789 research outputs found
Carta de Pawan Kumar Kamthan a M. Carbona Balaguer
No full textCarta de condol escrita per Pawan Kumar Kamthan a M. Carbona Balaguer, amb motiu de la mort de Ferran Sunyer
Simulations Of Accretion Powered Supernovae In The Progenitors Of Gamma-Ray Bursts
No full textObservational evidence suggests a link between long-duration gamma-ray bursts (LGRBs) and Type Ic supernovae. Here, we propose a potential mechanism for Type Ic supernovae in LGRB progenitors powered solely by accretion energy. We present spherically symmetric hydrodynamic simulations of the long-term accretion of a rotating gamma-ray burst progenitor star, a "collapsar," onto the central compact object, which we take to be a black hole. The simulations were carried out with the adaptive mesh refinement code FLASH in one spatial dimension and with rotation, an explicit shear viscosity, and convection in the mixing length theory approximation. Once the accretion flow becomes rotationally supported outside of the black hole, an accretion shock forms and traverses the stellar envelope. Energy is carried from the central geometrically thick accretion disk to the stellar envelope by convection. Energy losses through neutrino emission and nuclear photodisintegration are calculated but do not seem important following the rapid early drop of the accretion rate following circularization. We find that the shock velocity, energy, and unbound mass are sensitive to convective efficiency, effective viscosity, and initial stellar angular momentum. Our simulations show that given the appropriate combinations of stellar and physical parameters, explosions with energies similar to 5 x 10(50) erg, velocities similar to 3000 km s(-1), and unbound material masses greater than or similar to 6 M-circle dot are possible in a rapidly rotating 16 M-circle dot main-sequence progenitor star. Further work is needed to constrain the values of these parameters, to identify the likely outcomes in more plausible and massive LRGB progenitors, and to explore nucleosynthetic implications.National Science Foundation AST-0708795, AST-1009928, AST-0909110DOEAstronom
Collapsar accretion and the gamma-ray burst X-ray light curve
No full texttextWe present axisymmetric hydrodynamical simulations of the long-term accretion of a rotating gamma-ray burst progenitor star, a "collapsar," onto the central compact object, which we take to be a black hole. The simulations were carried out with the adaptive mesh refinement code FLASH in two spatial dimensions and with an explicit shear viscosity. The evolution of the central accretion rate exhibits phases reminiscent of the long GRB [gamma]-ray and X-ray light curve, which lends support to the proposal by Kumar et al. (2008a,b) that the luminosity is modulated by the central accretion rate. In the first "prompt" phase, the black hole acquires most of its final mass through supersonic quasiradial accretion occurring at a steady rate of [scientific symbols]. After a few tens of seconds, an accretion shock sweeps outward through the star. The formation and outward expansion of the accretion shock is accompanied with a sudden and rapid power-law decline in the central accretion rate Ṁ [proportional to] t⁻²̇⁸, which resembles the L[subscript x] [proportional to] t⁻³ decline observed in the X-ray light curves. The collapsed, shock-heated stellar envelope settles into a thick, low-mass equatorial disk embedded within a massive, pressure-supported atmosphere. After a few hundred seconds, the inflow of low-angular-momentum material in the axial funnel reverses into an outflow from the thick disk. Meanwhile, the rapid decline of the accretion rate slows down, which is potentially suggestive of the "plateau" phase in the X-ray light curve. We complement our adiabatic simulations with an analytical model that takes into account the cooling by neutrino emission and estimate that the duration of the prompt phase can be ~ 20 s. The model suggests that the steep decline in GRB X-ray light curves is triggered by the circularization of the infalling stellar envelope at radii where the virial temperature is below 10¹⁰ K, such that neutrino cooling is inefficient and an outward expansion of the accretion shock becomes imminent; GRBs with longer prompt [gamma]-ray emission should have more slowly rotating envelopes.Astronom
A Method for Integrating Network-on-Chip Topologies with 3D ICs
No full textThree dimensional integration is a promising approach for reducing the form factor of chips. Scalable Networks on Chips (NoCs) are a necessity to support the communication requirements of such 3D ICs. Mapping of NoC topologies onto the different layers of the 3D stack, while meeting the 3D technology requirements and application power-performance constraints is an important problem. In this paper, we present an algorithm that addresses this issue of performing 3D layer assignment of NoC components. We also integrate the algorithm with an existing NoC interconnect floor planner. Our experiments on many SoC benchmarks show a reduction of 8 - 10% in the NoC power consumption and a 49% reduction in the number of vertical links (and hence, the Through Silicon Vias (TSVs)) when compared to existing approaches
A Simulation Based Buffer Sizing Algorithm for Network on Chips
No full textBuffers in on-chip networks constitute a significant proportion of the power consumption and area of the interconnect. Hence, reducing the buffering overhead of Networks on Chips (NoCs) is an important problem. For application-specific designs, the network utilization across the different links and switches is non-uniform, thereby requiring a buffer sizing approach that tackles the non uniformity. Moreover, congestion effects that occur during network operation needs to be captured when sizing the buffers. To this end, we propose a two-phase algorithm to size the switch buffers in NoCs. Our algorithm considers both the static (based on bandwidth and latency requirements) and dynamic (based on simulation) effects when sizing buffers. Our experiments show that the application of the algorithm results in 42% reduction in amount of buffering required to meet the application constraints when compared to a standard buffering approach
A Buffer-Sizing Algorithm for Network-on-Chips with Multiple Voltage-Frequency Islands
No full textBuffers in on-chip networks constitute a significant
proportion of the power consumption and area of the
interconnect, and hence reducing them is an important problem.
Application-specific designs have nonuniform network
utilization, thereby requiring a buffer-sizing approach that
tackles the nonuniformity. Also, congestion effects that occur
during network operation need to be captured when sizing the
buffers. Many NoCs are designed to operate in multiple voltage/frequency islands, with interisland communication taking
place through frequency converters. To this end, we propose
a two-phase algorithm to size the switch buffers in network-on-chips (NoCs) considering support for multiple-frequency
islands. Our algorithm considers both the static and dynamic
effects when sizing buffers. We analyze the impact of placing
frequency converters (FCs) on a link, as well as pack and send
units that effectively utilize network bandwidth. Experiments
on many realistic system-on-Chip (SoC) benchmark show
that our algorithm results in 42% reduction in amount of
buffering when compared to a standard buffering approach
Fabrication of a Flexible UV Band-Pass Filter Using Surface Plasmon Metal-Polymer Nanocomposite Films for Promising Laser Applications
No full textWe introduce a strategy for the fabrication of silver/polycarbonate (Ag/PC) nanocomposite flexible films of (20 +/- 0.01) mu m thickness with different filling factor of surface plasmon metal using customized solution cast thermal evaporation method. Structural characterizations confirmed the good crystallinity with cubic phase of Ag nanoparticles in PC films. Moreover, the microstructural evolutions of nanocomposite films are investigated by transmission electron microscopy, which indicates that the metal fraction is in the form of fractals. Additionally, the surface plasmonic behavior of nanocomposite films has been explored in detail to examine the distribution of Ag nanoparticles in PC film by spectroscopic technique. Furthermore, the obtained transmittance spectral features of this nanocomposite film are suitable for the applications of band-pass filter at 320 nm UV range, which is highly desirable for a HeCd laser
Advancement of brazing filler alloy: An Overview
No full textThe brazing is a special type of joining technique for the complex parts of any engineering components, such as, heat exchangers, turbine engine parts of aircraft, spacecraft etc. In this method, joining area is significantly narrow (~1mm), which demands a specific joining method with optimum heat input to achieve a near net shape fabricated component. A suitable brazing filler alloy in this respect offers specific characteristics like adequate wetting, low thickness, narrow melting zone, avoidance of intermetallic formation and limited extent of stress generation at joint interface. The methodology is applicable for both similar and dissimilar combination of materials depending on particular requirement. Due to minimal thickness constraint, the brazing filler alloy is synthesized in the form of fine powders, paste, thin foils and controlled coating between / over the substrate to be joined. The thin foils (~50 µm thickness) are fabricated by rapid solidification technique. Paste of suitable composition is produced by mechanical alloying to obtain fine grain structure with overall chemical homogeneity. The mixed product is further wetted by chemical fluid, which is non-reactive to the components of mixture, however can provide substantial fluidity of the paste. There are several methods to produce thin foils. Once the composition is achieved by conventional melting and casting, the desired thickness is obtained by repetitive forging or rolling of the stock. Controlled coating of single / multiple metal can be produced by spattering, physical vapour deposition and chemical vapour deposition of pre-determined thickness over the substrate to be joined. The controlled thickness in all the above cases is apposite to bridge narrow crack or join components. This methodology is also lucrative considering ease in process control as the variables are limited to four only i.e. temperature, normal pressure, time and atmosphere. Thus a transition joint with satisfactory efficiency and structural homogeneity can be easily achieved
Development And Control Of Urban Water Network Models
No full textWater distribution systems convey drinking water from treatment plant and make available to consumers’ taps. It consists of essential components like pipes, valves, pumps, tanks and reservoirs etc. The main concern in the working of a water distribution system is to assure customer demands under a choice of quantity and quality throughout the complete life span for the probable loading situations. However, in some cases, the existing infrastructure may not be adequate to meet the customer’s requirements. In such cases, system modeling plays an important role in proper management of water supply systems. In present scenario, modeling plays a significant task in appropriate execution of water distribution system.
From the angle of taking management decisions valve throttling control and pumps speed control are very important. These operational problems can be addressed by manual control or by automatic control. The problem is the use of manual controls that slow down the effectiveness of the system. It reduces the efficiency of operation of valve or pump. To improve the efficiency of such water distribution systems, an automatic control based technology has been developed that links the operation of the variable speed pump control or valve throttling control. By employing an automatic control, the pump can adjust its speed at all times to meet the actual flow requirements of each load served.
In case of real system design Simulink is the most widely used tool. Commercial software package Matlab/Simulink used for creation of WDS model. The goal was to produce a model that could numerically analyze the dynamic performance of a water distribution system. A Comparison of single platform methodology (Simulink based control) and double platform methodology (Matlab and EPANET based control) has been done. Nonlinear Dynamic Inversion (DI) Control system model is developed for WDS model in Matlab/Simulink environment. Controller gain parameters are the very important value in control prospective. If the controller gain parameters are chosen incorrectly, the controlled process input can be unstable, i.e. its output diverges, with or without oscillation Tuning is the adjustment of control parameters (gains) to the optimum values for the desired control response. There are several methods for tuning controller like manual tuning (Trial and error procedure), Ziegler-Nichols method, Output Constraint Tuning (OCT) etc.
Establishment of a pump operational policy by which all the reservoirs can be fed simultaneously to meet their requirements without creating undue transients. Tune the gain of DI controllers by different tuning methods and evaluate the best tuning method on the basis of controller performance. Development of meaningful additional objective is search of lower bound pump speed on the basis of control time or settling time. To bring the pump speeds in feasible range, application of constraint in pumps speed is introduced. The magnitude of constraints can be found using Monte Carlo methods. Monte Carlo methods are frequently used in simulating physical and mathematical systems. This method may be the most commonly applied statistical method in engineering and science disciplines. Another benefit is providing increased confidence that a model is robust using Monte Carlo testing.
Model development for generalized control system for water distribution network provides the simplification needed for the simulation of large systems. Model development is based on the study of symmetric and non symmetric small, irregular networks, as well as large, regular and open bifurcating water distribution system. The problem considered in this section is that of flow dynamics in simple to complex, regular network which bifurcates in the form of a branching tree. In addition the control application of the flow network is investigated using valves as the manipulated variables to control branch flow rates. Communication between the network hydraulics coming from EPANET and control algorithm develop on Matlab (Programming Language) can be generalized with the help of development of general purpose control algorithm model
Towards robust machine learning with graph neural networks
No full textIn order to apply Neural Networks in safety-critical settings, such as healthcare or autonomous driving, we need to be able to analyse their robustness against adversarial attacks. These attacks perturb natural images by adding small, carefully chosen perturbations to them that are imperceptible to the human eye. Trained neural networks with high training and validation accuracy often misclassify a large number of these perturbed images. In this thesis we propose several new methods aimed at analysing the robustness of trained neural networks to adversarial attacks.
In the first part, we improve upon existing methods to generate adversarial examples more efficiently. We note that past work in this field has relied on optimization methods that ignore the inherent structure of the problem and data, or generative methods that rely purely on learning and often fail to generate adversarial examples where they are hard to find. To alleviate these deficiencies, we propose a novel stand-alone attack based on a GNN that takes advantage of the strengths of both approaches. Our GNN computes descent directions to guide an iterative procedure towards adversarial examples.
Our next contribution is inspired by the observation that many state-of-the-art adversarial attacks require many random restarts to generate adversarial examples. Each time we perform a restart we ignore all previous unsuccessful runs. In order to alleviate this deficiency, we propose a method that learns from its mistakes. Specifically, our method uses GNNs as an attention, to greatly reduce the search space for future iterations of the attacks.
For our final contribution, we note that adversarial attacks may fail, even where adversarial examples exist. We thus focus on formal complete neural network verification which returns a sound and complete proof of robustness. Recent years have witnessed the deployment of branch-and-bound (BaB) frameworks for formal verification in deep learning. The main computational bottleneck of BaB is the estimation of lower bounds. Past work in this field has relied on traditional optimization algorithms whose inefficiencies have limited their scope. To alleviate this deficiency, we propose a novel graph neural network (GNN) based approach. Our GNN aims to compute a dual solution of the convex relaxation, thereby providing a valid lower bound, which, if positive, proves robustness
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