Development and application of the GIM code for the Cyber 203 computer

The GIM computer code for fluid dynamics research was developed. Enhancement of the computer code, implicit algorithm development, turbulence model implementation, chemistry model development, interactive input module coding and wing/body flowfield computation are described. The GIM quasi-parabolic code development was completed, and the code used to compute a number of example cases. Turbulence models, algebraic and differential equations, were added to the basic viscous code. An equilibrium reacting chemistry model and implicit finite difference scheme were also added. Development was completed on the interactive module for generating the input data for GIM. Solutions for inviscid hypersonic flow over a wing/body configuration are also presented

Automating Vehicles by Deep Reinforcement Learning using Task Separation with Hill Climbing

Within the context of autonomous driving a model-based reinforcement learning algorithm is proposed for the design of neural network-parameterized controllers. Classical model-based control methods, which include sampling- and lattice-based algorithms and model predictive control, suffer from the trade-off between model complexity and computational burden required for the online solution of expensive optimization or search problems at every short sampling time. To circumvent this trade-off, a 2-step procedure is motivated: first learning of a controller during offline training based on an arbitrarily complicated mathematical system model, before online fast feedforward evaluation of the trained controller. The contribution of this paper is the proposition of a simple gradient-free and model-based algorithm for deep reinforcement learning using task separation with hill climbing (TSHC). In particular, (i) simultaneous training on separate deterministic tasks with the purpose of encoding many motion primitives in a neural network, and (ii) the employment of maximally sparse rewards in combination with virtual velocity constraints (VVCs) in setpoint proximity are advocated.Comment: 10 pages, 6 figures, 1 tabl

High-order volterra model predictive control and its application to a nonlinear polymerisation process

Model Predictive Control (MPC) has recently found wide acceptance in the process industry, but the existing design and implementation methods are restricted to linear process models. A chemical process involves, however, severe nonlinearity which cannot be ignored in practice. This paper aims to solve this nonlinear control problem by extending MPC to nonlinear models. It develops an analytical framework for nonlinear model predictive control (NMPC), and also offers a third-order Volterra series based nonparametric nonlinear modelling technique for NMPC design which relieves practising engineers from the need for first deriving a physical-principles based model. An on-line realisation technique for implementing the NMPC is also developed. The NMPC is then applied to a Mitsubishi Chemicals polymerisation reaction process. The results show that this nonlinear MPC technique is feasible and very effective. It considerably outperforms linear and low-order Volterra model based methods. The advantages of the approach developed lie not only in control performance superior to existing NMPC methods, but also in relieving practising engineers from the need for deriving an analytical model and then converting it to a Volterra model through which the model can only be obtained up to the second order

A comparison of GC-FID and PTR-MS toluene measurements in ambient air under conditions of enhanced monoterpene loading

Toluene was measured using both a gas chromatographic system (GC), with a flame ionization detector (FID), and a proton transfer reaction-mass spectrometer (PTR-MS) at the AIRMAP atmospheric monitoring station Thompson Farm (THF) in rural Durham, NH during the summer of 2004. Simultaneous measurements of monoterpenes, including alpha- and beta-pinene, camphene, Delta(3)-carene, and d-limonene, by GC-FID demonstrated large enhancements in monoterpene mixing ratios relative to toluene, with median and maximum enhancement ratios of similar to 2 and similar to 30, respectively. A detailed comparison between the GC-FID and PTR-MS toluene measurements was conducted to test the specificity of PTR-MS for atmospheric toluene measurements under conditions often dominated by biogenic emissions. We derived quantitative estimates of potential interferences in the PTR-MS toluene measurements related to sampling and analysis of monoterpenes, including fragmentation of the monoterpenes and some of their primary carbonyl oxidation products via reactions with H(3)O(+), O(2)(+) and NO(+) in the PTR-MS drift tube. The PTR-MS and GC-FID toluene measurements were in good quantitative agreement and the two systems tracked one another well from the instrumental limits of detection to maximum mixing ratios of similar to 0.5 ppbv. A correlation plot of the PTR-MS versus GC-FID toluene measurements was described by the least squares regression equation y=(1.13 +/- 0.02)x-(0.008 +/- 0.003) ppbv, suggesting a small similar to 13% positive bias in the PTR-MS measurements. The bias corresponded with a similar to 0.055 ppbv difference at the highest measured toluene level. The two systems agreed quantitatively within the combined 1 sigma measurement precisions for 60% of the measurements. Discrepancies in the measured mixing ratios were not well correlated with enhancements in the monoterpenes. Better quantitative agreement between the two systems was obtained by correcting the PTR-MS measurements for contributions from monoterpene fragmentation in the PTR-MS drift tube; however, the improvement was minor (\u3c10%). Interferences in the PTRMS measurements from fragmentation of the monoterpene oxidation products pinonaldehyde, caronaldehyde and alpha-pinene oxide were also likely negligible. A relatively large and variable toluene background in the PTR-MS instrument likely drove the measurement bias; however, the precise contribution was difficult to accurately quantify and thus was not corrected for in this analysis. The results from THF suggest that toluene can be reliably quantified by PTR-MS using our operating conditions (drift tube pressure, temperature and voltage of 2.0 mbar, 45 degrees C and 600V, respectively) under the ambient compositions probed. This work extends the range of field conditions under which PTR-MS validation studies have been conducted

The prevalence of coeliac disease-associated human leukocyte antigens in South African transplant donors and recipients

Background. Coeliac disease (CD) is an autoimmune condition occurring in genetically predisposed individuals exposed to an environmental trigger. The human leukocyte antigen (HLA) haplotypes HLA-DQ2.5 and HLA-DQ8 have the strongest association with CD, and 90 - 95% of CD patients bear these haplotypes. The susceptibility of the South African (SA) population to CD has not been studied previously.Objectives. To describe the genetic propensity of the SA population to CD.Methods. The South African National Blood Service database was used to analyse the prevalence of HLA-DQ2.5 and HLA-DQ8 in potential donors and recipients of organ transplants. Self-reported ethnic group was used to estimate the prevalence among different population groups.Results. The overall prevalence of HLA-DQ2.5 and HLA-DQ8 was 19.8%. The prevalence was lower in black participants (15.9%) than in whites (28.6%). Coloured (22.0%) and Indian (17.4%) participants had an intermediate prevalence. There was no significant difference between potential transplant donors and recipients.Conclusions. The prevalence of HLA-DQ2.5 and HLA-DQ8 differed among SA study participants of different ethnicities. However, the notion that CD does not occur in black South Africans owing to lack of a genetic predisposition is incorrect