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Powder bed fusion processes are common due to their ability to build complex components without the need for complex tooling. While additive manufacturing has gained increased interest in industry, academia and government, flaws are often still generated during the deposition process. Many flaws can be avoided through careful processing parameter selections including laser power, hatch spacing, spot size and shielding gas flow rate. The purpose of this paper is to study the effect of shielding gas flow on vapor plume behavior and on final deposition quality. The goal is to understand more fully how each parameter affects the plume and deposition process.

A filtered-photodiode based sensor was mounted onto a commercial EOS M280 machine to observed plume emissions. Three sets of single tracks were printed, each with one of three gas flow rates (nominal, 75% nominal and 50% nominal). Each set contained single-track beads deposited atop printed pedestals to ensure a steady-state, representative build environment. Each track had a set power and speed combination which covered the typical range of processing parameters. After deposition, coupons were cross-sectioned and bead width and depth were measured. Finally, bead geometry was compared to optical emissions originating in the plume.

The results show that decreasing gas flow rate, increasing laser power or increasing scan speed led to increased optical emissions. Furthermore, decreasing the gas cross-flow speed led to wider and shallower melt pools.

To the best of the authors’ knowledge, this paper is among the first to present a relationship among laser parameters (laser power, scan speed), gas flow speed, plume emissions and bead geometry using high-speed in situ data in a commercial machine. This study proposes that scattering and attenuation from the plume are responsible for deviations in physical geometry.

Detecting O₂ gas in a confined space at room temperature is particularly important to monitor the work process of precision equipment. This study aims to propose a miniaturized, low-cost, mass-scale produced O₂ sensor operating around 30°C.

The O₂ sensor based on lanthanum fluoride (LaF₃) solid electrolyte thin film was developed using MEMS technology. The principle of the sensor was a galvanic cell H₂O, O₂, Pt | LaF₃ | Sn, SnF₂ |, in which the Sn film was prepared by magnetron sputtering, and the LaF₃ film was prepared by thermal resistance evaporation.

Through pretreatments, the sensor’s response signal to 40% oxygen concentration was enhanced from 1.9 mV to 46.0 mV at 30°C and 97.0% RH. Tests at temperatures from 30°C to 50°C and humidity from 32.4% RH to 97.0% RH indicated that the output electromotive force (EMF) has a linear relationship with the logarithm of the oxygen concentration. The sensitivity of the sensor increases with an increase in both humidity and temperature in the couple mode, and the EMF of the sensor follows well with the Nernst equation at different temperatures and humidity.

This research could be applied to monitor the oxygen concentration below 25% in confined spaces at room temperature safely without a power supply.

The relationship between temperature and humidity coupling and the response of the sensor was obtained. The nano-film material was integrated with the MEMS process. It is expected to be practically applied in the future.

Artificial fruit ripening is hazardous to mankind. In the recent past, artificial fruit ripening is increasing gradually due to its commercial benefits. To discriminate the type of fruit ripening involved at the vendors’ side, there is a great demand for on-sight ethylene detection in a nondestructive manner. Therefore, this study aims to deal with a comparison of various laboratory and portable methods developed so far with high-performance metrics to identify the ethylene detection at fruit ripening site.

This paper focuses on various types of technologies proposed up to date in ethylene detection, fabrication methods and signal conditioning circuits for ethylene detection in parts per million and parts per billion levels. The authors have already developed an infrared (IR) sensor to detect ethylene and also developed a lab-based setup belonging to the electrochemical sensing methods to detect ethylene for the fruit ripening application.

The authors have developed an electrochemical sensor based on multi-walled carbon nanotubes whose performance is relatively higher than the sensors that were previously reported in terms of material, sensitivity and selectivity. For identifying the best sensing technology for optimization of ethylene detection for fruit ripening discrimination process, authors have developed an IR-based ethylene sensor and also semiconducting metal-oxide ethylene sensor which are all compared with literature-based comparable parameters. This review paper mainly focuses on the potential possibilities for developing portable ethylene sensing devices for investigation applications.

The authors have elaborately discussed the new chemical and physical methods of ethylene detection and quantification from their own developed methods and also the key findings of the methods proposed by fellow researchers working on this field. The authors would like to declare that the extensive analysis carried out in this technical survey could be used for developing a cost-effective and high-performance portable ethylene sensing device for fruit ripening and discrimination applications.

Gas transmission pipelines are at constant risk of gas leakage or fire due to various atmospheric environments, corrosion on pipe metal surfaces and other external factors. This study aims to reduce the human and financial risks associated with gas transmission by regularly monitoring pipeline performance, controlling situations and preventing disasters.

Facility managers can monitor the status of gas transmission lines in real-time by integrating sensor information into a building information modeling (BIM) 3D model. Using the Monitoring Panel plugin, coded in C# programming language and operated through Navisworks software, the model provides up-to-date information on pipeline safety and performance.

By collecting project information on the BIM and installing critical sensors, this approach allows facility manager to observe the real-time safety status of gas pipelines. If any risks of gas leakage or accidents are identified by the sensors, the BIM model quickly shows the location of the incident, enabling facility managers to make the best decisions to reduce financial and life risks. This intelligent gas transmission pipeline approach changes traditional risk management and inspection methods, minimizing the risk of explosion and gas leakage in the environment.

This research distinguishes itself from related work by integrating sensor data into a BIM model for real-time monitoring and providing facility managers with up-to-date safety information. By leveraging intelligent gas transmission pipelines, the system enables quick identification and location of potential hazards, reducing financial and human risks associated with gas transmission.

The purpose of this study is to achieve lower and lower temperature as infrared sensors works faster and better used for space application. For getting good quality images from space, the infrared sensors are need to keep in cryogenic temperature. Cooling to cryogenic temperatures is necessary for space-borne sensors used for space applications. Infrared sensors work faster or better at lower temperatures. It is the need for time to achieve lower and lower temperatures.

This study presents the investigation of the critical Stirling cryocooler parameters that influence the cold end temperature. In the paper, the design approach, the dimensions gained through thermal analysis, experimental procedure and testing results are discussed.

The effect of parameters such as multilayer insulation, helium gas charging pressure, compressor input voltage and cooling load was investigated. The performance of gold-plated and aluminized multilayer insulation is checked. The tests were done with multilayer insulation covering inside and outside the Perspex cover.

By using aluminized multilayer insulation inside and outside the Perspex cover, the improvement of 16 K in cool-down temperature was achieved. The cryocooler is charged with helium gas. The pressure varies between 14 and 18 bar. The optimum cooling is obtained for 17 bar gas pressure. The piston stroke increased as the compressor voltage increased, resulting in total helium gas compression. The optimum cool-down temperature was attained at 85 V.

The cryocooler is designed to achieve the cool-down temperature of 2 W cooling load at 100 K. The lowest cool-down temperature recorded was 105 K at a 2 W cooling load. Multilayer insulation is the major item that keeps the thermal radiation from the sun from reaching the copper tip.

Aero-engine exhaust plume length can be more than the aircraft length, making it easier to detect and track by infrared seeker. Aim of this study is to analyze the effect of free stream Mach number (M_∞) on length of potential core of plume. Also, change in infrared (IR) signature of plume and aircraft surface with variation in elevation angle (θ) is examined.

Convergent divergent (CD) nozzle is located outside the rear fuselage of the aircraft. A two dimensional axisymmetric computational fluid dynamics (CFD) study was carried out to study effect of M_∞ on potential core. The CFD data with aircraft and plume was then used for IR signature analysis. The sensor position is changed with respect to aircraft from directly bottom towards frontal section of aircraft. The IR signature is studied in mid wave IR (MWIR) and long wave IR (LWIR) band.

The potential plume core length and width increases as M_∞ increases. At higher altitudes, the potential core length increases for a fixed M_∞. The plume emits radiation in the MWIR band, whereas the aerodynamically heated aircraft surface emits IR in the LWIR band. The IR signature in the MWIR band continuously decreases as the sensor position changes from directly bottom towards frontal. In the LWIR band the IR signature initially decreases as the sensor moves from the directly bottom to the frontal, as the sensor begins to see the wing leading edges and nose cone, the IR signature in the LWIR band slightly increases.

The novelty of this study comes from the data reported on the effect of free stream Mach number on the potential plume core and variation of the overall IR signature of aircraft with change in elevation angle from directly below towards frontal section of aircraft.

Identifying the flow regime is a prerequisite for accurately modeling two-phase flow. This paper aims to introduce a comprehensive data-driven workflow for flow regime identification.

A numerical two-phase flow model was validated against experimental data and was used to generate dynamic pressure signals for three different flow regimes. First, four distinct methods were used for feature extraction: discrete wavelet transform (DWT), empirical mode decomposition, power spectral density and the time series analysis method. Kernel Fisher discriminant analysis (KFDA) was used to simultaneously perform dimensionality reduction and machine learning (ML) classification for each set of features. Finally, the Shapley additive explanations (SHAP) method was applied to make the workflow explainable.

The results highlighted that the DWT + KFDA method exhibited the highest testing and training accuracy at 95.2% and 88.8%, respectively. Results also include a virtual flow regime map to facilitate the visualization of features in two dimension. Finally, SHAP analysis showed that minimum and maximum values extracted at the fourth and second signal decomposition levels of DWT are the best flow-distinguishing features.

This workflow can be applied to opaque pipes fitted with pressure sensors to achieve flow assurance and automatic monitoring of two-phase flow occurring in many process industries.

This paper presents a novel flow regime identification method by fusing dynamic pressure measurements with ML techniques. The authors’ novel DWT + KFDA method demonstrates superior performance for flow regime identification with explainability.

This study aims to develop an experimentally validated three-dimensional numerical model for predicting different flow patterns produced with a gas dynamic virtual nozzle (GDVN).

The physical model is posed in the mixture formulation and copes with the unsteady, incompressible, isothermal, Newtonian, low turbulent two-phase flow. The computational fluid dynamics numerical solution is based on the half-space finite volume discretisation. The geo-reconstruct volume-of-fluid scheme tracks the interphase boundary between the gas and the liquid. To ensure numerical stability in the transition regime and adequately account for turbulent behaviour, the k-ω shear stress transport turbulence model is used. The model is validated by comparison with the experimental measurements on a vertical, downward-positioned GDVN configuration. Three different combinations of air and water volumetric flow rates have been solved numerically in the range of Reynolds numbers for airflow 1,009–2,596 and water 61–133, respectively, at Weber numbers 1.2–6.2.

The half-space symmetry allows the numerical reconstruction of the dripping, jetting and indication of the whipping mode. The kinetic energy transfer from the gas to the liquid is analysed, and locations with locally increased gas kinetic energy are observed. The calculated jet shapes reasonably well match the experimentally obtained high-speed camera videos.

The model is used for the virtual studies of new GDVN nozzle designs and optimisation of their operation.

To the best of the authors’ knowledge, the developed model numerically reconstructs all three GDVN flow regimes for the first time.

Vision, audition, olfactory, tactile and taste are five important senses that human uses to interact with the real world. As facing more and more complex environments, a sensing system is essential for intelligent robots with various types of sensors. To mimic human-like abilities, sensors similar to human perception capabilities are indispensable. However, most research only concentrated on analyzing literature on single-modal sensors and their robotics application.

This study presents a systematic review of five bioinspired senses, especially considering a brief introduction of multimodal sensing applications and predicting current trends and future directions of this field, which may have continuous enlightenments.

This review shows that bioinspired sensors can enable robots to better understand the environment, and multiple sensor combinations can support the robot’s ability to behave intelligently.

The review starts with a brief survey of the biological sensing mechanisms of the five senses, which are followed by their bioinspired electronic counterparts. Their applications in the robots are then reviewed as another emphasis, covering the main application scopes of localization and navigation, objection identification, dexterous manipulation, compliant interaction and so on. Finally, the trends, difficulties and challenges of this research were discussed to help guide future research on intelligent robot sensors.

In this study, an attempt has been made to collect the research that has been done on the construction and design of the H₂O₂ sensor. So far, many efforts have been made to quickly and sensitively determine H₂O₂ concentration based on different analytical principles. In this study, the importance of H₂O₂, its applications in various industries, especially the food industry, and the importance of measuring it with different techniques, especially portable sensors and on-site analysis, have been investigated and studied.

Hydrogen peroxide (H₂O₂) is a very simple molecule in nature, but due to its strong oxidizing and reducing properties, it has been widely used in the pharmaceutical, medical, environmental, mining, textile, paper, food production and chemical industries. Sensitive, rapid and continuous detection of H₂O₂ is of great importance in many systems for product quality control, health care, medical diagnostics, food safety and environmental protection.

Various methods have been developed and applied for the analysis of H₂O₂, such as fluorescence, colorimetry and electrochemistry, among them, the electrochemical technique due to its advantages in simple instrumentation, easy miniaturization, sensitivity and selectivity.

Monitoring the H₂O₂ concentration level is of practical importance for academic and industrial purposes. Edible oils are prone to oxidation during processing and storage, which may adversely affect oil quality and human health. Determination of peroxide value (PV) of edible oils is essential because PV is one of the most common quality parameters for monitoring lipid oxidation and oil quality control. The development of cheap, simple, fast, sensitive and selective H₂O₂ sensors is essential.