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We present updates to the conventional methodology of triple modular redundancy (TMR) insertion as it pertains to clock domain crossings (CDCs). Three types of TMR schemes and their suggested corresponding CDC revisions are discussed.
This paper presents a methodology for analytically comparing approaches to modular assembly of large space platforms. the methodology combines a physical model of the modules, a life-cycle cost model, and a risk model to capture influential trade-offs.
This paper presents a methodology for analytically comparing approaches to modular assembly of large space platforms.
A modular methodology has been developed to model both NASA Space Station onboard resupply/return requirements and Space Shuttle delivery/return capabilities. This approach divides nonpayload Space Station logistics into seven independent categories, each of which is a function of several rates multiplied by user-definable onboard usage scenarios and Shuttle resupply profiles. The categories are summed to arrive at an overall resupply or return requirement. Unused Shuttle resupply and return capacities are also evaluated. The method allows an engineer to evaluate the transportation requirements for a candidate Space Station operational scenario.
This invention provides a new hierarchical approach for supervised neural learning of time dependent trajectories. The modular hierarchical methodology leads to architectures which are more structured than fully interconnected networks. The networks utilize a general feedforward flow of information and sparse recurrent connections to achieve dynamic effects. The advantages include the sparsity of units and connections, the modular organization. A further advantage is that the learning is much more circumscribed learning than in fully interconnected systems. The present invention is embodied by a neural network including a plurality of neural modules each having a pre-established performance capability wherein each neural module has an output outputting present results of the performance capability and an input for changing the present results of the performance capabilitiy. For pattern recognition applications, the performance capability may be an oscillation capability producing a repeating wave pattern as the present results. In the preferred embodiment, each of the plurality of neural modules includes a pre-established capability portion and a performance adjustment portion connected to control the pre-established capability portion.
We present a test methodology for estimating system error rates of Field Programmable Gate Arrays (FPGAs) mitigated with Triple Modular Redundancy (TMR). The test methodology is founded in a mathematical model, which is also presented. Accelerator data from 90 nm Xilins Military/Aerospace grade FPGA are shown to fit the model. Fault injection (FI) results are discussed and related to the test data. Design implementation and the corresponding impact of multiple bit upset (MBU) are also discussed.
CRISP-90 software-design-analyzer system, update of CRISP-80, is set of computer programs constituting software tool for design and documentation of other software and supporting top-down, hierarchical, modular, structured methodologies for design and programming. Written in Microsoft QuickBasic.
On July 15, 2022, the Hunga Tonga-Hunga Ha’apai (HTHH) submarine volcano erupted, propelling trace gasses and ash through the troposphere and up into the stratosphere. Previous studies manually tracked the aerosol and trace gas plumes over time across different positions in the southern hemisphere. Using imagery from NASA’s Earth Observing System, including MODIS aerosol products and OMI sulfur dioxide products, this research demonstrates how open-source machine learning (ML) models, like Meta’s Segment Anything Model (SAM), can perform automatic plume tracking following the Hunga Tonga eruption. This extensible methodology, and modular data processing and modeling pipeline, establishes a framework for systematically and rapidly studying natural disasters, including additional volcanic eruptions and large-scale wildfires. By combining advanced machine learning techniques, such as SAM’s zero-shot learning, with large volumes of NASA’s Earth Observation and remote sensing data, this work shows how AI and open science can accelerate research and generate actionable results, even for unprecedented events. The tools and technologies presented here can help translate earth science to action from NASA’s current and future Earth observing satellite missions, and assist researchers and stakeholders in understanding, mapping, and responding to natural disasters in a changing world.
On January 15, 2022, the Hunga Tonga-Hunga Ha’apai (hereafter, Hunga Tonga) submarine volcano had an explosive eruption that thrusted ash, gases, and water vapor through the troposphere into the stratosphere and mesosphere. Previous studies manually tracked the aerosol and trace gas plumes over time across different positions in the southern hemisphere. Using data retrieved from low earth orbiting satellite instruments (e.g., OMPS, OMI, and CALIPSO), this research demonstrates how open-source machine learning (ML) models, like Meta’s Segment Anything Model (SAM), with prompt engineering can perform automatic plume tracking following the Hunga Tonga eruption. This extensible methodology, and modular data processing and modeling pipeline using NASA Earthdata and Openscapes, establishes a framework for systematically and rapidly studying extreme events, including volcanic eruptions and large-scale wildfires. By combining advanced machine learning techniques, such as SAM’s zero-shot learning, with large volumes of remote sensing data, this work demonstrates how AI and open science can accelerate research and generate actionable results. The tools and technologies presented here can help translate earth science to action from NASA’s current and future Earth observing satellite missions (e.g., the Atmosphere Observing System (AOS)), and assist researchers and stakeholders in understanding, mapping, and responding to natural disasters and extreme events in a changing world.
A robust space infrastructure encompasses a broad range of mission needs along with an imperative to reduce costs of satellites meeting those needs. A critical commodity for science, commercial and civil satellites is power at an affordable cost. The POWOW (POwer WithOut Wires) spacecraft concept was created to provide, at one end of the scale, multi-megawatts of power yet also be composed of modules that can meet spacecraft needs in the kilowatt range. With support from the NASA-sponsored Space Solar Power Exploratory Research and Technology Program, the POWOW spacecraft concept was designed to meet Mars mission needs - while at the same time having elements applicable to a range of other missions. At Mars, the vehicle would reside in an aerosynchronous orbit and beam power to a variety of locations on the surface. It is the purpose of this paper to present the latest concept design results. The Space Power Institute along with four companies: Able Engineering, Inc., Entech, Inc., Primex Aerospace Co., and TECSTAR have produced a modular, power-rich electrically propelled spacecraft design that meets these requirements. In addition, it also meets a range of civil and commercial needs. The spacecraft design is based on multijunction Ill-V solar cells, the new Stretched Lens Aurora (SLA) module, a lightweight array design based on a multiplicity of 8 kW end-of-life subarrays and electric thrusters. The solar cells have excellent radiation resistance and efficiencies above 30%. The SLA has a concentration ratio up to 15x while maintaining an operating temperature of 80 C. The design of the 8 kW array building block will be presented and its applicability to commercial and government missions will be discussed. Electric propulsion options include Hall, MPD and ion thrusters of various power levels and trade studies have been conducted to define the most advantageous options. The present baseline spacecraft design providing 900 kW using technologies expected to be available in 2003 will be described. Areal power densities of nearly 400 W/meters squared at 80 C operating temperatures and wing level specific powers of over 400 W/kg are projected. Details of trip times and payloads to Mars will be presented as well as trade studies of various electric propulsion options. Trip times compare favorably with chemical propulsion options. Because the design is modular, learning curve methodology can be applied to determine expected cost reductions. These results will also be included. This paper has not been presented at a previous meeting.
Electric propulsion has emerged as a cost-effective solution to a wide range of satellite applications. Deep Space 1 successfully demonstrated electric propulsion as the primary propulsion source for a satellite. The POWOW concept is a solar-electric propelled spacecraft capable of significant cargo and short trip times for traveling to Mars. There it would enter areosynchronous orbit (Mars GEO equivalent) and beam power to surface installations via lasers. The concept has been developed with industrial partner expertise in high efficiency solar cells, advanced concentrator modules, innovative arrays, and high power electric propulsion systems. The present baseline spacecraft design providing 898 kW using technologies expected to be available in 2003 will be described. Areal power densities approaching 350 W/sq m at 80 C operating temperatures and wing level specific powers of over 350 W/kg are projected. Details of trip times and payloads to Mars are presented. Electric propulsion options include Hall, MPD, and ion thrusters of various power levels and trade studies have been conducted to define the most advantageous options. Because the design is modular, learning curve methodology has been applied to determine expected cost reductions and is included.
To better understand the role of tensegrity structures in biological systems and their application to robotics, the Dynamic Tensegrity Robotics Lab at NASA Ames Research Center has developed and validated two different software environments for the analysis, simulation, and design of tensegrity robots. These tools, along with new control methodologies and the modular hardware components developed to validate them, are presented as a system for the design of actuated tensegrity structures. As evidenced from their appearance in many biological systems, tensegrity ("tensile-integrity") structures have unique physical properties which make them ideal for interaction with uncertain environments. Yet these characteristics, such as variable structural compliance, and global multi-path load distribution through the tension network, make design and control of bio-inspired tensegrity robots extremely challenging. This work presents the progress in using these two tools in tackling the design and control challenges. The results of this analysis includes multiple novel control approaches for mobility and terrain interaction of spherical tensegrity structures. The current hardware prototype of a six-bar tensegrity, code-named ReCTeR, is presented in the context of this validation.
Electric propulsion has emerged as a cost-effective solution to a wide range of satellite applications. Deep Space 1 demonstrated electric propulsion as a primary propulsion source for a spacecraft. The POwer WithOut Wires (POWOW) concept has been developed as a solar electric propelled spacecraft that would travel to Mars, for example, enter selenosynchronous orbit and then use lasers to beam power to surface installations. This concept has been developed with industrial expertise in high efficiency solar cells, advanced concentrator modules, innovative arrays, and high power electric propulsion systems. The paper will present the latest version of the spacecraft, the technologies involved, possible missions and trip times to Mars and laser beaming options. The POWOW spacecraft is a general purpose solar electric propulsion system that includes technologies that are directly applicable to commercial and government spacecraft with power levels ranging from 4 kW in Low Earth Orbits (LEO) to about 1 MW. The system is modular and expandable. Learning curve costing methodologies are used to demonstrate cost effectiveness of a modular system.
A study performed to continue development of computational techniques for the Space Shuttle Thermal Protection System is reported. The resulting computer code was used to perform some additional optimization studies on several TPS configurations. The program was developed in Fortran 4 for the CDC 6400, and it was converted to Fortran 5 to be used for the Univac 1108. The computational methodology is developed in modular fashion to facilitate changes and updating of the techniques and to allow overlaying the computer code to fit into approximately 131,000 octal words of core storage. The program logic involves subroutines which handle input and output of information between computer and user, thermodynamic stress, dynamic, and weight/estimate analyses of a variety of panel configurations. These include metallic, ablative, RSI (with and without an underlying phase change material), and a thermodynamic analysis only of carbon-carbon systems applied to the leading edge and flat cover panels. Two different thermodynamic analyses are used. The first is a two-dimensional, explicit precedure with variable time steps which is used to describe the behavior of metallic and carbon-carbon leading edges. The second is a one-dimensional implicity technique used to predict temperature in the charring ablator and the noncharring RSI. The latter analysis is performed simply by suppressing the chemical reactions and pyrolysis of the TPS material.
The component element method was used to develop a transient dynamic analysis computer program which is essentially based on modal synthesis combined with a central, finite difference, numerical integration scheme. The methodology leads to a modular or building-block technique that is amenable to computer programming. To verify the analytical method, turbine engine transient response analysis (TETRA), was applied to two blade-out test vehicles that had been previously instrumented and tested. Comparison of the time dependent test data with those predicted by TETRA led to recommendations for refinement or extension of the analytical method to improve its accuracy and overcome its shortcomings. The development of working equations, their discretization, numerical solution scheme, the modular concept of engine modelling, the program logical structure and some illustrated results are discussed. The blade-loss test vehicles (rig full engine), the type of measured data, and the engine structural model are described.
The avionics system software for human-rated launch vehicles requires an implementation approach that is robust to failures, especially the failure of sensors used to monitor vehicle conditions that might result in an abort determination. Sensor measurements provide the basis for operational decisions on human-rated launch vehicles. This data is often used to assess the health of system or subsystem components, to identify failures, and to take corrective action. An incorrect conclusion and/or response may result if the sensor itself provides faulty data, or if the data provided by the sensor has been corrupted. Operational decisions based on faulty sensor data have the potential to be catastrophic, resulting in loss of mission or loss of crew. To prevent these later situations from occurring, a Modular Architecture and Generalized Methodology for Sensor Data Qualification in Human-rated Launch Vehicles has been developed. Sensor Data Qualification (SDQ) is a set of algorithms that can be implemented in onboard flight software, and can be used to qualify data obtained from flight-critical sensors prior to the data being used by other flight software algorithms. Qualified data has been analyzed by SDQ and is determined to be a true representation of the sensed system state; that is, the sensor data is determined not to be corrupted by sensor faults or signal transmission faults. Sensor data can become corrupted by faults at any point in the signal path between the sensor and the flight computer. Qualifying the sensor data has the benefit of ensuring that erroneous data is identified and flagged before otherwise being used for operational decisions, thus increasing confidence in the response of the other flight software processes using the qualified data, and decreasing the probability of false alarms or missed detections.
CRISP80 software design analyzer system a set of programs that supports top-down, hierarchic, modular structured design, and programing methodologies. CRISP80 allows for expression of design as picture of program.
The main objective of this research is to develop a generic modeling methodology with a flexible and modular framework to aid in the design and performance evaluation of integrated manufacturing systems using a unified model. After a thorough examination of the available modeling methods, the Petri Net approach was adopted. The concurrent and asynchronous nature of manufacturing systems are easily captured by Petri Net models. Three basic modules were developed: machine, buffer, and Decision Making Unit. The machine and buffer modules are used for modeling transfer lines and production networks. The Decision Making Unit models the functions of a computer node in a complex Decision Making Unit Architecture. The underlying model is a Generalized Stochastic Petri Net (GSPN) that can be used for performance evaluation and structural analysis. GSPN's were chosen because they help manage the complexity of modeling large manufacturing systems. There is no need to enumerate all the possible states of the Markov Chain since they are automatically generated from the GSPN model.