A Physics-Based Approach to Unsupervised Discovery of Coherent Structures in Spatiotemporal Systems

Given that observational and numerical climate data are being produced at ever more prodigious rates, increasingly sophisticated and automated analysis techniques have become essential. Deep learning is quickly becoming a standard approach for such analyses and, while great progress is being made, major challenges remain. Unlike commercial applications in which deep learning has led to surprising successes, scientific data is highly complex and typically unlabeled. Moreover, interpretability and detecting new mechanisms are key to scientific discovery. To enhance discovery we present a complementary physics-based, data-driven approach that exploits the causal nature of spatiotemporal data sets generated by local dynamics (e.g. hydrodynamic flows). We illustrate how novel patterns and coherent structures can be discovered in cellular automata and outline the path from them to climate data.Comment: 4 pages, 1 figure; http://csc.ucdavis.edu/~cmg/compmech/pubs/ci2017_Rupe_et_al.ht

Matrix-free continuation of limit cycles and their bifurcations for a ducted premixed flame

AbstractMany experimental studies have demonstrated that ducted premixed flames exhibit stable limit cycles in some regions of parameter space. Recent experiments have also shown that these (period-1) limit cycles subsequently bifurcate to period-$2^{n}$, quasiperiodic, multiperiodic or chaotic behaviour. These secondary bifurcations cannot be found computationally using most existing frequency domain methods, because these methods assume that the velocity and pressure signals are harmonic. In an earlier study we have shown that matrix-free continuation methods can efficiently calculate the limit cycles of large thermoacoustic systems. This paper demonstrates that these continuation methods can also efficiently calculate the bifurcations from the limit cycles. Furthermore, once these bifurcations are found, it is then possible to isolate the coupled flame–acoustic motion that causes the qualitative change in behaviour. This information is vital for techniques that use selective damping to move bifurcations to more favourable locations in the parameter space. The matrix-free methods are demonstrated on a model of a ducted axisymmetric premixed flame, using a kinematic$G$-equation solver. The methods find limit cycles and period-2 limit cycles, and fold, period-doubling and Neimark–Sacker bifurcations as a function of the location of the flame in the duct, and the aspect ratio of the steady flame.Iain Waugh acknowledges the support of EPSRC through a Doctoral Training Grant and the IMechE through the postgraduate scholarship award. Karthik Kashinath acknowledges the support of EPSRC and Rolls-Royce through a Dorothy Hodgkin studentship. Matthew Juniper acknowledges the support of the ERC through project ALORS 2590620.This is the accepted manuscript. The final version is available from CUP at http://journals.cambridge.org/action/displayAbstract?fromPage=online&aid=9384264&fulltextType=RA&fileId=S002211201400549

Nonlinear self-excited thermoacoustic oscillations of a ducted premixed flame: Bifurcations and routes to chaos

AbstractThermoacoustic systems can oscillate self-excitedly, and often non-periodically, owing to coupling between unsteady heat release and acoustic waves. We study a slot-stabilized two-dimensional premixed flame in a duct via numerical simulations of a $G$-equation flame coupled with duct acoustics. We examine the bifurcations and routes to chaos for three control parameters: (i) the flame position in the duct, (ii) the length of the duct and (iii) the mean flow velocity. We observe period-1, period-2, quasi-periodic and chaotic oscillations. For certain parameter ranges, more than one stable state exists, so mode switching is possible. At intermediate times, the system is attracted to and repelled from unstable states, which are also identified. Two routes to chaos are established for this system: the period-doubling route and the Ruelle–Takens–Newhouse route. These are corroborated by analyses of the power spectra of the acoustic velocity. Instantaneous flame images reveal that the wrinkles on the flame surface and pinch-off of flame pockets are regular for periodic oscillations, while they are irregular and have multiple time and length scales for quasi-periodic and aperiodic oscillations. This study complements recent experiments by providing a reduced-order model of a system with approximately 5000 degrees of freedom that captures much of the elaborate nonlinear behaviour of ducted premixed flames observed in the laboratory.This is the author's accepted manuscript. The final version is available from CUP in the Journal of Fluid Mechanics at http://journals.cambridge.org/action/displayAbstract?fromPage=online&aid=9441088&fulltextType=RA&fileId=S002211201400601

Seed Quality Improvement in Okra through Specific Gravity Separation

A study was conducted to assess the efficiency of specific gravity separator in removing partially filled/chaffy seeds of okra during 2007 and 2008. Bulk seed, after extraction, was first subjected to an air screen cleaner with three screens. Then, the good seed fraction obtained was subjected to specific gravity separation. Three fractions were obtained, viz., heavy, medium and light and they were assessed for quality, along with ungraded seed. Test weight, germination percentage, first count, seedling vigour indices I&II and field emergence were significantly higher in the heavy seed fraction than in ungraded seed. Black seed content in heavy seed fraction was significantly low, thereby improving seed quality. Rejection percentage in terms of light and medium seed fractions put together was 3.5% and 12% in 2007 and 2008, respectively. By removal of these fractions, percentage of field emergence improved from 63% to 82% in 2007, and 62.8 to 76.4% in 2008, respectively

Microbiological Hazard Identification and Exposure Assessment of Poultry Products Sold in Various Localities of Hyderabad, India

A study was carried out to identify microbiological hazards and assess their exposure associated with consumption of poultry based street food served in different localities of Hyderabad. The study indicated that chicken 65, chicken fried rice, chicken noodles, chicken Manchuria and chilly chicken are the most common recipes. A process flow diagram was developed to identify critical control points in the food item. After analysis of the samples at each level of preparation, it was observed that rice and noodles were kept at room temperature for about 5-6 hrs which was a critical control point. A total of 376 samples including chicken fried rice, chicken noodles, boiled noodles and boiled rice were collected from circle 1, 2, 3, 4, 5, 6, and 7 of Greater Hyderabad municipal corporation (GHMC) and analyzed for microbiological examination. The most prevalent pathogenic bacteria isolated were S. aureus (3.4 log 10 cfu/g) and B. cereus (3.4 log 10 cfu/g). Salmonella spp. was present in salads (3.2 log 10 cfu/g) and hand washings of the food handler (3.5 log 10 cfu/g). Salmonella contamination was found in salads served along with chicken fried rice and chicken noodles than in the food

Pharmaceutico analytical study of Shodhita Shilajatu

Background: Shilajatu or Adrija is one of the Maharasa, which is considered as a wonderful medicine in Ayurveda. It is named as it comes out of the stones heated by the sun in summer in the form of thick blackish exudation having many shades. Since it contain stone, mud, wood, sand and various physical and metallic impurities, Shodhana (Purification) of Shilajatu is a mandatory procedure. It has been used as a prime ingredient in many formulations mainly for Prameha, Sotha, Pandu Roga, Kshaya, Swasa, Pliha Vrudhi, Jwara, Agnimandya, Apasmara, etc. Objectives: Shodhana of Ashudha Shilajatu and Physico chemical analysis of Shodhita Shilajatu. Materials & Methods: Bhringaraja Swarasa for Shodhana of Shilajatu. Results:It took 8 days for completion of Shilajatu Shodhana. XRD Analysis report indicates that the sample Shilajatu was Amorphous material. Conclusion: Total yield of Shodhita Shilajatu was 99.6%. The Sample of Shilajatu was found to be Amorphous material in XRD Analysis hence crystal structure was not identified

Efficient Row-Column Designs for Microarrav Experiments

This article deals with the problem of obtaining efficient designs for 2-colour microarray experiments where same set of genes are spotted on each array In the literature, optimal ity aspects of designs for microarray experiments have been investigated under a restricted model involving array and variety effects. The dye effects have been ignored from the model. If dye effects are also included in the model, then the structure of the design becomes that of a row-column design where arrays represent columns, dyes represent rows and varieties represent treatments. Further, the array effects in microarray experiments may be taken as random {see e.g. Kerr and Churchill (2001a). Lee (2004)). For obtaining efficient row-column designs under fixed mixed effects model, exchange and interchange algorithms of Lxcleston and Jones (1980) and Rathore et al. (2006) have been modified. The algorithm has been translated into a computer program using Microsoft Visual C++. The algorithm is general in nature and can be used for generating efficient row-column designs for any 2 < k < v. where v is the number of treatments (varieties) and k is number of rows (dyes). Here, the algorithm has been exploited for computer aided search of efficient row-column designs for making all possible pairwise treatment comparisons for k = 2 (2-colour microarray experiments) in the parametric range 3 < v < 10, v< h < v(v- l)/2; II < v< 25. b = v and (v, b) = (11, 13), (12, 14), (13, 14) and (13, 15), where h is the number of arrays (columns). Ffficient row-column designs obtained under fixed effects model have been compared with the best available designs and best even designs. 45 designs have been obtained with higher efficiencies than the best available designs and even designs. The robustness aspect of efficient row-column designs obtained under a fixed effects model and best available designs were investigated under a mixed effects model. Strength of the algorithm for obtaining row-column designs for 3-colour microarray experiments has been demonstrated with the help of examples

Topological data analysis and machine learning for recognizing atmospheric river patterns in large climate datasets

Identifying weather patterns that frequently lead to extreme weather events is a crucial first step in understanding how they may vary under different climate change scenarios. Here, we propose an automated method for recognizing atmospheric rivers (ARs) in climate data using topological data analysis and machine learning. The method provides useful information about topological features (shape characteristics) and statistics of ARs. We illustrate this method by applying it to outputs of version 5.1 of the Community Atmosphere Model version 5.1 (CAM5.1) and the reanalysis product of the second Modern-Era Retrospective Analysis for Research and Applications (MERRA-2). An advantage of the proposed method is that it is threshold-free – there is no need to determine any threshold criteria for the detection method – when the spatial resolution of the climate model changes. Hence, this method may be useful in evaluating model biases in calculating AR statistics. Further, the method can be applied to different climate scenarios without tuning since it does not rely on threshold conditions. We show that the method is suitable for rapidly analyzing large amounts of climate model and reanalysis output data.</p