9,676 research outputs found
Main specifications of CFD codes for WUIVIEW activities
CFD simulations will be the core activity of the WUVIEW performance based fire safety analysis. The purpose of this document is to provide WUIVIEW partners with a general overview of the CFD codes to be used in the Action.
The general simulation framework is described, particularly highlighting data inputs and scenario description requirements, to be developed in subsequent WUIVIEW WPs. This TN provides the technical foundations and main specifications of the databases to be designed within the WUIVIEW working program (ongoing action by UPC).Postprint (updated version
On Realization of Cinema Hall Fire Simulation Using Fire Dynamics Simulator
Currently known fire models are capable to describe fire dynamics in complex environments incorporating a wide variety of fire-related physical and chemical phenomena and utilizing large computational power of contemporary computers. In this paper, some issues related to realization of the simulation of fire in a cinema hall with sloping floor and curved ceiling furnished by upholstered seats modelled by FDS (Fire Dynamics Simulator) are discussed. The paper concentrates particularly on the impact of a computational meshes choice on resolving flow field and turbulence in the simulation and indicates problems related to parallelization of the calculation illustrated comparing sequential and parallel MPI calculation using 6 CPU cores. Results of the simulation described and their discussion demonstrate the ability of FDS simulation to capture main tendencies of smoke spread and to forecast the related safety risks realistically
BioSimulator.jl: Stochastic simulation in Julia
Biological systems with intertwined feedback loops pose a challenge to
mathematical modeling efforts. Moreover, rare events, such as mutation and
extinction, complicate system dynamics. Stochastic simulation algorithms are
useful in generating time-evolution trajectories for these systems because they
can adequately capture the influence of random fluctuations and quantify rare
events. We present a simple and flexible package, BioSimulator.jl, for
implementing the Gillespie algorithm, -leaping, and related stochastic
simulation algorithms. The objective of this work is to provide scientists
across domains with fast, user-friendly simulation tools. We used the
high-performance programming language Julia because of its emphasis on
scientific computing. Our software package implements a suite of stochastic
simulation algorithms based on Markov chain theory. We provide the ability to
(a) diagram Petri Nets describing interactions, (b) plot average trajectories
and attached standard deviations of each participating species over time, and
(c) generate frequency distributions of each species at a specified time.
BioSimulator.jl's interface allows users to build models programmatically
within Julia. A model is then passed to the simulate routine to generate
simulation data. The built-in tools allow one to visualize results and compute
summary statistics. Our examples highlight the broad applicability of our
software to systems of varying complexity from ecology, systems biology,
chemistry, and genetics. The user-friendly nature of BioSimulator.jl encourages
the use of stochastic simulation, minimizes tedious programming efforts, and
reduces errors during model specification.Comment: 27 pages, 5 figures, 3 table
Conedy: a scientific tool to investigate Complex Network Dynamics
We present Conedy, a performant scientific tool to numerically investigate
dynamics on complex networks. Conedy allows to create networks and provides
automatic code generation and compilation to ensure performant treatment of
arbitrary node dynamics. Conedy can be interfaced via an internal script
interpreter or via a Python module
Experimental Design of a Prescribed Burn Instrumentation
Observational data collected during experiments, such as the planned Fire and
Smoke Model Evaluation Experiment (FASMEE), are critical for progressing and
transitioning coupled fire-atmosphere models like WRF-SFIRE and WRF-SFIRE-CHEM
into operational use. Historical meteorological data, representing typical
weather conditions for the anticipated burn locations and times, have been
processed to initialize and run a set of simulations representing the planned
experimental burns. Based on an analysis of these numerical simulations, this
paper provides recommendations on the experimental setup that include the
ignition procedures, size and duration of the burns, and optimal sensor
placement. New techniques are developed to initialize coupled fire-atmosphere
simulations with weather conditions typical of the planned burn locations and
time of the year. Analysis of variation and sensitivity analysis of simulation
design to model parameters by repeated Latin Hypercube Sampling are used to
assess the locations of the sensors. The simulations provide the locations of
the measurements that maximize the expected variation of the sensor outputs
with the model parameters.Comment: 35 pages, 4 tables, 28 figure
Engineering Resilient Collective Adaptive Systems by Self-Stabilisation
Collective adaptive systems are an emerging class of networked computational
systems, particularly suited in application domains such as smart cities,
complex sensor networks, and the Internet of Things. These systems tend to
feature large scale, heterogeneity of communication model (including
opportunistic peer-to-peer wireless interaction), and require inherent
self-adaptiveness properties to address unforeseen changes in operating
conditions. In this context, it is extremely difficult (if not seemingly
intractable) to engineer reusable pieces of distributed behaviour so as to make
them provably correct and smoothly composable.
Building on the field calculus, a computational model (and associated
toolchain) capturing the notion of aggregate network-level computation, we
address this problem with an engineering methodology coupling formal theory and
computer simulation. On the one hand, functional properties are addressed by
identifying the largest-to-date field calculus fragment generating
self-stabilising behaviour, guaranteed to eventually attain a correct and
stable final state despite any transient perturbation in state or topology, and
including highly reusable building blocks for information spreading,
aggregation, and time evolution. On the other hand, dynamical properties are
addressed by simulation, empirically evaluating the different performances that
can be obtained by switching between implementations of building blocks with
provably equivalent functional properties. Overall, our methodology sheds light
on how to identify core building blocks of collective behaviour, and how to
select implementations that improve system performance while leaving overall
system function and resiliency properties unchanged.Comment: To appear on ACM Transactions on Modeling and Computer Simulatio
Resilience in Numerical Methods: A Position on Fault Models and Methodologies
Future extreme-scale computer systems may expose silent data corruption (SDC)
to applications, in order to save energy or increase performance. However,
resilience research struggles to come up with useful abstract programming
models for reasoning about SDC. Existing work randomly flips bits in running
applications, but this only shows average-case behavior for a low-level,
artificial hardware model. Algorithm developers need to understand worst-case
behavior with the higher-level data types they actually use, in order to make
their algorithms more resilient. Also, we know so little about how SDC may
manifest in future hardware, that it seems premature to draw conclusions about
the average case. We argue instead that numerical algorithms can benefit from a
numerical unreliability fault model, where faults manifest as unbounded
perturbations to floating-point data. Algorithms can use inexpensive "sanity"
checks that bound or exclude error in the results of computations. Given a
selective reliability programming model that requires reliability only when and
where needed, such checks can make algorithms reliable despite unbounded
faults. Sanity checks, and in general a healthy skepticism about the
correctness of subroutines, are wise even if hardware is perfectly reliable.Comment: Position Pape
A survey of high level frameworks in block-structured adaptive mesh refinement packages
pre-printOver the last decade block-structured adaptive mesh refinement (SAMR) has found increasing use in large, publicly available codes and frameworks. SAMR frameworks have evolved along different paths. Some have stayed focused on specific domain areas, others have pursued a more general functionality, providing the building blocks for a larger variety of applications. In this survey paper we examine a representative set of SAMR packages and SAMR-based codes that have been in existence for half a decade or more, have a reasonably sized and active user base outside of their home institutions, and are publicly available. The set consists of a mix of SAMR packages and application codes that cover a broad range of scientific domains. We look at their high-level frameworks, their design trade-offs and their approach to dealing with the advent of radical changes in hardware architecture. The codes included in this survey are BoxLib, Cactus, Chombo, Enzo, FLASH, and Uintah
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