The chaos machine: analogue computing rediscovered (1)

Analogue computers provide actual rather than virtual representations of model systems. They are powerful and engaging computing machines that are cheap and simple to build. This two-part Retronics article helps you build (and understand!) your own analogue computer to simulate the Lorenz butterfly that's become iconic for Chaos theory

Fat vs. thin threading approach on GPUs: application to stochastic simulation of chemical reactions

We explore two different threading approaches on a graphics processing unit (GPU) exploiting two different characteristics of the current GPU architecture. The fat thread approach tries to minimise data access time by relying on shared memory and registers potentially sacrificing parallelism. The thin thread approach maximises parallelism and tries to hide access latencies. We apply these two approaches to the parallel stochastic simulation of chemical reaction systems using the stochastic simulation algorithm (SSA) by Gillespie (J. Phys. Chem, Vol. 81, p. 2340-2361, 1977). In these cases, the proposed thin thread approach shows comparable performance while eliminating the limitation of the reaction system’s size

STOCHSIMGPU Parallel stochastic simulation for the Systems\ud Biology Toolbox 2 for MATLAB

Motivation: The importance of stochasticity in biological systems is becoming increasingly recognised and the computational cost of biologically realistic stochastic simulations urgently requires development of efficient software. We present a new software tool STOCHSIMGPU which exploits graphics processing units (GPUs)for parallel stochastic simulations of biological/chemical reaction systems and show that significant gains in efficiency can be made. It is integrated into MATLAB and works with the Systems Biology Toolbox 2 (SBTOOLBOX2) for MATLAB.\ud \ud Results: The GPU-based parallel implementation of the Gillespie stochastic simulation algorithm (SSA), the logarithmic direct method (LDM), and the next reaction method (NRM) is approximately 85 times faster than the sequential implementation of the NRM on a central processing unit (CPU). Using our software does not require any changes to the user’s models, since it acts as a direct replacement of the stochastic simulation software of the SBTOOLBOX2

Applicability of the Peclet number approach to blow-off and flashback limits of common steelworks process gases

The ever-increasing importance of energy efficiency has given rise to numerous areas of concern for operators and developers of combustion plants; as the need to utilise fuel gases of increasingly poor quality and variability is essential for sustainability, while emission standards continuing to become more stringent. Swirl combustors are ubiquitous in industry owing to their great stability range which occurs due to the formation of a CRZ, which through the recycling of heat and active chemical species to the root of the flame enhances stability over a wide range of operating conditions. Alternative fuels containing hydrogen offer the possibility of reduced greenhouse gas emissions; however flashback is of special concern with hydrogen enriched fuels, owing to the very high flame speed of hydrogen. Many by-products of process and waste industries can include a high proportion of hydrogen, for example Coke Oven Gas. Alternatively, many by-product process gases can contain a high proportion of non-combustible species such as nitrogen and carbon dioxide which can substantially reduce their flame speed and as a consequence increase the possibility of the flame extinguishing through blow-off. This paper examines the blow-off and flashback potential of common steelworks process gases (including one which contains hydrogen) in a compact, premixed swirl burner in swirl number regimes representative of those found in practical systems. Methane is used as a base fuel for comparison. All results are obtained at atmospheric pressure without air preheat. The Peclet number modelling approach incorporating a flame quenching parameter was applied to the results obtained for each of the fuel gases. Using this model, the quench factor value was seen to be dependent on burner configuration as well as fuel composition. It was found that the stable burner operating conditions significantly change from fuel to fuel; with the operating points at which flashback occurs with Coke Oven Gas producing blow-off with weaker process gases such as Blast Furnace Gas and Basic Oxygen Steelmaking gas

Research Notes : Genes y9 and y11 for similar chlorophyll deficiencies prove to be non-allelic

T219H and Tl35, two of the more vigorous chlorophyll-deficient types in the Genetic Type Collection, both have distinctly light green foliage through-out their life cycle. They are controlled by different genes since the Tl35 phenotype is caused by a homozygote, y9y9 (Probst, 1950), and the T219H phenotype by a heterozygote, Y11Y11 (Y11Y11 has a bright orange-yellow seedling-lethal phenotype) (Weber and Weiss, 1959). However, because of the similar phenotypes, it has been suggested that y9 and y11 may be multiple alleles at the same locus

Accessibility of physical states and non-uniqueness of entanglement measure

Ordering physical states is the key to quantifying some physical property of the states uniquely. Bipartite pure entangled states are totally ordered under local operations and classical communication (LOCC) in the asymptotic limit and uniquely quantified by the well-known entropy of entanglement. However, we show that mixed entangled states are partially ordered under LOCC even in the asymptotic limit. Therefore, non-uniqueness of entanglement measure is understood on the basis of an operational notion of asymptotic convertibility.Comment: 8 pages, 1 figure. v2: main result unchanged but presentation extensively changed. v3: figure added, minor correction