Transient Heat Analysis of a Carbon Composite Scramjet Combustion Chamber

A preliminary 2D transient analysis for a predicted trajectory in a representative scramjet flight path is presented. This model incorporates hypersonic convection and radiation heat transfer at the combustor walls and heat transfer to the fuel which is used as an endothermic heat sink. A heavy hydrocarbon fuel is selected due to the high density and energy release required for combustion, whilst still providing the necessary heat sink for cooling. In this process the fuel can be cracked to smaller carbon chained molecules for improved ignition and combustion. This analysis will be used in parallel with materials development to ensure appropriate composites are available in Australia for flight structures. The results show that for a postulated Mach 8 scramjet flight at 27km altitude that a combustor structure comprising of 1mm RCC, 1mm graphite foam insulation and a 3mm inconel fuel manifold the maximum temperatures reached are of the order of 1950K in the RCC. This falls within the temperature range allowed for the chosen materials to ensure that structural integrity is maintained. These results justify the further investigation into the use of composite materials and regenerative cooling with the aim of potentially using the analysis for the design of flight vehicles, including the upcoming HiFire series of experiments

A survey of image-based computational learning techniques for frost detection in plants

Frost damage is one of the major concerns for crop growers as it can impact the growth of the plants and hence, yields. Early detection of frost can help farmers mitigating its impact. In the past, frost detection was a manual or visual process. Image-based techniques are increasingly being used to understand frost development in plants and automatic assessment of damage resulting from frost. This research presents a comprehensive survey of the state-of the-art methods applied to detect and analyse frost stress in plants. We identify three broad computational learning approaches i.e., statistical, traditional machine learning and deep learning, applied to images to detect and analyse frost in plants. We propose a novel taxonomy to classify the existing studies based on several attributes. This taxonomy has been developed to classify the major characteristics of a significant body of published research. In this survey, we profile 80 relevant papers based on the proposed taxonomy. We thoroughly analyse and discuss the techniques used in the various approaches, i.e., data acquisition, data preparation, feature extraction, computational learning, and evaluation. We summarise the current challenges and discuss the opportunities for future research and development in this area including in-field advanced artificial intelligence systems for real-time frost monitoring

Transmission matrix of a uniaxial optically active crystal platelet

Expressions corresponding to the transmission of a uniaxial optically active crystal platelet are provided for an optical axis parallel and perpendicular to the plane of interface. The optical activity is taken into account by a consistent multipolar expansion of the crystal medium response due to the path of an electromagnetic wave. Numerical examples of the effect of the optical activity are given for quartz platelets of chosen thicknesses. The optical activity's effects on the variations of the transmission of quartz platelets as a function of the angle of incidence is also investigated.Comment: 18 pages, 12 figures. Accepted to Optics Communications Journa

SEREEGA: Simulating Event-Related EEG Activity

Abstract Electroencephalography (EEG) is a popular method to monitor brain activity, but it can be difficult to evaluate EEG-based analysis methods because no ground-truth brain activity is available for comparison. Therefore, in order to test and evaluate such methods, researchers often use simulated EEG data instead of actual EEG recordings, ensuring that it is known beforehand which e ects are present in the data. As such, simulated data can be used, among other things, to assess or compare signal processing and machine learn-ing algorithms, to model EEG variabilities, and to design source reconstruction methods. In this paper, we present SEREEGA, short for Simulating Event-Related EEG Activity . SEREEGA is a MATLAB-based open-source toolbox dedicated to the generation of sim-ulated epochs of EEG data. It is modular and extensible, at initial release supporting ve different publicly available head models and capable of simulating multiple different types of signals mimicking brain activity. This paper presents the architecture and general work ow of this toolbox, as well as a simulated data set demonstrating some of its functions. Highlights Simulated EEG data has a known ground truth, which can be used to validate methods. We present a general-purpose open-source toolbox to simulate EEG data. It provides a single framework to simulate many different types of EEG recordings. It is modular, extensible, and already includes a number of head models and signals. It supports noise, oscillations, event-related potentials, connectivity, and more

Design of test flows to investigate binary scaling in high enthalpy CO2-N2 mixtures

Binary scaling is a similitude law that facilitates the study of hypersonic flows around blunt bodies. It conserves the Reynolds number and the binary (two-body) reaction rates, which are mainly present in the nonequilibrium layer, and scales properly the convective heat transfer. It requires duplication of the product of density and a length scale of the flow, σL, as well as the free-stream enthalpy, H . Its use for ground-to-flight extrapolation depends on the fractional extent of regions of the flow where higher order reactions become important. This paper presents the design of flow conditions relevant to the study of binary scaling for the X2 super-orbital expansion tube. Flows conditions with similar free-stream enthalpy but distinct free-stream densities were obtained. With the help of numerical simulation, it was confirmed that those conditions were suitable to isolate the effect of binary scaling from the uncertainties and scattering of free-stream conditions

Evoked Potentials Recorded From the Spinal Cord During Neurostimulation for Pain: A Computational Modeling Study

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/153677/1/ner12965.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/153677/2/ner12965_am.pd

Trends in source gases

Source gases are defined as those gases that, by their breakdown, introduce into the stratosphere halogen, hydrogen, and nitrogen compounds that are important in stratospheric ozone destruction. Given here is an update of the existing concentration time series for chlorocarbons, nitrous oxide, and methane. Also reviewed is information on halogen containing species and the use of these data for establishing trends. Also reviewed is evidence on trends in trace gases that influence tropospheric chemistry and thus the tropospheric lifetimes of source gases, such as carbon dioxide, carbon monoxide, or nitrogen oxides. Much of the information is given in tabular form

VGLUT1 binding to endophilin or intersectin1 and dynamin phosphorylation in a diurnal context

Glutamate is concentrated into synaptic vesicles (SV) by the vesicular glutamate transporters (VGLUT) 1 and 2. VGLUTs also harbor a Na+/Pi-transport activity when residing at the plasma membrane. Here we aimed to identify whether the diurnal switches of VGLUT1 parallels interactions with or modification of endocytic proteins.VGLUT1 and dynamin bind to SH3 domains of either endophilin (Enph) or intersectin 1 (ITSN1) harboring one or five SH3 domains A–E, respectively. We followed diurnal variations by pull down experiments using SH3 fusion protein and brains from mice entrained in a strict 24-h light–dark cycle (12-h light Zeitgeber (ZT) 0, 6; 12-h dark ZT 12 and 18). In pull downs with EnphSH3 interaction with VGLUT1 is high during the resting light and reduced during the active dark period while dynamin binding does not vary. This diurnal light/dark pattern depends on a functional period 2 gene and changes when animals are kept in complete darkness. Pull downs using ITSN1SH3 A reveal diurnally varying binding of VGLUT1 with slightly reduced VGLUT1/dynamin ratios at the beginning of the light (ZT 0) or the dark (ZT 12) period. Phosphorylation increases binding of VGLUT1 but not of dynamin to EnphSH3. In contrast binding of dynamin to ITSN1SH3 A decreases under phosphorylating conditions with no changes in VGLUT1 binding. Phosphorylation of dynamin at Ser 774 is high at ZT 6 and ZT 18 when more VGLUT1 is at the plasma membrane but low at ZT 0 and ZT 12 the diurnal peaks of VGLUT1 endocytosis. In conclusion the diurnally varying endocytosis of VGLUT1 involves differential interactions with the SH3 domains of Enph and ITSN1 and correlates with the de-phosphorylation of dynamin1

Brachistochrone of Entanglement for Spin Chains

We analytically investigate the role of entanglement in time-optimal state evolution as an appli- cation of the quantum brachistochrone, a general method for obtaining the optimal time-dependent Hamiltonian for reaching a target quantum state. As a model, we treat two qubits indirectly cou- pled through an intermediate qubit that is directly controllable, which represents a typical situation in quantum information processing. We find the time-optimal unitary evolution law and quantify residual entanglement by the two-tangle between the indirectly coupled qubits, for all possible sets of initial pure quantum states of a tripartite system. The integrals of the motion of the brachistochrone are determined by fixing the minimal time at which the residual entanglement is maximized. Entan- glement plays a role for W and GHZ initial quantum states, and for the bi-separable initial state in which the indirectly coupled qubits have a nonzero value of the 2-tangle.Comment: 9 pages, 4 figure