Fixed-diamond abrasive wire saw cutting is one of the most common methods for cutting hard and brittle materials. This process has unique advantages including a narrow kerf and the ability to use a relatively small cutting force. In the cutting process, controlling the main process parameters can improve the processing efficiency, obtaining a better processing surface roughness. This work designs the PI controller (Proportional-Integral controller) based on the reciprocating wire saw cutting process. The control objects are the workpiece feed rate and wire saw velocity, and the control objective is the normal cutting force. For the control trials, several reference values of various normal cutting forces were chosen. The effects of feed rate and saw velocity on the cutting surface finish and cutting time were investigated in this work using wire saw cutting analysis on a square monocrystalline silicon specimen. The results of this study showed that under a constant applied force of 2.5 N, the optimal feed rate of the diamond wire through the specimen could reduce cutting time by 42% while achieving a 60% improvement in the measured surface finish. Likewise, optimal control of the wire saw velocity could reduce cycle time by 18% with a 45% improvement in the surface finish. Consequently, the feed speed control is more effective than the wire saw velocity.
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http://dx.doi.org/10.3390/mi15040473 | DOI Listing |
Sci Rep
December 2024
Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, PA, USA.
Polymer electrolyte membrane water electrolyzers (PEMWEs) are a critical technology for efficient hydrogen production to decarbonize fuels and industrial feedstocks. To make hydrogen cost-effective, the overpotentials across the cell need to be decreased and platinum-group metal loading reduced. One overpotential that needs to be better understood is due to mass transport limitations from bubble formation within the porous transport layer (PTL) and anode catalyst layer (ACL), which can lead to a reduction in performance at typical operating current densities.
View Article and Find Full Text PDFOpen Vet J
November 2024
Department of Fisheries and Marine Resources, Collage of Agriculture, Basrah University, Basrah, Iraq.
Background: Pomegranate () fruit rich in bioactive constituents, is used as a feed supplement against bacterial pathogens in aquaculture.
Aim: This study examined the effects of supplementing the diet of the common carp () infected with on growth and some hematological, biochemical, and immunological health indicators.
Methods: Carp was fed for 7 weeks a diet of 30% crude protein and 7% crude fat, supplemented with 0, 0.
Arch Razi Inst
June 2024
Department of Microbiology, Faculty of Veterinary Medicine, Urmia University, Urmia, Iran.
Mycotoxins are toxins produced by various types of fungi, including , which can produce different types of mycotoxins, such as Deoxynivalenol (DON), Zearalenone, T-2 toxin, and Fumonisins (FUM). Mycotoxins have the potential to reduce the quality of crops and pose health risks to both humans and animals. This can result in reduced animal production and substantial economic consequences on a global scale.
View Article and Find Full Text PDFPol J Vet Sci
June 2024
Department of Animal Nutrition and Husbandry, University of Veterinary Medicine and Pharmacy in Kosice, Komenskeho 73, 041 81 Kosice, Slovak Republic.
The present study was conducted to evaluate the effect of humic substances on performance and selected blood biochemical parameters in turkeys. A total of twenty 6-week-old turkey hybrids (Big 6) were divided into two groups. The first group of turkeys was fed the basal diet without any supplementation of humic substances as a control group.
View Article and Find Full Text PDFHeliyon
December 2024
School of Mechanical Engineering, Institute of Technology, Wallaga University, P.O. Box 395, Nekemte, Ethiopia.
Turning AISI (American Iron and Steel Institute) D3 tool steel can be challenging due to a lack of optimal process parameters and proper coolant application to achieve high surface quality and temperature control. Machine learning helps in predicting the optimal parameters, whereas nanofluids enhance cooling efficiency while preserving both the tool and the workpiece. This work intends to utilize advanced machine learning approaches to optimize process parameters with the application of hybrid nanofluids (AlO/graphene) during the CNC turning of AISI D3.
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