the authors offer systems engineers and scientists an approach for defining a viable solution space of a complex problem by developing constraint equations from uncontrollable, non-numeric variables.

Optimization of Piston Grooves, Bridges on Cylinder Head, and Inlet Valve Masking of Home-Fueled Diesel Engine by Response Surface Methodology

Naturally replenished biodiesel fuels are more precise in place of diesel engine applications as they have complying thermal properties, which are extensively used by various researchers. However, there is necessity to optimize their utility to meet stringent emission norms as per Bharat Stage VI (BS VI) and Euro 6. From the exhaustive survey on the studies, number of piston grooves (NG), number of grooves-n-bridges on cylinder head (Gr-Br), and inlet valve masking (IVM) using the response surface methodologies (RSM) technique have not been reported on the competence, emissions, and combustion attributes of diesel engines running on Honge oil methyl ester (HOME), hence this is an identified gap in literature. The present simulation work is for optimizing the performance and lessoning exhaust emitted from the diesel prime mover tested on non-conventional and petro fuels. Experimentation was carried out to inquest the competence, combustion, and emittance of a vertical cylinder, overhead valve, water cooling, open or induction swirl diesel engine running on HOME as the injecting fuel. The object of the present effort is to optimize competence of diesel engines via a statistics inquest called designs of experiments (DoE). To curtail the diverse variations to be experimented on, full factorial designs (FFDs) array was employed. The response surface methodologies (RSM)-based nonlinear or quadratic predictors establish the relation between the input parameters and proposed attributes. The RSM-based mathematical predictors are established to prognosticate the distinguished engine output attributes at 95% confidence interval. The response surface assay discovered that a combination of 2B 3G, ‘IVM’ of 900, and ‘NG’ of six grooves yields highest brake thermal efficiency (BTE), lessoning smoke, carbon monoxide (CO), and hydrocarbon (HC), but nitrogenous oxides (NOx) emissions increased slightly. Additionally, combustion attributes, such as Ignition delay (ID) and combustion duration (CD), were lessoned, but peak pressure (PP) and heat release rate (HRR) had a higher contrast to performance of HOME biodiesel in a conventional CI engine.

Monitoring the Zero-Inflated Time Series Model of Counts with Random Coefficient

In this research, we consider monitoring mean and correlation changes from zero-inflated autocorrelated count data based on the integer-valued time series model with random survival rate. A cumulative sum control chart is constructed due to its efficiency, the corresponding calculation methods of average run length and the standard deviation of the run length are given. Practical guidelines concerning the chart design are investigated. Extensive computations based on designs of experiments are conducted to illustrate the validity of the proposed method. Comparisons with the conventional control charting procedure are also provided. The analysis of the monthly number of drug crimes in the city of Pittsburgh is displayed to illustrate our current method of process monitoring.

Optimization of Manganese Recovery from a Solution Based on Lithium-Ion Batteries by Solvent Extraction with D2EHPA

Manganese is a critical metal for the steelmaking industry, and it is expected that its world demand will be increasingly affected by the growing market of lithium-ion batteries. In addition to the increasing importance of manganese, its recycling is mainly determined by trends in the recycling of iron and steel. The recovery of manganese by solvent extraction has been widely investigated; however, the interaction of different variables affecting the process is generally not assessed. In this study, the solvent extraction of manganese from a solution based on lithium-ion batteries was modeled and optimized using factorial designs of experiments and the response surface methodology. Under optimized conditions (O:A of 1.25:1, pH 3.25, and 0.5 M bis(2-ethylhexyl) phosphoric acid (D2EHPA)), extractions above 70% Mn were reached in a single extraction stage with a coextraction of less than 5% Co, which was mostly removed in two scrubbing stages. A stripping product containing around 23 g/L Mn and around 0.3 g/L Co can be obtained under optimized conditions (O:A of 8:1, 1 M H2SO4 and around 13 min of contact time) in one stripping stage.

D-optimal designs of experiments for trigonometric regression on interval with heteroscedastic observations

In article the problem of construction continuous (number of observations is not fixed) D-optimal designs of experiments for trigonometric regression in a case when variance of errors of observations depend on a point in which is made is investigated. Class of functions which describe change variance of heteroscedastic observations is defined for which it is possible construct continuous D-optimal designs of experiments. For trigonometric regression with three factors it is constructed continuous D-optimal designs of experiments with different types heteroscedastic observations. For each of these types the own class of functions describing change variance of observations is defined.

The Construction of Effective Multi-Dimensional Computer Designs of Experiments Based on a Quasi-Random Additive Recursive Rd-sequence

Uniform multi-dimensional designs of experiments for effective research in computer modelling are highly demanded. The combinations of several one-dimensional quasi-random sequences with a uniform distribution are used to create designs with high homogeneity, but their optimal choice is a separate problem, the solution of which is not trivial. It is believed that now the best results are achieved using Sobol’s LPτ-sequences, but this is not observed in all cases of their combinations. The authors proposed the creation of effective uniform designs with guaranteed acceptably low discrepancy using recursive Rd-sequences and not requiring additional research to find successful combinations of vectors set distributed in a single hypercube. The authors performed a comparative analysis of both approaches using indicators of centred and wrap-around discrepancies, graphical visualization based on Voronoi diagrams. The conclusion was drawn on the practical use of the proposed approach in cases where the requirements for the designs allowed restricting to its not ideal but close to it variant with low discrepancy, which was obtained automatically without additional research.