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At least 19 records

Real time computations of cryogenic He properties

The Fermilab PIP-II (proton improvement plan - II) project is being constructed at Fermilab to deliver $800\,MeV$ protons of $>1\,MW$ beam power to replace the present LINAC and provide protons to the remainder of the existing accelerator complex. The new LINAC consists of a warm front end, 23 superconducting RF cryomodules, and a beam transfer line to the existing complex. The cryomodules (CMs) are to be tested at Fermilab's CryoModule Test Facility (CMTF).An important measurement in cryogenic testing is the heat load of each CM. Traditionally, at Fermilab, these measurements were made collecting archived data offline and analyzing it. The new control system for PIP-II is being developed with the EPICS (Experimental Physics and Industrial Control System) framework, which allows us to compute the heat load in real time using the HePak library.We are exploring other $He$ properties, such as flow, where flow meters are not available, which can also be calculated in real time and fed back to the cryogenics engineers.This paper details the real time heat load calculation and $He$ flow software developed for CM testing at CMTF, as well as the first results from the prototype HB650 CM. Future plans for 2-phase $LHe$ flow will also be outlined.

Hanlet, Pierrick [Fermilab]↗

A tool for modeling concurrent real-time computation

Real-time computation is a significant area of research in general, and in AI in particular. The complexity of practical real-time problems demands use of knowledge-based problem solving techniques while satisfying real-time performance constraints. Since the demands of a complex real-time problem cannot be predicted (owing to the dynamic nature of the environment) powerful dynamic resource control techniques are needed to monitor and control the performance. A real-time computation model for a real-time tool, an implementation of the QP-Net simulator on a Symbolics machine, and an implementation on a Butterfly multiprocessor machine are briefly described.

Sharma, D. D.↗

Effects of the computational time step on numerical solutions for turbulent flow

Effects of large computational time steps on the computed turbulence were investigated using a fully implicit method. In turbulent channel flow computations the largest computational time step in wall units which led to accurate prediction of turbulence statistics was determined. Turbulence fluctuations could not be sustained if the computational time step was near or larger than the Kolmogorov time scale.

Choi, Haecheon↗

Characterization of real-time computers

A real-time system consists of a computer controller and controlled processes. Despite the synergistic relationship between these two components, they have been traditionally designed and analyzed independently of and separately from each other; namely, computer controllers by computer scientists/engineers and controlled processes by control scientists. As a remedy for this problem, in this report real-time computers are characterized by performance measures based on computer controller response time that are: (1) congruent to the real-time applications, (2) able to offer an objective comparison of rival computer systems, and (3) experimentally measurable/determinable. These measures, unlike others, provide the real-time computer controller with a natural link to controlled processes. In order to demonstrate their utility and power, these measures are first determined for example controlled processes on the basis of control performance functionals. They are then used for two important real-time multiprocessor design applications - the number-power tradeoff and fault-masking and synchronization.

Shin, K. G.↗

Orbital flux integrations: Parameter values for effective computer time reductions

To improve computer utilization and to reduce the cost of orbital flux integrations, the effects of integration parameters 'duration' (T) and 'stepsize' (delta t) on integration results were investigated. Over given ranges of T and delta t, and within specified acceptable accuracy restraints, optimal values of these parameters were established for circular subsynchronous trajectories, in terms of the variables altitude (H) and inclination (i). It is shown that (1) above a certain statistically important value, duration is independent of both h and i; (2) stepsize has a relative altitude dependence; and (3) stepsize is not a function of inclination. The substantial savings in computer time are discussed along with the possibility of greater savings by relaxing accuracy restrictions while not exceeding the minimum model-associated uncertainty factors of the environments.

Stassinopoulos, E. G.↗

Attentional Ptycho-Tomography (APT) for three-dimensional nanoscale X-ray imaging with minimal data acquisition and computation time

Abstract Noninvasive X-ray imaging of nanoscale three-dimensional objects, such as integrated circuits (ICs), generally requires two types of scanning: ptychographic, which is translational and returns estimates of the complex electromagnetic field through the IC; combined with a tomographic scan, which collects these complex field projections from multiple angles. Here, we present Attentional Ptycho-Tomography (APT), an approach to drastically reduce the amount of angular scanning, and thus the total acquisition time. APT is machine learning-based, utilizing axial self-Attention for Ptycho-Tomographic reconstruction. APT is trained to obtain accurate reconstructions of the ICs, despite the incompleteness of the measurements. The training process includes regularizing priors in the form of typical patterns found in IC interiors, and the physics of X-ray propagation through the IC. We show that APT with ×12 reduced angles achieves fidelity comparable to the gold standard Simultaneous Algebraic Reconstruction Technique (SART) with the original set of angles. When using the same set of reduced angles, then APT also outperforms Filtered Back Projection (FBP), Simultaneous Iterative Reconstruction Technique (SIRT) and SART. The time needed to compute the reconstruction is also reduced, because the trained neural network is a forward operation, unlike the iterative nature of these alternatives. Our experiments show that, without loss in quality, for a 4.48 × 93.2 × 3.92 µm 3 IC (≃6 × 10 8 voxels), APT reduces the total data acquisition and computation time from 67.96 h to 38 min. We expect our physics-assisted and attention-utilizing machine learning framework to be applicable to other branches of nanoscale imaging, including materials science and biological imaging.

47 OTHER INSTRUMENTATION↗

Comparing computational times for simulations when using PBPK model template and stand-alone implementations of PBPK models

Introduction We previously developed a PBPK model template that consists of a single model “superstructure” with equations and logic found in many physiologically based pharmacokinetic (PBPK) models. Using the template, one can implement PBPK models with different combinations of structures and features. Methods To identify factors that influence computational time required for PBPK model simulations, we conducted timing experiments using various implementations of PBPK models for dichloromethane and chloroform, including template and stand-alone implementations, and simulating four different exposure scenarios. For each experiment, we measured the required computational time and evaluated the impacts of including various model features (e.g., number of output variables calculated) and incorporating various design choices (e.g., different methods for estimating blood concentrations). Results We observed that model implementations that treat body weight and dependent quantities as constant (fixed) parameters can result in a 30% time savings compared with options that treat body weight and dependent quantities as time-varying. We also observed that decreasing the number of state variables by 36% in our PBPK model template led to a decrease of 20–35% in computational time. Other factors, such as the number of output variables, the method for implementing conditional statements, and the method for estimating blood concentrations, did not have large impacts on simulation time. In general, simulations with PBPK model template implementations of models required more time than simulations with stand-alone implementations, but the flexibility and (human) time savings in preparing and reviewing a model implemented using the PBPK model template may justify the increases in computational time requirements. Conclusion Our findings concerning how PBPK model design and implementation decisions impact computational speed can benefit anyone seeking to develop, improve, or apply a PBPK model, with or without the PBPK model template.

Bernstein, Amanda S.↗

Effects of computing time delay on real-time control systems

The reliability of a real-time digital control system depends not only on the reliability of the hardware and software used, but also on the speed in executing control algorithms. The latter is due to the negative effects of computing time delay on control system performance. For a given sampling interval, the effects of computing time delay are classified into the delay problem and the loss problem. Analysis of these two problems is presented as a means of evaluating real-time control systems. As an example, both the self-tuning predicted (STP) control and Proportional-Integral-Derivative (PID) control are applied to the problem of tracking robot trajectories, and their respective effects of computing time delay on control performance are comparatively evaluated. For this example, the STP (PID) controller is shown to outperform the PID (STP) controller in coping with the delay (loss) problem.

Shin, Kang G.↗

Vibration Analysis Reduces Computer Time

Improved calculation method promises to reduce computer time by factor of 10 for vibration analysis of complex structures. Method originally developed to predict mechanical response of spacecraft to maneuvers in various cases in which same booster is used with different payloads. Method is more exact than conventional normal-mode methods; it involves no initial approximations of assumptions. Calculation cost is reduced without loss of accuracy.

Engels, R. C.↗