Experimental characterization of gasoline sprays under highly evaporating conditions

An experimental investigation of multistream gasoline sprays under highly evaporating conditions is carried out in this paper. Temperature increase of fuel and low engine pressure could lead to flash boiling. The spray shape is normally modified significantly under flash boiling conditions. The spray plumes expansion along with reduction in the axial momentum causes the jets to merge and creates a low-pressure area below the injector’s nozzle. These effects initiate the collapse of spray cone and lead to the formation of a single jet plume or a big cluster like structure. The collapsing sprays reduces exposed surface and therefore they last longer and subsequently penetrate more. Spray plume momentum increase, jet plume reduction and spray target widening could delay or prevent the closure condition and limit the penetration (delayed formation of the cluster promotes evaporation). These spray characteristics are investigated experimentally using shadowgraphy, for five and six hole injectors, under various boundary conditions. Six hole injectors produce more collapsing sprays in comparison to five hole injector due to enhanced jet to jet interactions. The spray collapse tendency reduces with increase in injection pressure due high axial momentum of spray plumes. The spray evaporation rates of five hole injector are observed to be higher than six hole injectors. Larger spray cone angles of the six hole injectors promote less penetrating and less collapsing sprays

Meso scale component manufacturing: a comparative analysis of non-lithography and lithography-based processes

The paper identifies the meso scale (10 µm to few millimeters) component size that can be manufactured by using both lithography and non-lithography based approaches. Non-lithography based meso/micro manufacturing is gaining popularity to make micro 3D artifacts with various engineering materials. Being in the nascent stage, this technology looks promising for future micro manufacturing trends. Currently, lithography based micro manufacturing techniques are mature, and used for mass production of 2D, 2.5D features and products extending to 3D micro parts in some cases. In this paper, both the techniques at state-of-the-art level for meso/micro scale are explained first. The comparison is arranged based on examples and a criterion is set in terms of achievable accuracy, production rate, cost, size and form of artifacts and materials used. The analysis revealed a third combined approach where a mix of both techniques can work together for meso scale products. Critical issues affecting both the manufacturing approaches, to advance in terms of accuracy, process physics, materials, machines and product design are discussed. Process effectiveness guideline with respect to the component scale, materials, achievable tolerances, production rates and application is emerged, as a result of this exercise

Biomechanical modeling of human-robot accident scenarios: a computational assessment for heavy-payload-capacity robots

Exponentially growing technologies such as intelligent robots in the context of Industry 4.0 are radically changing traditional manufacturing to intelligent manufacturing with increased productivity and flexibility. Workspaces are being transformed into fully shared spaces for performing tasks during human-robot collaboration (HRC), increasing the possibility of accidents as compared to the fully restricted and partially shared workspaces. The next technological epoch of Industry 5.0 has a heavy focus on human well-being, with humans and robots operating in synergy. However, the reluctance to adopt heavy-payload-capacity robots due to safety concerns is a major hurdle. Therefore, the importance of analyzing the level of injury after impact can never be neglected for the safety of workers and for designing a collaborative environment. In this study, quasi-static and dynamic analyses of accidental scenarios during HRC are performed for medium-and low-payload-capacity robots according to the conditions given in ISO TS 15066 to assess the threshold level of injury and pain, and is subsequently extended for high speeds and heavy payloads for collaborative robots. For this purpose, accidental scenarios are simulated in ANSYS using a 3D finite element model of an adult human index finger and hand, composed of cortical bone and soft tissue. Stresses and strains in the bone and tissue, and contact forces and energy transfer during impact are studied, and contact speed limit values are estimated. It is observed that heavy-payload-capacity robots must be restricted to 80% of the speed limit of low-payload-capacity robots. Biomechanical modeling of accident scenarios offers insights and, therefore, gives confidence in the adoption of heavy-payload robots in factories of the future. The analysis allows for prediction and assessment of different hypothetical accidental scenarios in HRC involving high speeds and heavy-payload-capacity robots

A connective framework to minimize the anxiety of collaborative Cyber-Physical System

The role of Cyber-Physical systems (CPS) is well recognized in the context of Industry 4.0, which consists of human operators working with machines/robots. The interactions among them can be quite demanding in terms of cognitive resources. Existing systems do not yet consider the psychological aspects of safety in the domain. This lack can lead to hazardous situations, thus compromising the performance of the working system. This work proposes a connective decision-making framework for a flexible CPS, which can quickly respond to dynamic changes and be resilient to emergent hazards. First, Anxiety is defined and categorized for expected/unforeseen situations that a CPS could encounter through historical data using the Ishikawa method. Second, visual cues are used to gather the CPS's current state (such as human pose and object identification). Third, a mathematical model is developed using Mixed-integer programming (MIP) to allocate optimal resources, to tackle high-impact situations generating Anxiety. Finally, the logic is designed for an effective counter-mechanism to mitigate Anxiety. The proposed method was tested on a realistic industrial scenario incorporating a collaborative CPS. The results demonstrated that the proposed method improves the decision-making of a CPS facing a complex scenario, ensures physical safety, and effectively enhances the human-machine team's productivity

A use case of exclusive economic zone of Pakistan for wave power potential estimation

The demand for energy is constantly rising in developing countries. Ocean waves with continuous energy flux can contribute to universal energy production. The wave energy has its advantages of renewable, non-polluting and large storage, however, the technological solution to extract energy from oceans is still at early stages. In this paper, a strategy is devised to estimate wave power potential for a developing country. Pakistan is considered as a use case on the basis of less renewable energy share and facing energy crises. In this study, wave energy potential is estimated for power generation by excluding the sensitive areas from the exclusive economic zone. The year long significant wave height and mean wave period data set is used for the purpose. A GIS based multi-criteria overlay analysis model is implemented using different restriction and weighted factors such as ocean bathymetry, distance to ports and shoreline. The results show that average wave power is peaked at 9.15 kW/m in the summer season and 85% of Pakistan economic zone is suitable for wave farm development. The wave energy potential assessment is coupled by extractable power estimation that is worked out by assessing the performance of commercial wave energy converters in regional context