Conceptual design of sonic boom stealth supersonic transports

This paper introduces a supersonic transport aircraft design model developed in the GENUS aircraft conceptual design environment. A conceptual design model appropriate to supersonic transports with low-to-medium-fidelity methods are developed in GENUS. With this model, the authors reveal the relationship between the sonic boom signature and the lift and volume distributions and the possibility to optimise the lift distribution and volume distribution together so that they can cancel each other at some region. A new inspiring design concept—sonic boom stealth is proposed by the authors. The sonic boom stealth concept is expected to inspire the supersonic aircraft designers to design low-boom concepts through aircraft shaping and to achieve low ground impacts. A family of different classes of supersonic aircraft, including a single-seat supersonic demonstrator (0.47 psf), a 10-passenger supersonic business jet (0.90 psf) and a 50-seat supersonic airliner (1.02 psf), are designed to demonstrate the sonic boom stealth design principles. Although, there are challenges to balance the volume with packaging and control requirements, these concepts prove the feasibility of low-boom low-drag design for supersonic transports from a multidisciplinary perspective.

Expanding quasiperiodicity in soft matter: Supramolecular decagonal quasicrystals by binary giant molecule blends

The quasiperiodic structures in metal alloys have been known to depend on the existence of icosahedral order in the melt. Among different phases observed in intermetallics, decagonal quasicrystal (DQC) structures have been identified in many glass-forming alloys yet remain inaccessible in bulk-state condensed soft matters. Via annealing the mixture of two giant molecules, the binary system assemblies into an axial DQC superlattice, which is identified comprehensively with meso-atomic accuracy. Analysis indicates that the DQC superlattice is composed of mesoatoms with an unusually broad volume distribution. The interplays of submesoatomic (molecular) and mesoatomic (supramolecular) local packings are found to play a crucial role in not only the formation of the metastable DQC superlattice but also its transition to dodecagonal quasicrystal and Frank–Kasper σ superlattices.

Estimation of Fracture Properties by Combining DAS and DTS Measurements

Distributed Temperature Sensing (DTS) and Distributed Acoustic Sensing (DAS) measurements during hydraulic fracturing treatments are used to estimate fluid volume distribution among perforation clusters. DAS is sensitive to the acoustic signal induced by fluid flow in the near-well region during pumping a stage, while DTS is sensitive to temperature variation caused by fluid flow inside the wellbore and in the reservoir. Raw acoustic signal has to be transferred to frequency band energy (FBE) which is defined as the integration of the squared raw measurements in each DAS channel location for a fixed period of time. In order to be used in further interpretation, FBE has to be averaged between several fiber-optic channels for each cluster on each time step. Based on this input, DAS allows us to consider fluid flow through perforation stage by stage during an injection period, and to evaluate the volume of fluid pumped in each cluster location as a function of time, and therefore to estimate the cumulative volume of fluid injected into each cluster. This procedure is based on a lab-derived and computational dynamics model confirmed correlation between the acoustic signal and the flow rate. At each time step, we apply the perforation/fracture noise correlation to determine the flow rate into each cluster, constrained by the requirement that the sum of the flow rates into individual clusters must equal the total injection rate at that time. On the other hand, the DTS interpretation method is based on the transient temperature behavior during the fracturing stimulation. During injection, the temperature of the reservoir surrounding the well is cooled by the injection fluid inside the well. After shut-in of stage pumping, temperature recovers at a rate depending on the injected volume of fluid at the location. The interpretation procedure is based on the temperature behavior during the warm-back period. This temperature distribution is obtained by solution of a coupled 3-D reservoir thermal model with 1-D wellbore thermal model iteratively. Once we confirm that the DAS and DTS interpretation methods provide comparable results of the fluid volume distribution, either of the interpretation results can be used as a known input parameter for the other interpretation method to estimate additional unknown such as one of the fracture properties. In this work, the injected fluid volume distribution obtained by the DAS interpretation is used as an input parameter for a forward model which computes the temperature profile in the reservoir. By conducting temperature inversion to reproduce the temperature profile that matches the measured temperature with the fixed injection rate for each cluster, we can predict distribution of injected fluid for hydraulic fractures along a wellbore. The temperature inversion shows that multiple fractures are created in a swarm pattern from each perforation cluster with a much tighter spacing than the cluster spacing. The field data from MIP-3H provided by the Marcellus Shale Energy and Environmental Laboratory is used to demonstrate the DAS/DTS integrated interpretation method. This approach can be a valuable means to evaluate the fracturing treatment design and further understand the field observation of hydraulic fractures.

Study of core strength characteristics as an indicator of the volume distribution of the Temposcreen-Plus polymer-gel system

Filtration experiments are widely used in the oil and gas industry. They are used to determine the key physical and chemical characteristics of the porous medium, the parameters of fluid filtration. Also, filtration experiments are the main method for evaluating the residual resistance factor for compositions that are used in water shut-off technologies. However, filtration studies are not sufficient to study the distribution of the filtrate over the volume of the porous medium. This paper describes a method for using strength characteristics studies to evaluate the distribution of the polymer-gel system "Temposcreen-Plus" in the pore volume of the core after filtration. A method for representing core strength data in the form of a visualized image of the hardness distribution on a color scale is also proposed. Keywords: strength characteristics; hardness; core; "Temposcreen-Plus"; filtration experiments; visualization.

Evolution of a Polydisperse Ensemble of Ellipsoidal Crystals with Fluctuating Growth Rates in Supercooled Melts

In this paper, an analytical solution to the model of the evolution of ellipsoidal crystals with fluctuating growth rates at the intermediate step of bulk phase transition is presented. A complete system of integrodifferential equations describing the problem was derived and analytically solved using the Laplace integral method. The kinetics of supercooling removal in melts has been found. The particle-volume distribution function represents a pike-shaped curve decreasing its maximum with time. It is demonstrated the differences in the distribution function for ellipsoidal and spherical crystals.

Spectroscopic and Transport Behavior of HAB-6FDA Thermally Rearranged (TR) Nanocomposite Membranes

Nanocomposite membranes are a class of innovative filtering materials made up of nanofillers embedded in a polymeric or inorganic oxide matrix that functionalized for the membrane. Thermally rearranged (TR) polymers are found to have a good blending of selectivity and permeability. Chemical iridization is a process for used to make HAB-6FDA polyimide from 3,3 dihydroxy-4,4 diamino-biphenyl (HAB) & 2,2-bis-(3,4-dicarboxyphenyl) hexafluoro propane dianhydride (6FDA). The sample is first changed from a pure polymer membrane to a silica nanofiller doped polymer layer and explain thermally rearrangement for gas permeability in polymer nanocomposite layers and its relationship with kinetic diameter of different gases. The selectivity is decreases as the permeability increases that shows on a trade-off relationship between permeability & selectivity. The CO2 permeability of the HAB-6FDA TR polymers is greater than that of other classes of polymers by equal free volume and indicating that these TR polymers have free volume distribution that supports high permeability. Thermally rearranged polymer nanocomposite exhibits higher gas permeability than that of silica doped and pure polymer. The selectivity for H2/N2 and H2/CO2 gas pairs exceeds towards Robeson's upper bound limit and in case of H2/CH4 gas pair this limit were crossed the Robeson’s upper bond limit. UV spectroscopy shows the change in transmission at higher wavelengths, while XRD show the reduction in FWHM with thermal treatment temperature. Polymer nanocomposite can be utilized to obtain high purity hydrogen gas for refinery and petrochemical applications.

Methods of In Situ Quantitative Root Biology

When dealing with plant roots, a multiscale description of the functional root structure is needed. Since the beginning of 21st century, new devices such as laser confocal microscopes have been accessible for coarse root structure measurements, including three-dimensional (3D) reconstruction. Most researchers are familiar with using simple 2D geometry visualization that does not allow quantitative determination of key morphological features from an organ-like perspective. We provide here a detailed description of the quantitative methods available for 3D analysis of root features at single-cell resolution, including root asymmetry, lateral root analysis, cell size and nuclear organization, cell-cycle kinetics, and chromatin structure analysis. Quantitative maps of the root apical meristem (RAM) are shown for different species, including Arabidopsis thaliana (L.), Heynh, Nicotiana tabacum L., Medicago sativa L., and Setaria italica (L.) P. Beauv. The 3D analysis of the RAM in these species showed divergence in chromatin organization and cell volume distribution that might be used to study root zonation for each root tissue. Detailed protocols and possible pitfalls in the usage of the marker lines are discussed. Therefore, researchers who need to improve their quantitative root biology portfolio can use them as a reference.

63. PK-RNN-V: A Deep Learning Model for Vancomycin Therapeutic Drug Monitoring using Electronic Health Record Data

Background Therapeutic drug monitoring (TDM) for vancomycin (VAN) with Bayesian models is recommended by national guidelines. However, limited data incorporating the models may hurt the performance. Our aim is to develop a novel deep learning-based pharmacokinetic model for vancomycin (PK-RNN-V) using electronic medical records (EHRs) data to achieve more accurate and personalized predictions for VAN levels. Methods EHR data were retrospectively retrieved from Memorial Hermann Hospital System, comprising 14 hospitals in the greater Houston area. All patients who received VAN and had any VAN levels were eligible. Patients receiving hemodialysis and extracorporeal membrane oxygenation were excluded. Demographic data, vital signs, diagnostic codes, concomitant medications, VAN administration, and laboratory data were preprocessed as longitudinal data. VAN infusion, VAN level measurement, or each hospital day were the time steps for the models. The dataset was splited 70:15:15 for training, validation, and test sets. Our PK-RNN-V model predicted individual patient volume distribution (v) and VAN elimination (k) at each time step using an irregular timesteps GRU model. To compare, Bayesian models were developed from publicly available models, and tuned to feedback the first VAN level to update the v and k. (VTDM) Results A total of 12,258 patients with 195,140 encounters were identified from Aug, 2019 and March, 2020. After exclusion of 6,775 patients, 5,483 patients with 8,689 encounters were included. Table 1 summarized the characteristics of patients included in our study. 55,336 doses of VAN were administered with a median dosage of 1.0 gm. VAN levels were measured 18,588 times at various timings. The median VAN level was 14.7 mcg/mL Table 2 described the performance of our models and VTDM models. Our model exhibited better performance compared to VTDM model (RMSE: 5.64 vs. 6.57, respectively). Figure 1 shows example prediction curves of VAN levels from each model. Conclusion PK-RNN-V model is a novel approach to predict patient PK and VAN levels. Our results revealed promising performance of this model. Our model can take a wide range of real-world patient data into the model. Further studies are warranted for external validations and model optimizations. Disclosures All Authors: No reported disclosures

Power-law distribution found in city-scale traffic flow simulation

Origin of a power-law in traffic-volume distribution found in traffic simulations of Kobe city was studied. The traffic distribution which was obtained from a shortest path search with randomized OD (origin-destination) set in Kobe city digital map obeys power-law. The toy model that Cayley tree is embedded in the network is also verified. It is theoretically shown that the traffic distribution with all possible OD set in a Cayley tree obeys power-law like distribution. With randomized OD set, the distribution is diffused from the theoretical point sets. Relationship between these facts and the origin of power-law is discussed.