Gas/liquid flow behaviours in a downward section of large diameter vertical serpentine pipes

An experimental study on air/water flow behaviours in a 101.6 mm i.d. vertical pipe with a serpentine configuration is presented. The experiments are conducted for superficial gas and liquid velocities ranging from 0.15 to 30 m/s and 0.07 to 1.5 m/s, respectively. The bend effects on the flow behaviours are significantly reduced when the flow reaches an axial distance of 30 pipe diameters or more from the upstream bend. The mean film thickness data from this study has been used to compare with the predicted data using several falling film correlations and theoretical models. It was observed that the large pipe data exhibits different tendencies and this manifests in the difference in slope when the dimensionless film thickness is plotted as a power law function of the liquid film Reynolds number

Interfacial shear in adiabatic downward gas/liquid co-current annular flow in pipes

Interfacial friction is one of the key variables for predicting annular two-phase flow behaviours in vertical pipes. In order to develop an improved correlation for interfacial friction factor in downward co-current annular flow, the pressure gradient, film thickness and film velocity data were generated from experiments carried out on Cranfield University’s Serpent Rig, an air/water two-phase vertical flow loop of 101.6 mm internal diameter. The air and water superficial velocity ranges used are 1.42–28.87 and 0.1–1.0 m/s respectively. These correspond to Reynolds number values of 8400–187,000 and 11,000–113,000 respectively. The correlation takes into account the effect of pipe diameter by using the interfacial shear data together with dimensionless liquid film thicknesses related to different pipe sizes ranging from 10 to 101.6 mm, including those from published sources by numerous investigators. It is shown that the predictions of this new correlation outperform those from previously reported studies

Sustainable Irrigation Management of Ornamental Cordyline Fruticosa “Red Edge” Plants with Saline Water

The aim of this work was to analyze the influence of the salinity of the nutrient solution on the transpiration and growth of Cordyline fruticosa var. “Red Edge” plants. A specific irrigation management model was calibrated with the experimental data. An experiment was performed with four treatments. These treatments consisted of the application of four nutrient solutions with different electrical conductivity (ECw) levels ranging from 1.5 dS m−1 (control treatment) to 4.5 dS m−1. The results showed that day-time transpiration decreases when salt concentration in the nutrient solution increases. The transpiration of the plant in the control treatment was modelled by applying a combination method while the effect of the salinity of the nutrient solution was modelled by deriving a saline stress coefficient from the experimental data. The results showed that significant reductions in plant transpiration were observed for increasing values of ECw. The crop development and yield were also affected by the increasing salinity of the nutrient solution. A relationship between the ECw and the relative crop yield was derived

Mid-infrared photodetectors operating over an extended wavelength range up to 90 K

We report a wavelength threshold extension, from the designed value of 3.1 to 8.9 μm, in a -type heterostructure photodetector. This is associated with the use of a graded barrier and barrier offset, and arises from hole–hole interactions in the detector absorber. Experiments show that using long-pass filters to tune the energies of incident photons gives rise to changes in the intensity of the response. This demonstrates an alternative approach to achieving tuning of the photodetector response without the need to adjust the characteristic energy that is determined by the band structure

Polyamide Nanocomposites for Selective Laser Sintering

Current polyamide 11 and 12 are lacking in fire retardancy and high strength/high heat resistance characteristics for a plethora of finished parts that are desired and required for performance driven applications. It is anticipated that nanomodification of polyamide 11 and 12 will result in enhanced polymer performance, i.e., fire retardancy, high strength and high heat resistance for polyamide 11 and 12. It is expected that these findings will expand the market opportunities for polyamide 11 and 12 resin manufacturers. The objective of this research is to develop improved polyamide 11 and 12 polymers with enhanced flame retardancy, thermal, and mechanical properties for selective laser sintering (SLS) rapid manufacturing (RM). A nanophase was introduced into the polyamide 11 and 12 via twin screw extrusion to provide improved material properties of the polymer blends. Arkema RILSAN® polyamide 11 molding polymer pellets and Degussa VESTAMID® L1670 polyamide 12 were examined with three types of nanoparticles: chemically modified montmorillonite (MMT) organoclays, surface modified nanosilica, and carbon nanofibers (CNFs) to create polyamide 11 and 12 nanocomposites. Wide angle X-ray diffraction (WAXD) and transmission electron microscopy (TEM) were used to determine the degree of dispersion. Injection molded test specimens were fabricated for physical, thermal, mechanical properties, and flammability tests. Thermal stability of these polyamide 11 and 12 nanocomposites was examined by TGA. Mechanical properties such as tensile, flexural, and elongation at break were measured. Flammability properties were also obtained using the Cone Calorimeter at an external heat flux of 50 kW/m2. TEM micrographs, physical, mechanical, and flammability properties are included in the paper. Polyamide 11 and 12 nanocomposites properties are compared with polyamide 11 and 12 baseline polymers. Based on flammability and mechanical material performance, selective polymers including polyamide 11 nanocomposites and control polyamide 11 were cryogenically ground into fine powders and fabricated into SLS parts.Mechanical Engineerin

Accurate molecular polarizabilities with coupled-cluster theory and machine learning

The molecular polarizability describes the tendency of a molecule to deform or polarize in response to an applied electric field. As such, this quantity governs key intra- and inter-molecular interactions such as induction and dispersion, plays a key role in determining the spectroscopic signatures of molecules, and is an essential ingredient in polarizable force fields and other empirical models for collective interactions. Compared to other ground-state properties, an accurate and reliable prediction of the molecular polarizability is considerably more difficult as this response quantity is quite sensitive to the description of the underlying molecular electronic structure. In this work, we present state-of-the-art quantum mechanical calculations of the static dipole polarizability tensors of 7,211 small organic molecules computed using linear-response coupled-cluster singles and doubles theory (LR-CCSD). Using a symmetry-adapted machine-learning based approach, we demonstrate that it is possible to predict the molecular polarizability with LR-CCSD accuracy at a negligible computational cost. The employed model is quite robust and transferable, yielding molecular polarizabilities for a diverse set of 52 larger molecules (which includes challenging conjugated systems, carbohydrates, small drugs, amino acids, nucleobases, and hydrocarbon isomers) at an accuracy that exceeds that of hybrid density functional theory (DFT). The atom-centered decomposition implicit in our machine-learning approach offers some insight into the shortcomings of DFT in the prediction of this fundamental quantity of interest

Beyond the Classroom: Using Google Sites as a Supplementary Material to Improve the Learners’ English Academic Performance

The present study investigated the common challenges of learners in the new mode of learning and their frequency, if there would be a significant difference in the performance of the participants after using Google Sites, the acceptability of the Google Sites in terms of its content quality, instructional quality, and technical quality, and the experience of the respondents in using Beyond the Classroom as supplementary material for the Third Quarter. This action research used the survey questionnaires, evaluation tool, pre-tests, and posttest as instruments in answering the research questions. Respondents were 15 Grade 8 High School learners who have internet access. Results indicated always and sometimes characterized their experience on challenges such as understanding the lessons after reading the discussion found in the modules and that there is a significant difference between the pre-test and post-test scores for lessons that are easy for them to understand and learn alone. Results also revealed that Beyond the Classroom is very acceptable in terms of its content, instructional, and technical quality, and respondents found it helpful in understanding their lessons. Finally, this study showed that learners struggle to cope with the changes in the new normal, and online supplementary material helps them understand their lessons and activities for the Third Quarter of the academic year 2021-2022

Innovative Selective Laser Sintering Rapid Manufacturing using Nanotechnology

The objective of this research is to develop an improved nylon 11 (polyamide 11) polymer with enhanced flame retardancy, thermal, and mechanical properties for selective laser sintering (SLS) rapid manufacturing (RM). A nanophase was introduced into nylon 11 via twin screw extrusion to provide improved material properties of the polymer blends. Atofina (now known as Arkema) RILSAN® nylon 11 injection molding polymer pellets was used with three types of nanoparticles: chemically modified montmorillonite (MMT) organoclays, nanosilica, and carbon nanofibers (CNF) to create nylon 11 nanocomposites. Wide angle X-ray diffraction (WAXD) and transmission electron microscopy (TEM) were used to determine the degree of dispersion. Fifteen nylon 11 nanocomposites and control nylon 11 were fabricated by injection molding. Flammability properties (using a cone calorimeter with a radiant flux of 50 kW/m2 ) and mechanical properties such as tensile strength and modulus, flexural modulus, elongation at break were determined for the nylon 11 nanocomposites and compared with the baseline nylon 11. Based on flammability and mechanical material performance, five polymers including four nylon 11 nanocomposites and a control nylon 11 were cryogenically ground into fine powders for SLS RM. SLS specimens were fabricated for flammability, mechanical, and thermal properties characterization. Nylon 11-CNF nanocomposites exhibited the best overall properties for this study.Mechanical Engineerin

Designing calibration and expressivity-efficient instruction sets for quantum computing

Near-term quantum computing (QC) systems have limited qubit counts, high gate (instruction) error rates, and typically support a minimal instruction set having one type of two-qubit gate (2Q). To reduce program instruction counts and improve application expressivity, vendors have proposed, and shown proof-of-concept demonstrations of richer instruction sets such as XY gates (Rigetti) and fSim gates (Google). These instruction sets comprise of families of 2Q gate types parameterized by continuous qubit rotation angles. That is, it allows a large set of different physical operations to be realized on the qubits, based on the input angles. However, having such a large number of gate types is problematic because each gate type has to be calibrated periodically, across the full system, to obtain high fidelity implementations. This results in substantial recurring calibration overheads even on current systems which use only a few gate types. Our work aims to navigate this tradeoff between application expressivity and calibration overhead, and identify what instructions vendors should implement to get the best expressivity with acceptable calibration time.Studying this tradeoff is challenging because of the diversity in QC application requirements, the need to optimize applications for widely different hardware gate types and noise variations across gate types. Therefore, our work develops NuOp, a flexible compilation pass based on numerical optimization, to efficiently decompose application operations into arbitrary hardware gate types. Using NuOp and four important quantum applications, we study the instruction set proposals of Rigetti and Google, with realistic noise simulations and a calibration model. Our experiments show that implementing 4-8 types of 2Q gates is sufficient to attain nearly the same expressivity as a full continuous gate family, while reducing the calibration overhead by two orders of magnitude. With several vendors proposing rich gate families as means to higher fidelity, our work has potential to provide valuable instruction set design guidance for near-term QC systems