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At least 541 records · Page 30

Integrated Software for Analyzing Designs of Launch Vehicles

Launch Vehicle Analysis Tool (LVA) is a computer program for preliminary design structural analysis of launch vehicles. Before LVA was developed, in order to analyze the structure of a launch vehicle, it was necessary to estimate its weight, feed this estimate into a program to obtain pre-launch and flight loads, then feed these loads into structural and thermal analysis programs to obtain a second weight estimate. If the first and second weight estimates differed, it was necessary to reiterate these analyses until the solution converged. This process generally took six to twelve person-months of effort. LVA incorporates text to structural layout converter, configuration drawing, mass properties generation, pre-launch and flight loads analysis, loads output plotting, direct solution structural analysis, and thermal analysis subprograms. These subprograms are integrated in LVA so that solutions can be iterated automatically. LVA incorporates expert-system software that makes fundamental design decisions without intervention by the user. It also includes unique algorithms based on extensive research. The total integration of analysis modules drastically reduces the need for interaction with the user. A typical solution can be obtained in 30 to 60 minutes. Subsequent runs can be done in less than two minutes.

Philips, Alan D.↗

An Energy-Based Low-Order Approach for Mission Analysis of Air Vehicles in LEAPS

Mission analysis methods that allow rapid analysis of conceptual aircraft provide great benefits to designers because a large number of feasibility and optimization studies can be performed quickly. This paper presents a novel low-order mission analysis approach that will be included in a new aircraft analysis tool called the Layered and Extensible Aircraft Performance System, also known as LEAPS. This approach is based on the mission analysis method used in the Flight Optimization System, also known as FLOPS. FLOPS has been developed at NASA Langley Research Center for over 30 years, and it is mainly used to analyze conventional aircraft (e.g., gas turbine-powered aircraft). One of the main features of FLOPS is its ability to perform rapid mission analysis. This quick analysis turnaround makes FLOPS a suitable tool to perform a large number of trade studies and optimizations. For this reason, the main concepts applied in FLOPS will be used and expanded in LEAPS to allow the analysis of unconventional aircraft that use novel propulsion systems. This expanded approach includes the capability to handle electric propulsion systems as well as multiple propulsor classes at the same time. A novel hybrid-electric aircraft configuration is used to investigate the potential benefits of the proposed mission analysis approach. The results show that the design space increases which can potentially lead to better designs.

Capristan, Francisco M.↗

Systems analysis of a closed loop ECLSS using the ASPEN simulation tool. Thermodynamic efficiency analysis of ECLSS components

Our first goal in this project was to perform a systems analysis of a closed loop Environmental Control Life Support System (ECLSS). This pertains to the development of a model of an existing real system from which to assess the state or performance of the existing system. Systems analysis is applied to conceptual models obtained from a system design effort. For our modelling purposes we used a simulator tool called ASPEN (Advanced System for Process Engineering). Our second goal was to evaluate the thermodynamic efficiency of the different components comprising an ECLSS. Use is made of the second law of thermodynamics to determine the amount of irreversibility of energy loss of each component. This will aid design scientists in selecting the components generating the least entropy, as our penultimate goal is to keep the entropy generation of the whole system at a minimum.

Chatterjee, Sharmista↗

Exploring Mission Concepts with the JPL Innovation Foundry A-Team

The JPL Innovation Foundry has established a new approach for exploring, developing, and evaluating early concepts called the A-Team. The A-Team combines innovative collaborative methods with subject matter expertise and analysis tools to help mature mission concepts. Science, implementation, and programmatic elements are all considered during an A-Team study. Methods are grouped by Concept Maturity Level (CML), from 1 through 3, including idea generation and capture (CML 1), initial feasibility assessment (CML 2), and trade space exploration (CML 3). Methods used for each CML are presented, and the key team roles are described from two points of view: innovative methods and technical expertise. A-Team roles for providing innovative methods include the facilitator, study lead, and assistant study lead. A-Team roles for providing technical expertise include the architect, lead systems engineer, and integration engineer. In addition to these key roles, each A-Team study is uniquely staffed to match the study topic and scope including subject matter experts, scientists, technologists, flight and instrument systems engineers, and program managers as needed. Advanced analysis and collaborative engineering tools (e.g. cost, science traceability, mission design, knowledge capture, study and analysis support infrastructure) are also under development for use in A-Team studies and will be discussed briefly. The A-Team facilities provide a constructive environment for innovative ideas from all aspects of mission formulation to eliminate isolated studies and come together early in the development cycle when they can provide the biggest impact. This paper provides an overview of the A-Team, its study processes, roles, methods, tools and facilities.

Team Eureka↗

Three-dimensional inelastic analysis for hot section components, BEST 3D code

The goal is the development of an alternative stress analysis tool, distinct from the finite element method, applicable to the engineering analysis of gas turbine engine structures. The boundary element method was selected for this development effort on the basis of its already demonstrated applicability to a variety of geometries and problem types characteristic of gas turbine engine components. Major features of the BEST3D computer program are described, and some of the significant developments carried out as part of the Inelastic Methods Contract are outlined.

Wilson, Raymond B.↗

Integrated Analysis Capability Program

Integrated Analysis Capability (IAC) software system intended to provide highly effective, interactive analysis tool for integrated design of large structures. Supports needs of engineering analysis groups concerned with interdisciplinary problems. Developed to serve as software interface between computer programs from fields of structures, thermodynamics, controls, and dynamics of systems on one hand and executive software system and data base on other hand to yield highly efficient multi-disciplinary system. Special attention given to such users' requirements as handling data and online assistance with operational features and ability to add new modules of user's choice at future date. Written in FORTRAN 77.

Vos, R. G.↗

"Genetically Engineered" Nanoelectronics

The quantum mechanical functionality of nanoelectronic devices such as resonant tunneling diodes (RTDs), quantum well infrared-photodetectors (QWIPs), quantum well lasers, and heterostructure field effect transistors (HFETs) is enabled by material variations on an atomic scale. The design and optimization of such devices requires a fundamental understanding of electron transport in such dimensions. The Nanoelectronic Modeling Tool (NEMO) is a general-purpose quantum device design and analysis tool based on a fundamental non-equilibrium electron transport theory. NEW was combined with a parallelized genetic algorithm package (PGAPACK) to evolve structural and material parameters to match a desired set of experimental data. A numerical experiment that evolves structural variations such as layer widths and doping concentrations is performed to analyze an experimental current voltage characteristic. The genetic algorithm is found to drive the NEMO simulation parameters close to the experimentally prescribed layer thicknesses and doping profiles. With such a quantitative agreement between theory and experiment design synthesis can be performed.

Klimeck, Gerhard↗

Cultivating an Emergent Earth Observation Analytics Ecosystem in the Cloud

A diverse set of data analytics systems for Earth Observations are sprouting up in the Earth Science community, with a wealth of processing algorithms and analysis methods. There is a similar wealth of data resources available via myriad data providers and clearinghouses, including large institutional systems like the Earth Observing System Data and Information System, Comprehensive Large Scale Array-data Stewardship System, and Federated Earth Observation Missions gateway. With Earth system science driving a need to work with more datasets together, and the community developing more analysis tools (some of them dataset-specific), how can we develop analysis workflows that incorporate far-flung datasets and leverage analysis resources from multiple organizations? Cloud computing points the way toward a solution in two different respects. Firstly, the access to and abstraction of virtually unlimited storage and computing power provides an environment that enables more straightforward means of pulling datasets and analysis resources together. Just as importantly, however, cloud computing serves as an example of an "ecosystem" of interoperating services, since the essence of cloud computing is the presentation of all resources as a service, from hardware to infrastructure to platform to software. This enables the combination of off-the-shelf, diverse services to construct entire systems that emerge out of an equally diverse community of architects and developers. This approach can be similarly applied to the data and analysis resources in the Earth Observation community. By exposing these resources via well understood services, and consuming resources in the same way, different organizations can construct bespoke analysis workflows and systems for their own purposes. The key leap the community needs to make is to develop analysis systems in components that interact with other components via services. The result would be a rich ecosystem of analytics components that can be combined to analyze datasets at scale and in conjunction with other datasets from other sources.

chaos↗

"Genetically Engineered" Nanoelectronics

The Nanoelectronic Modeling Tool (NEMO) is a general-purpose quantum device design and analysis tool based on a fundamental non-equilibrium electron transport theory.

genetics↗

A Workflow to Rapidly Interrogate Multiscale Model Simulation Results Across Multiple Length Scales

Many tools can be used to visualize field and state variables for a single scale analysis so that the influence of relevant mechanisms can be evaluated. Finite element software is often utilized to simulate a unit cell of a material and visualize results at that scale. Material properties can be homogenized from individual constituents and local deformation, damage, and failure mechanisms can be evaluated within the unit cell due to globally applied boundary conditions. Such solutions can produce satisfactory results if a user is only interested in analyzing a single scale. But materials in general contain features across multiple length scales, and assumptions must be made when attempting to account for lower length scale phenomena within a higher length scale model. Multiscale modeling is an attractive means to model materials because detailed material responses can be tracked across multiple disparate length scales while reducing the amount of required assumptions. However, as the complexity of these models increases, a large amount of data can be produced, and data traceability can become increasingly more difficult. Field and state variables, which are naturally dependent on spatial position, may themselves be calculated from one or more lower length scale unit cell models each with their own appropriate field and state variables. The NASA Multiscale Analysis Tool (NASMAT) is one software that can be used to perform a multiscale analysis efficiently and output requested data at all length scales in the analysis. A companion open-source Python software, NASMAT PrePost, can be used to visualize NASMAT model results and rapidly interrogate multiscale data across multiple length scales. This presentation will demonstrate some of the key features of NASMAT PrePost on two multiscale problems by quickly displaying and demonstrating connectivity among multiscale results from large datasets.

Python↗

Improvements to the Flight Analysis and Simulation Tool (FAST) and Initial Development of the Genesis Flight Mechanics Simulation for Ascent, Aerocapture, Entry, Descent, and Landing (A2EDL) Trajectory Design

The NASA Engineering and Safety Center (NESC) was requested to provide significant enhancements to the Flight Analysis and Simulation Tool (FAST), a generic, variable-degree-of-freedom, multi-body ascent, aerocapture, entry, descent, and landing (A2EDL) flight simulation code and a key Agency analysis tool. This report details the upgrades to FAST that were completed, describes a change to the assessment’s scope that allowed its goals to be exceeded with a new and innovative approach, and discusses the results of the modified approach.

NASA Engineering and Safety Center; Flight Analysi↗

Interoperability of Tools at the CCMC

The CCMC has a diverse set of tools in many languages that support utilization of simulation outputs accessible through CCMC interactive archives. Some model output post-processing and analysis tools are delivered to tCCMC by the community. One such model output post-processing/utilization tool developed by the CCMC is the open source Kamodo package. Kamodo is developed primarily in Python (with some C) and has already established strong interoperability with other Python libraries inside PyHC and out. While that interoperability is important, interoperability with other languages and tools is as important. Many models are written in Fortran or C, and their ability to pull in data from a Python tool or export directly to other analysis software in a different language will greatly increase scientific productivity. Interoperability within Python is important, but broader interoperability is just as important.

CCMC↗

Efficient Multidisciplinary Analysis Approach for Conceptual Design of Aircraft with Large Shape Change

The conceptual and preliminary design processes for aircraft with large shape changes are generally difficult and time-consuming, and the processes are often customized for a specific shape change concept to streamline the vehicle design effort. Accordingly, several existing reports show excellent results of assessing a particular shape change concept or perturbations of a concept. The goal of the current effort was to develop a multidisciplinary analysis tool and process that would enable an aircraft designer to assess several very different morphing concepts early in the design phase and yet obtain second-order performance results so that design decisions can be made with better confidence. The approach uses an efficient parametric model formulation that allows automatic model generation for systems undergoing radical shape changes as a function of aerodynamic parameters, geometry parameters, and shape change parameters. In contrast to other more self-contained approaches, the approach utilizes off-the-shelf analysis modules to reduce development time and to make it accessible to many users. Because the analysis is loosely coupled, discipline modules like a multibody code can be easily swapped for other modules with similar capabilities. One of the advantages of this loosely coupled system is the ability to use the medium- to high-fidelity tools early in the design stages when the information can significantly influence and improve overall vehicle design. Data transfer among the analysis modules are based on an accurate and automated general purpose data transfer tool. In general, setup time for the integrated system presented in this paper is 2-4 days for simple shape change concepts and 1-2 weeks for more mechanically complicated concepts. Some of the key elements briefly described in the paper include parametric model development, aerodynamic database generation, multibody analysis, and the required software modules as well as examples for a telescoping wing, a folding wing, and a bat-like wing. The paper also includes the verification of a medium-fidelity aerodynamic tool used for the aerodynamic database generation with a steady and unsteady high-fidelity CFD analysis tool for a folding wing example.

Chwalowski, Pawel↗

Applied Meteorology Unit (AMU) Quarterly Report Fourth Quarter FY-13

Ms. Shafer completed the task to determine relationships between pressure gradients and peak winds at Vandenberg Air Force Base (VAFB), and began developing a climatology for the VAFB wind towers; Dr. Huddleston completed the task to develop a tool to help forecast the time of the first lightning strike of the day in the Kennedy Space Center (KSC)/Cape Canaveral Air Force Station (CCAFS) area; Dr. Bauman completed work on a severe weather forecast tool focused on the Eastern Range (ER), and also developed upper-winds analysis tools for VAFB and Wallops Fl ight Facility (WFF); Ms. Crawford processed and displayed radar data in the software she will use to create a dual-Doppler analysis over the east-central Florida and KSC/CCAFS areas; Mr. Decker completed developing a wind pairs database for the Launch Services Program to use when evaluating upper-level winds for launch vehicles; Dr. Watson continued work to assimilate observational data into the high-resolution model configurations she created for WFF and the ER.

Bauman, William↗

Langley Research Center contributions in advancing active control technology

The application of active control technology to reduce aeroelastic response of aircraft structures offers a potential for significant payoffs in terms of aerodynamic efficiency and weight savings. Some of the contributions of the Langley Research Center in advancing active control technology are described. Contributions are categorized into the development of appropriate analysis tools, control law synthesis methodology, and experimental investigations aimed at verifying both analysis and synthesis methodology.

Abel, I.↗

Overview of Langley activities in active controls research

The application of active controls technology to reduce aeroelastic response of aircraft structures offers a potential for significant payoffs in terms of aerodynamic efficiency and weight savings. The activities of the Langley Research Center (laRC) in advancing active controls technology. Activities are categorized into the development of appropriate analysis tools, control law synthesis methodology, and experimental investigations aimed at verifying both analysis and synthesis methodology.

Abel, I.↗

Space transportation vehicle design evaluation using saturated designs

An important objective in the preliminary design and evaluation of space transportation vehicles is to find the best values of design variables that optimize the performance characteristic (e.g. dry weight). For a given configuration, the vehicle performance can be determined by the use of complex sizing and performance evaluation computer programs. These complex computer programs utilize iterative algorithms and they are generally too expensive and/or difficult to use directly in multidisciplinary design optimization. An alternative is to use response surface methodology (RSM) and obtain quadratic polynomial approximations to the functional relationships between performance characteristics and design variables. In RSM, these approximation models are then used to determine optimum design parameter values and for rapid sensitivity studies. Constructing a second-order model requires that 'n' design parameters be studied at least at 3 levels (values) so that the coefficients in the model can be estimated. There, 3(n) factorial experiments (point designs or observations) may be necessary. For small values of 'n' such as two or three, this design works well. However, when a large number of design parameters are under study, the number of design points required for a full-factorial design may become excessive. Fortunately, these quadratic polynomial approximations can be obtained by selecting an efficient design matrix using central composite designs (CCD) from design of experiments theory. Each unique point design from the CCD matrix is then conducted using computerized analysis tools (e.g. POST, CONSIZ, etc.). In the next step, least squares regression analysis is used to calculate the quadratic polynomial coefficients from the data. However, in some multidisciplinary applications involving a large number of design variables and several disciplines, the computerized performance synthesis programs may get too time consuming and expensive to run even with the use of efficient central composite designs. In such cases, it may be preferable to keep the number of design points to an absolute minimum and trade some model accuracy with cost. For this purpose, another class of experimental designs, called saturated D-optimal designs may be utilized for generating a matrix of vehicle designs. A design is called saturated when the number of design points is exactly equal to the number of terms in the model to be fitted. As a result, saturated designs require the absolute minimum number of design points ((n+1)(n+2)/s) to estimate the quadratic polynomial model coefficients. Saturated designs can be generated using the D-optimality criterion. A good saturated design should give rise to least squares estimates with minimum generalized variance.

Unal, Resit↗