Search Results (158)

Nanoparticle additives are used to increase the cooling efficiency of cutting fluids in machining. In this study, changing dynamic viscosity values depending on the addition of nanoparticles to cutting oils was investigated. Mono nanofluids were prepared by adding hBN (hexagonal boron nitride), ZnO, MWCNT (multi-walled carbon nanotube), TiO₂, and Al₂O₃ as nanoparticles, hybrid nanofluids were prepared by using two types of nanoparticles (ZnO + MWCNT, hBN + MWCNT etc.), and ternary nanofluids were prepared by using three types of nanoparticles. GPR (Gaussian process regression) was used to estimate unmeasured dynamic viscosity values using the dynamic viscosity values measured for different temperatures. Dynamic viscosity results are a precise determination (R² = 1). An augmented dataset was obtained by adding the dynamic viscosity values estimated with high accuracy. A fitness function based on dynamic viscosity and nanoparticle unit costs was proposed for the cost analysis. With the help of the proposed fitness function, it was observed that the best performing nanoparticles were the ZnO and ZnO hybrid mixtures according to different dynamic viscosity and cost effects. The study showed that the most suitable nanofluid selection focused on performance and cost could be made without performing experiments under various operating conditions by increasing the limited experimental measurements with strong GPR estimates and using the proposed fitness function. Full article

The rapid growth of the machining market and advancements in additive manufacturing (AM) present new opportunities for innovative tool designs. This preliminary study proposes a design for additive manufacturing (DfAM) approach to redesign a milling cutter head in 17-4 PH stainless steel by integrating topology optimization (TO) and internal coolant channel optimization, enabled by laser powder bed fusion (LPBF). An industrial eight-insert milling cutting tool was reimagined with conformal cooling channels and a lightweight topology-optimized structure. The design process considered LPBF constraints and was iteratively refined using computational fluid dynamics (CFD) and finite element analysis (FEA) to validate fluid flow and structural performance. The optimized milling head achieved approximately 10% weight reduction while improving stiffness (reducing maximum deformation under load from 160 μm to 151 μm) and providing enhanced coolant distribution to the cutting inserts. The results demonstrate that combining TO with internal channel design can yield a high-performance and lightweight milling tool that leverages the freedom of additive manufacturing. As proof of concept, this integrated CFD–FEA validation approach under DfAM guidelines highlights a promising pathway toward superior cutting tool designs for industrial applications. Full article

In additive–subtractive hybrid manufacturing (ASHM), machining and additive processes are combined in a single operation to merge the benefits of both. This method faces challenges, especially during the machining steps. Parts made through additive manufacturing often have low machinability due to factors like residual stresses and fine, hard microstructures. In ASHM, intermediate heat treatments are not possible, leading to the increased hardness of the printed material. Cutting fluids, typically used to reduce temperature and friction, can contaminate the build environment and impair layer adhesion; therefore, they are not recommended in ASHM. This study investigates soft metallic lubricant coatings in ASHM as substitutes for conventional fluid lubricants during dry machining. The coatings form a lubricating layer between the tool and workpiece, providing an alternative to cutting fluids. This research evaluates their effectiveness in improving the surface integrity of additively manufactured parts and supporting dry machining. The results of our research show a 65% reduction in force, a 50% reduction in tool wear, and a reduction in microstructural changes during machining while maintaining dry machining. Full article

The widespread use of mineral cutting fluids in metalworking poses challenges due to their poor wettability, toxicity, and non-biodegradability. This study explores cactus oil-based nanofluids as sustainable alternatives for metal cutting applications. Samples of cactus oil are prepared in plain form and with 0.025 wt.%, 0.05 wt.%, and 0.1 wt.% activated carbon nanoparticles (ACNPs) from recycled plastic waste. Plain cactus oil exhibited a 34% improvement in wettability over commercial soluble oil, further enhanced by 60% with 0.05 wt.% ACNPs. Cactus oil displayed consistent Newtonian behavior with a high viscosity index (283), outperforming mineral-based cutting fluid in thermal stability. The addition of ACNPs enhanced the dynamic viscosity by 108–130% across the temperature range of 40–100 °C. The presence of nano-additives reduced the friction coefficient in the boundary lubrication zone by a maximum reduction of 32% for CO2 compared to plain cactus oil. The physical and rheological results translated directly to the observed improvements in surface finish and tool wear during machining operations on H13 steel. Cactus oil with 0.05 wt.% ACNP outperformed conventional fluids, reducing surface roughness by 35% and flank wear by 57% compared to dry. This work establishes cactus oil-based nanofluids as a sustainable alternative, combining recycled waste-derived additives and non-edible feedstock for greener manufacturing. Full article

Additive manufacturing (AM) stands out for its variable applications in terms of material, quality, and geometry. Wire Arc Additive Manufacturing (WAAM) is remarkable for producing large parts in reduced times when compared to other AM methods. The possibility of producing a part with a near-net shape not only enhances productivity but also reduces resources usage. However, parts produced by WAAM may need post-processing by machining to achieve functional surface requirements. Therefore, it is important that machining, even if minimized, does not lead to a significant environmental impact. In this sense, this work evaluates the effect of using compressed air, dry cut, and synthetic biodegradable cutting fluid at varying nozzle positions and flow rates on the surface quality of ER70S-6 steel produced by WAAM, after milling with TiAlN-coated carbide tools. To analyze the surface roughness, parameters Ra, Rq, and Rz were measured and microscopy was used to further evaluate the surfaces. The surface hardness was also evaluated. The results showed that a flow rate of 10 L/min promotes better surface quality, which can be further improved using compressed air, leading to a surface quality 50% better when compared to dry cutting. Dry cut was not suitable for machining ER70S-6 WAAM material as it resulted in rough surface texture with an Rz = 4.02 µm. Compressed air was the best overall condition evaluated, achieving a 36% Ra reduction compared to dry cutting, the second-lowest hardness deviation at 6.51%, and improved sustainability by eliminating the need for cutting fluid. Full article

Pancreatic cystic lesions (PCLs) are increasingly identified via computerized tomography (CT) and magnetic resonance (MR), with a prevalence of 2–45%. Distinguishing mucinous PCLs (M-PCLs), which include intraductal papillary mucinous neoplasms (IPMNs) and mucinous cystic neoplasms (MCNs) that can progress to pancreatic ductal adenocarcinoma, from non-mucinous PCLs (NM-PCLs) is essential. Carcinoembryonic antigen (CEA) remains widely used but often demonstrates limited sensitivity and specificity. In contrast, endoscopic ultrasound-guided measurement of intracystic glucose more accurately differentiates PCL subtypes, as tumor-related metabolic changes lower cyst fluid glucose in mucinous lesions. Numerous prospective and retrospective studies suggest a glucose cut-off between 30 and 50 mg/dL, yielding a sensitivity of 88–95% and specificity of 76–91%, frequently outperforming CEA. Additional benefits include immediate point-of-care assessment via standard glucometers and minimal interference from blood contamination. DNA-based biomarkers, including KRAS and GNAS mutations, enhance specificity (up to 99%) but exhibit moderate sensitivity (61–71%) and necessitate specialized, expensive platforms. Molecular analyses can be crucial in high-risk lesions, yet their uptake is constrained by technical challenges. In practice, combining glucose assessment with targeted molecular assays refines risk stratification and informs the choice between surgical resection or active surveillance. Future investigations should establish standardized glucose thresholds, improve the cost-effectiveness of genetic testing, and integrate advanced biomarkers into routine protocols. Ultimately, these strategies aim to optimize patient management, limit unnecessary interventions for benign lesions, and ensure timely therapy for lesions at risk of malignant transformation. Full article

Microfluidic devices are tiny tools used to manipulate small volumes of liquids in various fields. However, these devices frequently require additional equipment to control fluid flow, increasing the cost and complexity of the systems and limiting their potential for widespread use in low-resource biomedical applications. Here, we present a cost-effective and simple fabrication method for PMMA microfluidic chips using laser cutting technology, along with a low-cost and open-source peristaltic pump constructed with common hardware. The pump, programmed with an Arduino microcontroller, offers precise flow control in microfluidic devices for small volume applications. The developed application for controlling the peristaltic pump is user-friendly and open source. The microfluidic chip and pump system was tested using Jurkat cells. The cells were cultured for 24 h in conventional cell culture and a microfluidic chip. The LDH assay indicated higher cell viability in the microfluidic chip (111.99 ± 7.79%) compared to conventional culture (100 ± 15.80%). Apoptosis assay indicated 76.1% live cells, 18.7% early apoptosis in microfluidic culture and 99.2% live cells, with 0.5% early apoptosis in conventional culture. The findings from the LDH and apoptosis analyses demonstrated an increase in both cell proliferation and cellular stress in the microfluidic system. Despite the increased stress, the majority of cells maintained membrane integrity and continued to proliferate. In conclusion, the chip fabrication method and the pump offer advantages, including design flexibility and precise flow rate control. This study promises solutions that can be tailored to specific needs for biomedical applications. Full article

PVD hard coatings improve the wear and frictional properties in metal cutting and, therefore, extend the lives of cutting tools. Cutting fluids, including the novel use of liquid carbon dioxide (LCO₂), are crucial for reducing tool wear and enhancing machining efficiency. This experimental research is focused on ball-on-disc wear tests of TiAlN hard coatings in environmental, N₂ and CO₂ atmospheres. In the latter case, the experiments were also performed by adding LCO₂ directly into the contact zone. In order to achieve the same temperatures as real cutting conditions, tests were performed at 250 °C, 500 °C and 700 °C, in addition to room temperature. Results show that the TiAlN coating had the highest wear rate in room-temperature tests, regardless of the atmosphere. The wear significantly dropped with the test temperature. It was the lower in the CO₂ atmosphere at all temperatures than in all gas-only atmospheres. When LCO₂ was introduced to the contact, the wear was at its highest at 500 °C, which is the opposite of all other gas-only atmospheres, where it was at its lowest. In all tribological LCO₂ tests, we noticed increased friction coefficient fluctuations. In all gas-only atmospheres, adhered material was observed on the wear tracks, but in LCO₂, wear debris was not detected either on the disk or on the ball. Full article

Machining processes often face challenges such as elevated temperatures and wear, which traditional cutting fluids are insufficient to address. As a result, solutions involving nanoparticle additives are being explored to enhance cooling and lubrication performance. This study investigates the effect of thermal conductivity, an important property influenced by the densities of mono and hybrid nanofluids. To this end, various nanofluids were prepared by incorporating hexagonal boron nitride (hBN), zinc oxide (ZnO), multi-walled carbon nanotubes (MWCNTs), titanium dioxide (TiO₂), and aluminum oxide (Al₂O₃) nanoparticles into sunflower oil as the base fluid. Hybrid nanofluids were created by combining two nanoparticles, including ZnO + MWCNT, hBN + MWCNT, hBN + ZnO, hBN + TiO₂, hBN + Al₂O₃, and TiO₂ + Al₂O₃. A dataset consisting of 180 data points was generated by measuring the thermal conductivity and density of the prepared nanofluids at various temperatures (30–70 °C) in a laboratory setting. Conducting thermal conductivity measurements across different temperature ranges presents significant challenges, requiring considerable time and resources, and often resulting in high costs and potential inaccuracies. To address these issues, a feedforward artificial neural network (FFANN) method was proposed to predict thermal conductivity. Our multilayer FFANN model takes as input the temperature of the experimental environment where the measurement is made, the measured thermal conductivity of the relevant nanoparticle, and the relative density of the nanoparticle. The FFANN model predicts the thermal conductivity value linearly as output. The model demonstrated high predictive accuracy, with a reliability of R = 0.99628 and a coefficient of determination (R²) of 0.9999. The average mean absolute error (MAE) for all hybrid nanofluids was 0.001, and the mean squared error (MSE) was 1.76 × 10⁻⁶. The proposed FFANN model provides a State-of-the-Art approach for predicting thermal conductivity, offering valuable insights into selecting optimal hybrid nanofluids based on thermal conductivity values and nanoparticle density. Full article

The application of high-pressure jet-assisted (HPJA) machining can increase tool life during machining, as the cutting fluid penetrates better into the interfaces between the tool and the workpiece. In this work, tool life in semi-finish turning of Inconel 718 with coated carbide tools and a high-pressure coolant supply is investigated. In a preliminary experiment, tool life was compared between conventional flooding and HPJA machining. The results show tool life that is more than twice as long with HPJA at higher cutting speeds. In the main experiment, tool life was investigated as a function of various high-pressure-jet parameters (nozzle diameter, distance between the point of impact of the jet and the cutting edge and pressure of the jet) and basic cutting parameters (cutting speed and feed rate). The relationship between the above-mentioned process parameters and tool life was analyzed and modeled using response surface methodology (RSM). Analysis of variance (ANOVA) was performed to evaluate the statistical significance of each process parameter for the response. The results revealed that cutting speed is the most important factor for maximizing tool life, followed by pressure of the jet and feed rate. In addition, optimization using the biogeographic optimization (BBO) algorithm was performed and validated in this study. The results of the confirmation experiments show that the proposed optimization method is very effective and results in approximately 8.4% longer tool life compared to the best trial results. Full article

Aneurysmal subarachnoid hemorrhage (aSAH) is a life-threatening condition that results from intracranial aneurysm rupture, leading to the accumulation of blood between the arachnoid and pia mater. The blood breakdown products and damage-associated molecule patterns (DAMPs), which are released as a result of vascular and cellular compromise following aneurysm rupture, elicit local endothelial reactions leading to the narrowing of cerebral arteries and ischemia. In addition, vascular inflammation, characterized by activated endothelial cells, perpetuates disruption of the neurovascular unit and the blood–brain barrier. The uncertain prognosis of aSAH patients contributes to the necessity of a fluid biomarker that can serve as a valuable adjunct to radiological and clinical evaluation. Limited studies have investigated vascular inflammation and angiogenic protein expression following aSAH. Reliable markers of the vascular inflammatory and angiogenic response associated with aSAH may allow for the earlier detection of patients at risk for complications and aid in the identification of novel pharmacologic targets. We investigated whether vascular inflammatory and angiogenesis signaling proteins may serve as potential biomarkers of aSAH. Serum and cerebrospinal fluid (CSF) from fifteen aSAH subjects and healthy age-matched controls as well as hydrocephalus (CSF) no-aneurysm controls were evaluated for levels of vascular inflammatory and angiogenesis proteins. Protein measurement was carried out using electrochemiluminescence. The area under the curve (AUC) was calculated using receiver operating characteristics (ROC) to obtain information on biomarker reliability, specificity, sensitivity, cut-off points, and likelihood ratio. In addition, patients were grouped by Glasgow Outcome Score—Extended at 3 months post-injury to determine the correlation between vascular inflammatory protein levels and clinical outcome measures. aSAH subjects demonstrated elevated vascular inflammatory protein levels in serum and CSF when compared to controls. Certain vascular injury and angiogenic proteins were found to be promising biomarkers of inflammatory response in aSAH in the CSF and serum. In particular, elevated levels of serum amyloid-alpha (SAA) were found to be correlated with unfavorable outcomes following aSAH. Determination of these protein levels in CSF and serum in aSAH may be utilized as reliable biomarkers of inflammation in aSAH and used clinically to monitor patient outcomes. Full article

The startup dynamics of wind turbines have a direct impact on their cut-in speed and thus their capacity factor, considering highly transient winds in urban environments. Due to the complex nature of the startup dynamics, the published research on it is severely lacking. Unless the startup dynamics and cut-in speed of a wind turbine are known, it is difficult to evaluate its capacity factor and levelized cost of energy (LCoE) for commercial viability. In this study, a Savonius vertical-axis wind turbine (VAWT) has been considered and its startup dynamics evaluated using numerical techniques. Moreover, the effects of turbine inertia, arising from bearing frictional losses, generator load, etc., on the startup dynamics have been studied. Advanced computational fluid dynamics (CFD)-based solvers have been utilized for this purpose. The flow-induced rotation of the turbine blades has been modeled using a six degree of freedom (6DoF) approach. Turbine inertia has been modeled using the mass moment of inertia of the turbine rotor and systematically increased to mimic the additional inertia and losses due to bearings and the generator. The results indicate that inertia has a significant impact on the startup dynamics of the VAWT. It was observed that as the turbine inertia increased, it took longer for the turbine to reach its steady or peak operational speed. Increasing the inertia by 10%, 20% and 30% increased the time taken by the turbine to reach its peak rotational speed by 13.3%, 16.7% and 23.2%, respectively. An interesting observation from the results obtained is that an increase in turbine inertia does not change the peak rotational speed. For the Savonius rotor considered, the peak rotational speed remained 122 rpm, and its tip speed ratio (TSR) remained 0.6 while increasing the turbine inertia. Full article

This study analyzed the physical and hydrodynamic characteristics of various horizons in the Kumkol and East Kumkol oil fields by special core analysis to integrate strategies for controlling water cuts and well-intervention procedures for a more effective oil flow rate in mature oil fields in Kazakhstan. The results indicated that the recovery factor (RF) for Horizon I is 48.3% (98.7% water cut), while Horizon II has an RF of 45.5% (97.9% water cut). Horizon III has an RF of 52.7% (98.8% water cut), and Horizon IV has an RF of 32.6% (98.6% water cut) in the Kumkol Field. In the East Kumkol Field, Horizon I has an RF of 49.5% (96.7% of water cut), and Horizon II has an RF of 31% (94.9% of water cut). The average increase in oil flow rate from well optimization ranges from 5.3 to 6.4 tons per day in the Kumkol Field and 5.22 tons per day in the East Kumkol Field. The maximum increase in oil flow rate is 10.8 tons/day for Horizon I in the Kumkol Field and 6.9 tons/day for Horizon II in the East Kumkol Field. The well-intervention procedures are more effective in the Kumkol Field than in the East Kumkol Field. Given the high water cut observed in these mature reservoirs, this study also examines polymer flooding as an enhanced oil recovery (EOR) technique to improve oil displacement efficiency and reduce water production. Polymer flooding has been successfully implemented in high water-cut reservoirs, including the Uzen field in Kazakhstan, demonstrating its ability to modify fluid filtration profiles and enhance oil recovery. The feasibility of applying polymer flooding in the Kumkol and East Kumkol fields is analyzed, along with a comparison of its effectiveness against conventional water shut-off and well-intervention methods. Additional research is needed to assess polymer retention, reservoir compatibility, and the economic feasibility of large-scale implementation. Full article

Background: Anastomotic leakage (AL) is a serious and potentially fatal complication that can occur after colorectal cancer (CRC) surgery, and it significantly affects patient recovery and increases morbidity. While serum C-reactive protein (CRP) is a recognized systemic inflammatory marker, the level of CRP in peritoneal fluid may serve as a more specific and localized biomarker for early AL detection. This meta-analysis explores the diagnostic potential of peritoneal fluid CRP, aiming to enhance postoperative care for CRC patients. Methods: A comprehensive literature search was conducted following the PRISMA guidelines. Eligible studies were included based on strict inclusion and exclusion criteria. Diagnostic accuracy was pooled using a random-effects model. The risk of bias was assessed using the QUADAS-2 tool. Results: The pooled sensitivity and specificity were 0.74 and 0.83, respectively, with an area under the curve (AUC) of 0.84, indicating good diagnostic accuracy. The overall diagnostic performance was consistent for sensitivity with no significant heterogeneity, but high heterogeneity was observed for specificity, suggesting variability between studies. Subgroup analysis revealed improved diagnostic performance between postoperative days 5–7 and higher CRP cut-off values (70–150 mg/L). The analysis confirmed the stability of the results through a sensitivity analysis and found no significant publication bias. Conclusions: Peritoneal fluid CRP is a reliable biomarker for detecting AL after CRC surgery, especially in the later postoperative period. However, heterogeneity in study methodologies and patient populations limits the generalizability of the findings. Future research should focus on standardizing protocols and exploring additional biomarkers to improve diagnostic accuracy. Full article

Drilling fluids are vital in oil and gas well operations, ensuring borehole stability, cutting removal, and pressure control. However, fluid loss into formations during drilling can compromise formation integrity, alter permeability, and risk groundwater contamination. Water-based drilling fluids (WBDFs) are favored for their environmental and cost-effective benefits but often require additives to address filtration and rheological limitations. This study explored the feasibility of using vegetable waste, including pumpkin peel (PP), courgette peel (CP), and butternut squash peel (BSP) in fine (75 μm) and very fine (10 μm) particle sizes as biodegradable WBDF additives. Waste vegetable peels were processed using ball milling and characterized via FTIR, TGA, and EDX. WBDFs, prepared per API SPEC 13A with 3 wt% of added additives, were tested for rheological and filtration properties. Results highlighted that very fine pumpkin peel powder (PP_10) was the most effective additive, reducing fluid loss and filter cake thickness by 43.5% and 50%, respectively. PP_10 WBDF maintained mud density, achieved a pH of 10.52 (preventing corrosion), and enhanced rheological properties, including a 50% rise in plastic viscosity and a 44.2% increase in gel strength. These findings demonstrate the remarkable potential of biodegradable vegetable peels as sustainable WBDF additives. Full article