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Standardized Sky Partitioning for the Next Generation Astronomy and Space Science Archives

The Johns Hopkins University and Space Telescope Science Institute are working together on this project to develop a library of standard software for data archives that will benefit the wider astronomical community. The ultimate goal was to develop and distribute a software library aimed at providing a common system for partitioning and indexing the sky in manageable sized regions and provide complex queries on the objects stored in this system. Whilst ongoing maintenance work will continue the primary goal has been completed. Most of the next generation sky surveys in the different wavelengths like 2MASS, GALEX, SDSS, GSC-II, DPOSS and FIRST have agreed on this common set of utilities. In this final report, we summarize work on the work elements assigned to the STScI project team.

Lal, Nand↗

Electron lithography STAR design guidelines. Part 1: The STAR user design manual

The STAR system developed by NASA enables any user with a logic diagram to design a semicustom digital MOS integrated circuit. The system is comprised of a library of standard logic cells and computer programs to place, route, and display designs implemented with cells from the library. Library cells of the CMOS metal gate and CMOS silicon gate technologies were simulated using SPICE, and the results are shown and compared.

Trotter, J. D.↗

Electron lithography STAR design guidelines. Part 2: The design of a STAR for space applications

The STAR design system developed by NASA enables any user with a logic diagram to design a semicustom digital MOS integrated circuit. The system is comprised of a library of standard logic cells and computr programs to place, route, and display designs implemented with cells from the library. Also described is the development of a radiation-hard array designed for the STAR system. The design is based on the CMOS silicon gate technology developed by SANDIA National Laboratories. The design rules used are given as well as the model parameters developed for the basic array element. Library cells of the CMOS metal gate and CMOS silicon gate technologies were simulated using SPICE, and the results are shown and compared.

Trotter, J. D.↗

Field Encapsulation Library The FEL 2.2 User Guide

This document describes version 2.2 of the Field Encapsulation Library (FEL), a library of mesh and field classes. FEL is a library for programmers - it is a "building block" enabling the rapid development of applications by a user. Since FEL is a library intended for code development, it is essential that enough technical detail be provided so that one can make full use of the code. Providing such detail requires some assumptions with respect to the reader's familiarity with the library implementation language, C++, particularly C++ with templates. We have done our best to make the explanations accessible to those who may not be completely C++ literate. Nevertheless, familiarity with the language will certainly help one's understanding of how and why things work the way they do. One consolation is that the level of understanding essential for using the library is significantly less than the level that one should have in order to modify or extend the library. One more remark on C++ templates: Templates have been a source of both joy and frustration for us. The frustration stems from the lack of mature or complete implementations that one has to work with. Template problems rear their ugly head particularly when porting. When porting C code, successfully compiling to a set of object files typically means that one is almost done. With templated C++ and the current state of the compilers and linkers, generating the object files is often only the beginning of the fun. On the other hand, templates are quite powerful. Used judiciously, templates enable more succinct designs and more efficient code. Templates also help with code maintenance. Designers can avoid creating objects that are the same in many respects, but not exactly the same. For example, FEL fields are templated by node type, thus the code for scalar fields and vector fields is shared. Furthermore, node type templating allows the library user to instantiate fields with data types not provided by the FEL authors. This type of flexibility would be difficult to offer without the support of the language. For users who may be having template-related problems, we offer the consolation that support for C++ templates is destined to improve with time. Efforts such as the Standard Template Library (STL) will inevitably drive vendors to provide more thorough, optimized tools for template code development. Furthermore, the benefits will become harder to resist for those who currently subscribe to the least-common-denominator "code it all in C" strategy. May FEL bring you both increased productivity and aesthetic satisfaction.

Moran, Patrick J.↗

Hardware synthesis from DDL description

The details of digital systems can be conveniently input into the design automation system by means of hardware description language (HDL). The computer aided design and test (CADAT) system at NASA MSFC is used for the LSI design. The digital design language (DDL) was selected as HDL for the CADAT System. DDL translator output can be used for the hardware implementation of the digital design. Problems of selecting the standard cells from the CADAT standard cell library to realize the logic implied by the DDL description of the system are addressed.

Shiva, S. G.↗

Hardware synthesis from DDL

The details of the digital systems can be conveniently input into the design automation system by means of Hardware Description Languages (HDL). The Computer Aided Design and Test (CADAT) system at NASA MSFC is used for the LSI design. The Digital Design Language (DDL) has been selected as HDL for the CADAT System. DDL translator output can be used for the hardware implementation of the digital design. This paper addresses problems of selecting the standard cells from the CADAT standard cell library to realize the logic implied by the DDL description of the system.

Shah, A. M.↗

Data Systems Dynamic Simulator

The Data System Dynamic Simulator (DSDS) is a discrete event simulation tool. It was developed for NASA for the specific purpose of evaluating candidate architectures for data systems of the Space Station era. DSDS provides three methods for meeting this requirement. First, the user has access to a library of standard pre-programmed elements. These elements represent tailorable components of NASA data systems and can be connected in any logical manner. Secondly, DSDS supports the development of additional elements. This allows the more sophisticated DSDS user the option of extending the standard element set. Thirdly, DSDS supports the use of data streams simulation. Data streams is the name given to a technique that ignores packet boundaries, but is sensitive to rate changes. Because rate changes are rare compared to packet arrivals in a typical NASA data system, data stream simulations require a fraction of the CPU run time. Additionally, the data stream technique is considerably more accurate than another commonly-used optimization technique.

Rouff, Christopher↗

Ultraviolet Imaging Telescope photometry of massive stars - The OB association NGC 206 in M31

The Ultraviolet Imaging Telescope (UIT) obtained UV images of the giant M31 OB association NGC 206. Magnitudes in bands at 1520 and 2490 A were obtained for 30 massive stars, which demonstrate the effectiveness of UIT for photometry of moderately crowded hot stars to V about 21. The UV colors and magnitudes observed for stars in NGC 206 place them in the region of the color magnitude diagram occupied by evolutionary models for 30-60 solar mass stars, after correcting for extinction. The brighter stars are systematically redder than the fainter stars, indicating that they are supergiants of age about 4 Myr, while the fainter, bluer stars are nearer age zero. The relative numbers of probable supergiants measured by us and the number of probable main-sequence O stars measured from optical images are in agreement with the relative lifetimes. Calculated UIT colors are presented for a library of standard star spectra constructed from IUE and ground-based observations.

Hill, Jesse K.↗

Automating analog design: Taming the shrew

The pace of progress in the design of integrated circuits continues to amaze observers inside and outside of the industry. Three decades ago, a 50 transistor chip was a technological wonder. Fifteen year later, a 5000 transistor device would 'wow' the crowds. Today, 50,000 transistor chips will earn a 'not too bad' assessment, but it takes 500,000 to really leave an impression. In 1975 a typical ASIC device had 1000 transistors, took one year to first samples (and two years to production) and sold for about 5 cents per transistor. Today's 50,000 transistor gate array takes about 4 months from spec to silicon, works the first time, and sells for about 0.02 cents per transistor. Fifteen years ago, the single most laborious and error prone step in IC design was the physical layout. Today, most IC's never see the hand of a layout designer: and automatic place and route tool converts the engineer's computer captured schematic to a complete physical design using a gate array or a library of standard cells also created by software rather than by designers. CAD has also been a generous benefactor to the digital design process. The architect of today's digital systems creates the design using an RTL or other high level simulator. Then the designer pushes a button to invoke the logic synthesizer-optimizer tool. A fault analyzer checks the result for testability and suggests where scan based cells will improve test coverage. One obstinate holdout amidst this parade of progress is the automation of analog design and its reduction to semi-custom techniques. This paper investigates the application of CAD techniques to analog design.

Barlow, A.↗

Fast interrupt platform for extended DOS

Extended DOS offers the unique combination of a simple operating system which allows direct assess to the interrupt tables, 32 bit protected mode access to a 4096 MByte address space, and the use of industry standard C compilers. The drawback is that fast interrupt handling requires both 32 bit and 16 bit versions of each real-time process interrupt handler to avoid mode switches on the interrupts. A set of tools has been developed which automates the process of transforming the output of a standard 32 bit C compiler to 16 bit interrupt code which directly handles the real mode interrupts. The entire process compiles one set of source code via a make file, which boosts productivity by making the management of the compile-link cycle very simple. The software components are in the form of classes written mostly in C. A foreground process written as a conventional application which can use the standard C libraries can communicate with the background real-time classes via a message passing mechanism. The platform thus enables the integration of high performance real-time processing into a conventional application framework.

Duryea, T. W.↗

Fast interrupt platform for extended DOS

Extended DOS offers the unique combination of a simple operating system which allows direct access to the interrupt tables, 32 bit protected mode access to 4096 MByte address space, and the use of industry standard C compilers. The drawback is that fast interrupt handling requires both 32 bit and 16 bit versions of each real-time process interrupt handler to avoid mode switches on the interrupts. A set of tools has been developed which automates the process of transforming the output of a standard 32 bit C compiler to 16 bit interrupt code which directly handles the real mode interrupts. The entire process compiles one set of source code via a make file, which boosts productivity by making the management of the compile-link cycle very simple. The software components are in the form of classes written mostly in C. A foreground process written as a conventional application which can use the standard C libraries can communicate with the background real-time classes via a message passing mechanism. The platform thus enables the integration of high performance real-time processing into a conventional application framework.

Duryea, T. W.↗

Performance Assessment of OVERFLOW on Distributed Computing Environment

The aerodynamic computer code, OVERFLOW, with a multi-zone overset grid feature, has been parallelized to enhance its performance on distributed and shared memory paradigms. Practical application benchmarks have been set to assess the efficiency of code's parallelism on high-performance architectures. The code's performance has also been experimented with in the context of the distributed computing paradigm on distant computer resources using the Information Power Grid (IPG) toolkit, Globus. Two parallel versions of the code, namely OVERFLOW-MPI and -MLP, have developed around the natural coarse grained parallelism inherent in a multi-zonal domain decomposition paradigm. The algorithm invokes a strategy that forms a number of groups, each consisting of a zone, a cluster of zones and/or a partition of a large zone. Each group can be thought of as a process with one or multithreads assigned to it and that all groups run in parallel. The -MPI version of the code uses explicit message-passing based on the standard MPI library for sending and receiving interzonal boundary data across processors. The -MLP version employs no message-passing paradigm; the boundary data is transferred through the shared memory. The -MPI code is suited for both distributed and shared memory architectures, while the -MLP code can only be used on shared memory platforms. The IPG applications are implemented by the -MPI code using the Globus toolkit. While a computational task is distributed across multiple computer resources, the parallelism can be explored on each resource alone. Performance studies are achieved with some practical aerodynamic problems with complex geometries, consisting of 2.5 up to 33 million grid points and a large number of zonal blocks. The computations were executed primarily on SGI Origin 2000 multiprocessors and on the Cray T3E. OVERFLOW's IPG applications are carried out on NASA homogeneous metacomputing machines located at three sites, Ames, Langley and Glenn. Plans for the future will exploit the distributed parallel computing capability on various homogeneous and heterogeneous resources and large scale benchmarks. Alternative IPG toolkits will be used along with sophisticated zonal grouping strategies to minimize the communication time across the computer resources.

Djomehri, M. Jahed↗

Design of a Model Execution Framework: Repetitive Object-Oriented Simulation Environment (ROSE)

The ROSE framework was designed to facilitate complex system analyses. It completely divorces the model execution process from the model itself. By doing so ROSE frees the modeler to develop a library of standard modeling processes such as Design of Experiments, optimizers, parameter studies, and sensitivity studies which can then be applied to any of their available models. The ROSE framework accomplishes this by means of a well defined API and object structure. Both the API and object structure are presented here with enough detail to implement ROSE in any object-oriented language or modeling tool.

Gray, Justin S.↗

Biomaterials Out of Thin Air: in Situ, On-Demand Printing of Advanced Biocomposites

Upmass is the single most significant limitation of our current space mission capability. Although biomaterials and biocomposites have mass, strength, flexibility, and self-healing properties that could significantly reduce upmass, their use is limited by the following drawbacks: Expensive, specific production. Many biomaterials can only be produced as part of significant support ecosystem; Inaccessible functional customization. The grain of wood, the porosity of bone, and so on are an integral part of the materials' desired mechanical properties, but are not deterministic when the material is naturally grown; Limited compositions. Most biomaterials (unlike metal, plastic, etc.) cannot be easily combined or modified to produce new materials. This project builds on recent advances in: Synthetic biology. Libraries of standardized genetic parts which can be used for controlled cellular material production, delivery, and binding; 3D printing. Commercial off-the-shelf components which can be used to make of a pico- to nanoliter cell deposition system; Tissue engineering. Proven cell-compatible support hydrogels and scaffolds can be modified to bind the deposited biomaterials of interest. Objectives: Feasibility and benefit analysis. Two mission contexts span the concept's scope (see below); Proof-of-concept demonstration. A simple grid of two proteins, fluorescent for easy detection, to validate the core technology concept; Proposed implementations for follow-on work. Avenues for future work on each core component (host cell, production control, material delivery, material binding, etc.); Complementary studies exploration. A survey of other emerging areas (in situ resource utilization, protein engineering, etc.) with the potential to multiply our technology's impact. Potential Impacts: This application could dramatically expand manufacturing capabilities on Earth and in space: In situ resource utilization. A far greater range of materials and products will be available from the limited palette offered by in situ resource extraction techniques; Reduced equipment and material upmass for off-Earth habitats. Ready- to-use highly specialized construction materials (radiation hardened, compressive/tensile, light or dense) from an extremely low starting mass; Structured biomaterial production. New ready-to-use macro, micro, and molecular manufacturing techniques for traditional biomaterials such as wood, bone and shell; New and novel biocomposite creation. The ability to create completely novel material composites from any base material that cells can be engineered to produce. Suggested Mission Contexts: ISS part manufacturing. A 'minimal working example' making a finished biomaterial part aboard the International Space Station; A long-term Mars habitat. 'Cradle-to-grave' use at a hypothetical Mars habitat, covering everything from tools to construction materials. Alternate Abstract: Imagine being able to print anything from tools and composite building materials to food and human tissues. Imagine being on Mars with the ability to replace any broken part, whether it's a part of your spacesuit, your habitat, or your own body. We propose a technique that would allow just that. By printing 3D arrays of cells engineered to secrete the necessary materials, the abundant in situ resources of atmosphere and regolith become organic, inorganic, or organic-inorganic composite materials. Such materials include novel, biologically derived materials not previously possible to fabricate.

habitats↗

Biomaterials Out of Thin Air: in Situ, On-demand Printing of Advanced Biocomposites

Upmass is the single most significant limitation of our current space mission capability. Although biomaterials and biocomposites have mass, strength, flexibility, and self-healing properties that could significantly reduce upmass, their use is limited by the following drawbacks: Expensive, specific production. Many biomaterials can only be produced as part of significant support ecosystem; Inaccessible functional customization. The grain of wood, the porosity of bone, and so on are an integral part of the materials' desired mechanical properties, but are not deterministic when the material is naturally grown; Limited compositions. Most biomaterials (unlike metal, plastic, etc.) cannot be easily combined or modified to produce new materials. This project builds on recent advances in: Synthetic biology. Libraries of standardized genetic parts which can be used for controlled cellular material production, delivery, and binding; 3D printing. Commercial off-the-shelf components which can be used to make of a pico- to nanoliter cell deposition system; Tissue engineering. Proven cell-compatible support hydrogels and scaffolds can be modified to bind the deposited biomaterials of interest. Objectives: Feasibility and benefit analysis. Two mission contexts span the concept's scope (see below); Proof-of-concept demonstration. A simple grid of two proteins, fluorescent for easy detection, to validate the core technology concept; Proposed implementations for follow-on work. Avenues for future work on each core component (host cell, production control, material delivery, material binding, etc.); Complementary studies exploration. A survey of other emerging areas (in situ resource utilization, protein engineering, etc.) with the potential to multiply our technology's impact. Potential Impacts: This application could dramatically expand manufacturing capabilities on Earth and in space: In situ resource utilization. A far greater range of materials and products will be available from the limited palette offered by in situ resource extraction techniques; Reduced equipment and material upmass for off-Earth habitats. Ready- to-use highly specialized construction materials (radiation hardened, compressive/tensile, light or dense) from an extremely low starting mass; Structured biomaterial production. New ready-to-use macro, micro, and molecular manufacturing techniques for traditional biomaterials such as wood, bone and shell; New and novel biocomposite creation. The ability to create completely novel material composites from any base material that cells can be engineered to produce. Suggested Mission Contexts: ISS part manufacturing. A 'minimal working example' making a finished biomaterial part aboard the International Space Station; A long-term Mars habitat. 'Cradle-to-grave' use at a hypothetical Mars habitat, covering everything from tools to construction materials. Alternate Abstract: Imagine being able to print anything from tools and composite building materials to food and human tissues. Imagine being on Mars with the ability to replace any broken part, whether it's a part of your spacesuit, your habitat, or your own body. We propose a technique that would allow just that. By printing 3D arrays of cells engineered to secrete the necessary materials, the abundant in situ resources of atmosphere and regolith become organic, inorganic, or organic-inorganic composite materials. Such materials include novel, biologically derived materials not previously possible to fabricate.

habitats↗

Aero-Engines AI - A Machine-Learning App for Aircraft Engine Concepts Assessment

Effective deployment of machine-learning (ML) models could drive a high level of efficiency in aircraft engine conceptual design. Aero-Engines AI is a user-friendly app that has been created to deploy trained machine-learning (ML) models to assess aircraft engine concepts. It was created using tkinter, a GUI (graphical user interface) module that is built into the standard Python library. Employing tkinter greatly facilitates the sharing of ML application as an executable file which can be run on Windows machines (without the need to have Python or any library installed). The app gets user input for a turbofan design, preprocesses the input data, and deploys trained ML models to predict turbofan thrust specific fuel consumption (TSFC), engine weight, core size, and turbomachinery stage-counts. The ML predictive models were built by employing supervised deep-learning and K-nearest neighbor regression algorithms to study patterns in an existing open-source database of production and research turbofan engines. They were trained, cross-validated, and tested in Keras, an open-source neural networks API (application programming interface) written in Python, with TensorFlow (Google open-source artificial intelligence library) serving as the backend engine. The smooth deployment of these ML models using the app shows that Aero-Engines AI is an easy-touse and a time-saving tool for aircraft engine design-space exploration during the conceptual design stage. Current version of the app focuses on the performance prediction of conventional turbofans. However, the scope of the app can easily be expanded to include other engine types (such as turboshaft and hybrid-electric systems) after their ML models are developed. Overall, the use of a machine-learning app for aircraft engine concept assessment represents a promising area of development in aircraft engine conceptual design.

machine learning↗

Aero-Engines AI - A Machine-Learning App for Aircraft Engine Concepts Assessment

Effective deployment of trained machine-learning models could drive a high level of efficiency in aircraft engine conceptual design. Aero-Engines AI is a Windows app that has been created to deploy trained machine-learning models to assess aircraft engine concepts. It was created using tkinter, a GUI (graphical user interface) module that is built into the standard Python library. Employing tkinter greatly facilitates the sharing of machine-learning application as an executable file which can be run on Windows machines (without the need to have Python or any library installed). Current version of the app focuses on the performance prediction of conventional turbofans. The app gets user input for a turbofan design, preprocesses the input data, and deploys trained machine-learning models to predict turbofan thrust specific fuel consumption (TSFC), engine weight, core size, and turbomachinery stage-counts. The machine-learning predictive models were built by employing supervised deep-learning algorithm to study patterns in an existing open-source database of production and research turbofan engines. They were trained, cross-validated, and tested in Keras, an open-source neural networks API (application programming interface) written in Python, with TensorFlow (Google open-source artificial intelligence library) serving as the backend engine. The smooth deployment of these machine-learning models using the app shows that Aero-Engines AI is an easy-to-use and a time-saving tool for aircraft engine design-space exploration during the conceptual design stage.

machine learning↗

Aero-Engines AI - A Machine-Learning App for Aircraft Engine Concepts Assessment

Effective deployment of machine-learning (ML) models could drive a high level of efficiency in aircraft engine conceptual design. Aero-Engines AI is a user-friendly app that has been created to deploy trained machine-learning (ML) models to assess aircraft engine concepts. It was created using tkinter, a GUI (graphical user interface) module that is built into the standard Python library. Employing tkinter greatly facilitates the sharing of ML application as an executable file which can be run on Windows machines (without the need to have Python or any library installed). The app gets user input for a turbofan design, preprocesses the input data, and deploys trained ML models to predict turbofan thrust specific fuel consumption (TSFC), engine weight, core size, and turbomachinery stage-counts. The ML predictive models were built by employing supervised deep-learning and K-nearest neighbor regression algorithms to study patterns in an existing open-source database of production and research turbofan engines. They were trained, cross-validated, and tested in Keras, an open-source neural networks API (application programming interface) written in Python, with TensorFlow (Google open-source artificial intelligence library) serving as the backend engine. The smooth deployment of these ML models using the app shows that Aero-Engines AI is an easy-touse and a time-saving tool for aircraft engine design-space exploration during the conceptual design stage. Current version of the app focuses on the performance prediction of conventional turbofans. However, the scope of the app can easily be easily expanded to include other engine types (such as turboshaft and hybrid-electric systems) after their ML models are developed. Overall, the use of a machine-learning app for aircraft engine concept assessment represents a promising area of development in aircraft engine conceptual design.

machine learning↗