OEXP Analysis Tools Workshop

This publication summarizes the software needs and available analysis tools presented at the OEXP Analysis Tools Workshop held at the NASA Langley Research Center, Hampton, Virginia on June 21 to 22, 1988. The objective of the workshop was to identify available spacecraft system (and subsystem) analysis and engineering design tools, and mission planning and analysis software that could be used for various NASA Office of Exploration (code Z) studies, specifically lunar and Mars missions

A strategy for reducing turnaround time in design optimization using a distributed computer system

There is a need to explore methods for reducing lengthly computer turnaround or clock time associated with engineering design problems. Different strategies can be employed to reduce this turnaround time. One strategy is to run validated analysis software on a network of existing smaller computers so that portions of the computation can be done in parallel. This paper focuses on the implementation of this method using two types of problems. The first type is a traditional structural design optimization problem, which is characterized by a simple data flow and a complicated analysis. The second type of problem uses an existing computer program designed to study multilevel optimization techniques. This problem is characterized by complicated data flow and a simple analysis. The paper shows that distributed computing can be a viable means for reducing computational turnaround time for engineering design problems that lend themselves to decomposition. Parallel computing can be accomplished with a minimal cost in terms of hardware and software

Sensitivity and optimization of composite structures using MSC/NASTRAN

Design sensitivity analysis for composites will soon be available in MSC/NASTRAN. The design variables for composites can be lamina thicknesses, orientation angles, material properties or a combination of all three. With the increasing use of composites in aerospace and automotive industries, this general capability can be used in its own right for carrying out sensitivity analysis of complicated real-life structures. As part of a research effort, the sensitivity analysis was coupled with a general purpose optimizer. This preliminary version of the optimizer is capable of dealing with minimum weight structural design with a rather general design variable linking capability at the element level or system level. Only sizing type of design variables (i.e., lamina thicknesses) can be handled by the optimizer. Test cases were run and validated by comparison with independent finite element packages. The linking of design sensitivity capability for composites in MSC/NASTRAN with an optimizer would give designers a powerful automated tool to carry out practical opitmization design of real-life complicated composite structures

Multi-objective/loading optimization for rotating composite flexbeams

With the evolution of advanced composites, the feasibility of designing bearingless rotor systems for high speed, demanding maneuver envelopes, and high aircraft gross weights has become a reality. These systems eliminate the need for hinges and heavily loaded bearings by incorporating a composite flexbeam structure which accommodates flapping, lead-lag, and feathering motions by bending and twisting while reacting full blade centrifugal force. The flight characteristics of a bearingless rotor system are largely dependent on hub design, and the principal element in this type of system is the composite flexbeam. As in any hub design, trade off studies must be performed in order to optimize performance, dynamics (stability), handling qualities, and stresses. However, since the flexbeam structure is the primary component which will determine the balance of these characteristics, its design and fabrication are not straightforward. It was concluded that: pitchcase and snubber damper representations are required in the flexbeam model for proper sizing resulting from dynamic requirements; optimization is necessary for flexbeam design, since it reduces the design iteration time and results in an improved design; and inclusion of multiple flight conditions and their corresponding fatigue allowables is necessary for the optimization procedure

Getting expert systems off the ground: Lessons learned from integrating model-based diagnostics with prototype flight hardware

As an initial attempt to introduce expert system technology into an onboard environment, a model based diagnostic system using the TRW MARPLE software tool was integrated with prototype flight hardware and its corresponding control software. Because this experiment was designed primarily to test the effectiveness of the model based reasoning technique used, the expert system ran on a separate hardware platform, and interactions between the control software and the model based diagnostics were limited. While this project met its objective of showing that model based reasoning can effectively isolate failures in flight hardware, it also identified the need for an integrated development path for expert system and control software for onboard applications. In developing expert systems that are ready for flight, artificial intelligence techniques must be evaluated to determine whether they offer a real advantage onboard, identify which diagnostic functions should be performed by the expert systems and which are better left to the procedural software, and work closely with both the hardware and the software developers from the beginning of a project to produce a well designed and thoroughly integrated application

Master of Science

thesisIn the United States, the buildings sector is responsible for approximately 40% of the national carbon dioxide (CO2) emissions. CO2 is created during the generation of heat and electricity, and has been linked to climate change, acid rain, a variety of health threats, surface water depletion, and the destruction of natural habitats. Building energy modeling is a powerful educational tool that building owners, architects, engineers, city planners, and policy makers can use to make informed decisions. The aim of this thesis is to simulate the reduction in CO2 emissions that may be achieved for three commercial buildings located in Salt Lake City, UT. The following two questions were used to guide this process: 1. How much can a building's annual CO2 emissions be reduced through a specific energy efficiency upgrade or policy? 2. How much can a building's annual CO2 emissions be reduced through the addition of a photovoltaic (PV) array? How large should the array be? Building energy simulations were performed with the Department of Energy's EnergyPlus software, commercial reference building models, and TMY3 weather data. The chosen models were a medium office building, a primary school, and a supermarket. Baseline energy consumption data were simulated for each model in order to identify changes that would have a meaningful impact. Modifications to the buildings construction and operation were considered before a PV array was incorporated. These modifications include (1) an improved building envelope, (2) reduced lighting intensity, and (3) modified HVAC temperature set points. The PV array sizing was optimized using a demand matching approach based on the method of least squares. The arrays tilt angle was optimized using the golden section search algorithm. Combined, energy efficiency upgrades and the PV array reduced building CO2 emissions by 58.6, 54.0, and 52.2% for the medium office, primary school, and supermarket, respectively. However, for these models, it was determined that the addition of a PV array is not feasible from a purely economic viewpoint. Several avenues for expansion of this research are presented in Chapter 5

Supercomputers, Monte Carlo simulation and regression analysis

Monte Carlo Technique;Supercomputer;computer science

Development and validation of an advanced low-order panel method

A low-order potential-flow panel code, PMARC, for modeling complex three-dimensional geometries, is currently being developed at NASA Ames Research Center. The PMARC code was derived from a code named VSAERO that was developed for Ames Research Center by Analytical Methods, Inc. In addition to modeling potential flow over three-dimensional geometries, the present version of PMARC includes several advanced features such as an internal flow model, a simple jet wake model, and a time-stepping wake model. Data management within the code was optimized by the use of adjustable size arrays for rapidly changing the size capability of the code, reorganization of the output file and adopting a new plot file format. Preliminary versions of a geometry preprocessor and a geometry/aerodynamic data postprocessor are also available for use with PMARC. Several test cases are discussed to highlight the capabilities of the internal flow model, the jet wake model, and the time-stepping wake model

Vector computers, Monte Carlo simulation, and regression analysis: An introduction (Version 2)

Monte Carlo Technique;Supercomputer;computer science

Modular Multilevel Converters with Module-Level Energy Storage for Medium Voltage Applications

This dissertation is on Modular Multilevel Converter (MMC) converter design and analysis and its integration with energy storage at the low voltage module-level. The developed converter concept and topology can be used in various applications especially for the support of intermittent renewable energy resources. The general converter structure is analyzed and extended to include integrated energy storage suitable but not limited to medium voltage applications. The behavior of the idealized structure is analyzed to obtain equations that govern general converter behavior and identify possible control loops. Detail mathematical switching model is developed for the MMC converter with generalized module structure. The switching model is averaged to obtain a large signal model and then reduced to obtain lower order models suitable for sizing and optimization. Open and compensated closed loop current control is proposed and extended to include feedback loops needed for full control of integrated energy storage. General sizing procedure with the optimization aspects is then proposed and used on the example system to obtain the converter structure parameters. The example system models are then used to fine tune the control and structure parameters and investigate the converter behavior