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At least 199 records · Page 11

Simulator design for advanced ISDN satellite design and experiments

This simulation design task completion report documents the simulation techniques associated with the network models of both the Interim Service ISDN (integrated services digital network) Satellite (ISIS) and the Full Service ISDN Satellite (FSIS) architectures. The ISIS network model design represents satellite systems like the Advanced Communication Technology Satellite (ACTS) orbiting switch. The FSIS architecture, the ultimate aim of this element of the Satellite Communications Applications Research (SCAR) program, moves all control and switching functions on-board the next generation ISDN communication satellite. The technical and operational parameters for the advanced ISDN communications satellite design will be obtained from the simulation of ISIS and FSIS engineering software models for their major subsystems. Discrete events simulation experiments will be performed with these models using various traffic scenarios, design parameters and operational procedures. The data from these simulations will be used to determine the engineering parameters for the advanced ISDN communications satellite.

Pepin, Gerald R.↗

Interim Service ISDN Satellite (ISIS) hardware experiment development for advanced ISDN satellite designs and experiments

The Interim Service Integrated Service Digital Network (ISDN) Satellite (ISIS) Hardware Experiment Development for Advanced Satellite Designs describes the development of the ISDN Satellite Terminal Adapter (ISTA) capable of translating ISDN protocol traffic into Time Division Multiple Access (TDMA) signals for use by a communications satellite. The ISTA connects the Type 1 Network Termination (NT1) via the U-interface on the line termination side of the CPE to the RS-499 interface for satellite uplink. The same ISTA converts in the opposite direction the RS-499 to U-interface data with a simple switch setting.

Pepin, Gerard R.↗

Experiments and other methods for developing expertise with design of experiments in a classroom setting

The only way to gain genuine expertise in Statistical Process Control (SPC) and the design of experiments (DOX) is with repeated practice, but not on canned problems with dead data sets. Rather, one must negotiate a wide variety of problems each with its own peculiarities and its own constantly changing data. The problems should not be of the type for which there is a single, well-defined answer that can be looked up in a fraternity file or in some text. The problems should match as closely as possible the open-ended types for which there is always an abundance of uncertainty. These are the only kinds that arise in real research, whether that be basic research in academe or engineering research in industry. To gain this kind of experience, either as a professional consultant or as an industrial employee, takes years. Vast amounts of money, not to mention careers, must be put at risk. The purpose here is to outline some realistic simulation-type lab exercises that are so simple and inexpensive to run that the students can repeat them as often as desired at virtually no cost. Simulations also allow the instructor to design problems whose outcomes are as noisy as desired but still predictable within limits. Also the instructor and the students can learn a great deal more from the postmortum conducted after the exercise is completed. One never knows for sure what the true data should have been when dealing only with real life experiments. To add a bit more realism to the exercises, it is sometimes desirable to make the students pay for each experimental result from a make-believe budget allocation for the problem.

Patterson, John W.↗

Propagation of Computational Uncertainty Using the Modern Design of Experiments

This paper describes the use of formally designed experiments to aid in the error analysis of a computational experiment. A method is described by which the underlying code is approximated with relatively low-order polynomial graduating functions represented by truncated Taylor series approximations to the true underlying response function. A resource-minimal approach is outlined by which such graduating functions can be estimated from a minimum number of case runs of the underlying computational code. Certain practical considerations are discussed, including ways and means of coping with high-order response functions. The distributional properties of prediction residuals are presented and discussed. A practical method is presented for quantifying that component of the prediction uncertainty of a computational code that can be attributed to imperfect knowledge of independent variable levels. This method is illustrated with a recent assessment of uncertainty in computational estimates of Space Shuttle thermal and structural reentry loads attributable to ice and foam debris impact on ascent.

DeLoach, Richard↗

Design of Orion Soil Impact Study using the Modern Design of Experiments

Two conventional One Factor At a Time (OFAT) test matrices under consideration for an Orion Landing System subscale soil impact study are reviewed. Certain weaknesses in the designs, systemic to OFAT experiment designs generally, are identified. An alternative test matrix is proposed that is based in the Modern Design of Experiments (MDOE), which achieves certain synergies by combining the original two test matrices into one. The attendant resource savings are quantified and the impact on uncertainty is discussed.

DeLoach, Richard↗

Some experiences in aircraft aeroelastic design using Preliminary Aeroelastic Design of Structures (PAD)

The design experience associated with a benchmark aeroelastic design of an out of production transport aircraft is discussed. Current work being performed on a high aspect ratio wing design is reported. The Preliminary Aeroelastic Design of Structures (PADS) system is briefly summarized and some operational aspects of generating the design in an automated aeroelastic design environment are discussed.

Radovcich, N. A.↗

Nuclear Data Sensitivity/Uncertainty Studies of Tantalum-Reflected Systems

Tantalum (Ta) is a refractory metal with high melting point and high corrosion resistance. This makes it useful as a mold material for plutonium casting operations. Unfortunately, there are few criticality benchmarks with high nuclear data sensitivities. Given that, it is desirable to design new experiments to provide additional validation data for nuclear criticality safety, which is the objective of the Thales project. Multiple application models were used to represent process conditions (either normal conditions or credible upset conditions) both at Los Alamos National Laboratory (LANL) and Savannah River Site (SRS). A total of 40 application models were obtained. Given this, it was useful to down-select the number of needed application models. This work documents the down-selection based on several nuclear data sensitivity/uncertainty metrics. In addition to showing the result of the specific down-selection used for the Thales project, this work discusses potential ways to represent a large number of application models with a smaller number of proposed experiment designs.

42 ENGINEERING↗

A Hybrid Gradient Method to Designing Bayesian Experiments for Implicit Models

Bayesian experimental design (BED) aims at designing an experiment to maximize the information gathering from the collected data. The optimal design is usually achieved by maximizing the mutual information (MI) between the data and the model parameters. When the analytical expression of the MI is unavailable, e.g.,having implicit models with intractable data distributions, a neural network-based lower bound of the MI was recently proposed and a gradient ascent method was used to maximize the lower bound [1]. However, the approach in [1] requires a pathwise sampling path to compute the gradient of the MI lower bound with respect to the design variables, and such a pathwise sampling path is usually inaccessible for implicit models. In this work, we propose a hybrid gradient approach that leverages recent advances in variational MI estimator and evolution strategies (ES)combined with black-box stochastic gradient ascent (SGA) to maximize the MI lower bound. This allows the design process to be achieved through a unified scalable procedure for implicit models without sampling path gradients. Several experiments demonstrate that our approach significantly improves the scalability of BED for implicit models in high-dimensional design space.

Zhang, Jiaxin↗

Space Shuttle Debris Impact Tool Assessment Using the Modern Design of Experiments

Complex computer codes are used to estimate thermal and structural reentry loads on the Shuttle Orbiter induced by ice and foam debris impact during ascent. Such debris can create cavities in the Shuttle Thermal Protection System. The sizes and shapes of these cavities are approximated to accommodate a code limitation that requires simple "shoebox" geometries to describe the cavities -- rectangular areas and planar walls that are at constant angles with respect to vertical. These approximations induce uncertainty in the code results. The Modern Design of Experiments (MDOE) has recently been applied to develop a series of resource-minimal computational experiments designed to generate low-order polynomial graduating functions to approximate the more complex underlying codes. These polynomial functions were then used to propagate cavity geometry errors to estimate the uncertainty they induce in the reentry load calculations performed by the underlying code. This paper describes a methodological study focused on evaluating the application of MDOE to future operational codes in a rapid and low-cost way to assess the effects of cavity geometry uncertainty.

DeLoach, Richard↗

Optimizing Batch Crystallization with Model-based Design of Experiments

Poster for Foundations of Computer Aided Process Design (FOCAPD) 2024 describing the formality of model-based design of experiments for batch crystallization. This paper focuses on the implementation of model-based design of experiments for parameter precision, enabled by Pyomo.DoE, a package in Python. Specifically, this work outlines an identifiability analysis for the estimability of the model parameters in a batch crystallization system.

Lynch, Hailey↗

Advanced ISDN satellite designs and experiments

The research performed by GTE Government Systems and the University of Colorado in support of the NASA Satellite Communications Applications Research (SCAR) Program is summarized. Two levels of research were undertaken. The first dealt with providing interim services Integrated Services Digital Network (ISDN) satellite (ISIS) capabilities that accented basic rate ISDN with a ground control similar to that of the Advanced Communications Technology Satellite (ACTS). The ISIS Network Model development represents satellite systems like the ACTS orbiting switch. The ultimate aim is to move these ACTS ground control functions on-board the next generation of ISDN communications satellite to provide full-service ISDN satellite (FSIS) capabilities. The technical and operational parameters for the advanced ISDN communications satellite design are obtainable from the simulation of ISIS and FSIS engineering software models of the major subsystems of the ISDN communications satellite architecture. Discrete event simulation experiments would generate data for analysis against NASA SCAR performance measure and the data obtained from the ISDN satellite terminal adapter hardware (ISTA) experiments, also developed in the program. The Basic and Option 1 phases of the program are also described and include the following: literature search, traffic mode, network model, scenario specifications, performance measures definitions, hardware experiment design, hardware experiment development, simulator design, and simulator development.

Pepin, Gerard R.↗