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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2005

International Space Station Electric Power System Performance Code-SPACE

The System Power Analysis for Capability Evaluation (SPACE) software analyzes and predicts the minute-by-minute state of the International Space Station (ISS) electrical power system (EPS) for upcoming missions as well as EPS power generation capacity as a function of ISS configuration and orbital conditions. In order to complete the Certification of Flight Readiness (CoFR) process in which the mission is certified for flight each ISS System must thoroughly assess every proposed mission to verify that the system will support the planned mission operations; SPACE is the sole tool used to conduct these assessments for the power system capability. SPACE is an integrated power system model that incorporates a variety of modules tied together with integration routines and graphical output. The modules include orbit mechanics, solar array pointing/shadowing/thermal and electrical, battery performance, and power management and distribution performance. These modules are tightly integrated within a flexible architecture featuring data-file-driven configurations, source- or load-driven operation, and event scripting. SPACE also predicts the amount of power available for a given system configuration, spacecraft orientation, solar-array-pointing conditions, orbit, and the like. In the source-driven mode, the model must assure that energy balance is achieved, meaning that energy removed from the batteries must be restored (or balanced) each and every orbit. This entails an optimization scheme to ensure that energy balance is maintained without violating any other constraints.

Hojnicki, Jeffrey↗
NASA NTRSDate not supplied

Modeling Spacecraft Power Systems Using the SPACE Code

The NASA Glenn Research Center’s Power Architecture and Analysis Branch performs spacecraft electrical power system (EPS) performance analysis using the System Power Analysis for Capability Evaluation (SPACE) model. Accurately predicting EPS performance requires a wide range of inputs, including the spacecraft’s position, attitude, solar array temperature, load demand, and data on the EPS itself. By operating as a combined analysis tool with integrated orbit mechanics, attitude, shadowing, thermal, solar array, battery, and electrical component models, SPACE provides flexibility for the analyst to examine various scenarios without a time-consuming iterative process involving separate analysis tools and groups. SPACE also achieves short run times by tailoring the complexity of the included models, providing enough fidelity to ensure accurate EPS performance predictions without being bogged down by unnecessary detail. These advantages that SPACE has over similar power system models has contributed to its successful use on a variety of human spaceflight programs for over three decades, and makes it applicable across the development cycle from early conceptual design up through on-orbit operations.

Electrical Power System↗
NASA NTRS1992

Space System Architecture Code

Space System Architecture Code (SSAC) program performs sensitivity studies on operating parameters of space missions. SSAC examines effects of variations in sizes of crews of piloted missions, chemical vs. nuclear electric propulsion, and specific impulse. Written in FORTRAN 77.

Jan, Darrell L.↗
NASA NTRS2018

Development and Use of the SPACE Computer Code for Analyzing the Space Station Electrical Power System

This special publication tells the story of the dedicated efforts of very talented individuals to create a preeminent space electrical power system modeling and simulation tool called SPACE, short for System Power Analysis for Capability Evaluation. This computer model has evolved for 30 years, withstanding the test of time and obsolescence, and garnering international recognition for its ability to simulate complex space electrical power systems. The analytical results from this model have saved millions of dollars in hardware redesign, testing, and verification for NASA's International Space Station (ISS) and its European and Russian partners. SPACE has played a pivotal role in the station's design and development and continues to support its ongoing operation. It has also extended its reach beyond the ISS to other key NASA programs, where it guides the design and planned operation of NASA's Multi-Purpose Crew Vehicle Orion and simulates electric power system operation in a dusty atmosphere on Mars' surface. The SPACE lineage was created by a core civil servant staff, supplemented by a cadre of interns and other temporary helpers. They created a tightly integrated tool that includes all phenomena that impact a solar array and battery space power system performance. SPACE is self-contained, requiring no other software modules and associated license fees. SPACE "rings true" in that is has been extensively validated with ISS on-orbit telemetry data. This report is being released as the generation of engineers who created it are nearing retirement, passing the baton to a new generation. This next generation will carry the code into the future, no doubt further evolving it to be able to assure mission planners that newly conceived systems will successfully power NASA's next endeavors. As a previous SPACE code developer and analyst, I have worked alongside many of the people mentioned in this report. The engineers who created the code, along with those just now learning it, are among the best and brightest at NASA. It is an honor to write this foreword as the present Branch Chief under which the legacy of SPACE continues to thrive.

Electrical Power System↗
NASA NTRS2018

The SPACE Computer Code for Analyzing the International Space Station Electrical Power System: Past, Present, and Future

The System Power Analysis for Capability Evaluation (SPACE) computer code was initially developed by NASA in 1988 to assess the Space Station Freedom electric power system and later adapted to support contractor electrical power system capability analyses for the International Space Station (ISS). Over time, the code has supported many efforts such as ISS redesign activities in the early 1990s, assessment of time-phased loads against power system operating limits for future ISS assembly flights (including Certification of Flight Readiness reviews by the ISS program office), and determining the optimum solar array gimbal positions while respecting keep-out zones which minimize both solar array contamination and structural loads. The code has been validated by comparisons with ISS on-orbit data in multiple validation episodes. Recent updates to the code include the incorporation of a Lithium-Ion battery model in addition to the Nickel Hydrogen battery model and modifications to the solar array degradation model to better match on-orbit test results. SPACE has also been extended beyond the ISS to include modeling of the Orion Multi-Purpose Crew Vehicle electrical power system (SPACE-MPCV) and Mars Surface Electrical Power Systems (MSEPS). Portions of SPACE were integrated with a trajectory code to form a Solar Electric Propulsion Simulation (SEPSim), which can be used for analyzing solar electric propulsion missions. In addition, SPACE methods and subroutines have been adapted to a multitude of other projects. This paper summarizes the initial code development and subsequent code utilization in the context of the overall ISS program development and on-orbit operations. Recent updates and results from the code are discussed, including preliminary analyses for the Orion power system.

Electrical Power System↗
DOE OSTI2020

Code to map Xray reflectivity data from real space to reciprocal space

Code to map X-ray reflectivity data from real space to reciprocal space. The code is written as a Jupyter notebook. Example data are included as a separate file (example_data.csv). These data were collected on a Panalytical XRD system. As a first step, run all cells in the notebook. Opportunities are identified for users to make their own choices for choosing the boundaries of the region of interest to estimate background. A simple algorithm is used to estimate background from the outer regions of the data collection region, interpolating the result inside the region of interest. The background is removed and then the data mapped to Qx-Qz (reciprocal space) coordinates. The results are written as NumPy binary and Matlab formatted files.

Fitzsimmons, Michael [Oak Ridge National Lab. (ORN↗
NASA NTRS1969

Block coding for space communications.

Block coded telemetry systems design for phase coherent space communication employing double conversion superheterodyne phase locked receivers

Lindsey, W. C.↗
NASA NTRS1992

Coded aperture devices for viewing extended objects from space

Coded aperture sensors for photons or energetic neutral atoms (ENAs), which incorporate FOV limiters and subdivide the object field into a number of elements which is smaller than the number of detector pixels, are described. A least squares fit to the data is made in reconstructing the object field. To evaluate the optics and reconstruction algorithms, two 'breadboard' sensors have been constructed, one based on a film camera and the other upon a UV-light sensitive microchannel plate detector system. Results obtained thus far show that the concept is viable, and no special difficulties should be encountered in adapting the detector geometries to neutral particle imaging systems. Charged particle deflection plates could be incorporated into the region between the FOV limiter and the aperture, or installed ahead of the limiter.

Curtis, C. C.↗
NASA NTRS1993

Transform coding for space applications

Data compression coding requirements for aerospace applications differ somewhat from the compression requirements for entertainment systems. On the one hand, entertainment applications are bit rate driven with the goal of getting the best quality possible with a given bandwidth. Science applications are quality driven with the goal of getting the lowest bit rate for a given level of reconstruction quality. In the past, the required quality level has been nothing less than perfect allowing only the use of lossless compression methods (if that). With the advent of better, faster, cheaper missions, an opportunity has arisen for lossy data compression methods to find a use in science applications as requirements for perfect quality reconstruction runs into cost constraints. This paper presents a review of the data compression problem from the space application perspective. Transform coding techniques are described and some simple, integer transforms are presented. The application of these transforms to space-based data compression problems is discussed. Integer transforms have an advantage over conventional transforms in computational complexity. Space applications are different from broadcast or entertainment in that it is desirable to have a simple encoder (in space) and tolerate a more complicated decoder (on the ground) rather than vice versa. Energy compaction with new transforms are compared with the Walsh-Hadamard (WHT), Discrete Cosine (DCT), and Integer Cosine (ICT) transforms.

Glover, Daniel↗
NASA NTRS2019

Size and Structure of the Sequence Space of Repeat Proteins

The coding space of protein sequences is shaped by evolutionary constraints set by requirements of function and stability. We show that the coding space of a given protein family— the total number of sequences in that family—can be estimated using models of maximum entropy trained on multiple sequence alignments of naturally occurring amino acid sequences. We analyzed and calculated the size of three abundant repeat proteins families, whose members are large proteins made of many repetitions of conserved portions of *30 amino acids. While amino acid conservation at each position of the alignment explains most of the reduction of diversity relative to completely random sequences, we found that correlations between amino acid usage at different positions significantly impact that diversity. We quantified the impact of different types of correlations, functional and evolutionary, on sequence diversity. Analysis of the detailed structure of the coding space of the families revealed a rugged landscape, with many local energy minima of varying sizes with a hierarchical structure, reminiscent of frustrated energy landscapes of spin glass in physics. This clustered structure indicates a multiplicity of subtypes within each family and suggests new strategies for protein design.

Jacopo Marchi↗
NASA NTRS2002

Advances in space radiation shielding codes

Early space radiation shield code development relied on Monte Carlo methods and made important contributions to the space program. Monte Carlo methods have resorted to restricted one-dimensional problems leading to imperfect representation of appropriate boundary conditions. Even so, intensive computational requirements resulted and shield evaluation was made near the end of the design process. Resolving shielding issues usually had a negative impact on the design. Improved spacecraft shield design requires early entry of radiation constraints into the design process to maximize performance and minimize costs. As a result, we have been investigating high-speed computational procedures to allow shield analysis from the preliminary concept to the final design. For the last few decades, we have pursued deterministic solutions of the Boltzmann equation allowing field mapping within the International Space Station (ISS) in tens of minutes using standard Finite Element Method (FEM) geometry common to engineering design methods. A single ray trace in such geometry requires 14 milliseconds and limits application of Monte Carlo methods to such engineering models. A potential means of improving the Monte Carlo efficiency in coupling to spacecraft geometry is given.

manned↗
NASA NTRS1995

Space Debris Surfaces (Computer Code): Probability of No Penetration Versus Impact Velocity and Obliquity

A unique collection of computer codes, Space Debris Surfaces (SD_SURF), have been developed to assist in the design and analysis of space debris protection systems. SD_SURF calculates and summarizes a vehicle's vulnerability to space debris as a function of impact velocity and obliquity. An SD_SURF analysis will show which velocities and obliquities are the most probable to cause a penetration. This determination can help the analyst select a shield design that is best suited to the predominant penetration mechanism. The analysis also suggests the most suitable parameters for development or verification testing. The SD_SURF programs offer the option of either FORTRAN programs or Microsoft-EXCEL spreadsheets and macros. The FORTRAN programs work with BUMPERII. The EXCEL spreadsheets and macros can be used independently or with selected output from the SD_SURF FORTRAN programs. Examples will be presented of the interaction between space vehicle geometry, the space debris environment, and the penetration and critical damage ballistic limit surfaces of the shield under consideration.

Elfer, N.↗
NASA NTRS1986

Manual for obscuration code with space station applications

The Obscuration Code, referred to as SHADOW, is a user-oriented computer code to determine the case shadow of an antenna in a complex environment onto the far zone sphere. The surrounding structure can be composed of multiple composite cone frustums and multiply sided flat plates. These structural pieces are ideal for modeling space station configurations. The means of describing the geometry input is compatible with the NEC-BASIC Scattering Code. In addition, an interactive mode of operation has been provided for DEC VAX computers. The first part of this document is a user's manual designed to give a description of the method used to obtain the shadow map, to provide an overall view of the operation of the computer code, to instruct a user in how to model structures, and to give examples of inputs and outputs. The second part is a code manual that details how to set up the interactive and non-interactive modes of the code and provides a listing and brief description of each of the subroutines.

Marhefka, R. J.↗