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The prototype intermediate frequency video down converter of the Deep Space Network (BLK 1) Very Long Base Interferometry system, a hybrid of analog and digital circuits, was completed and tested. The initial results met all design specifications, establishing a milestone in new design technology for such devices. This device has uses in other similar applications and can form the basis for expanded design and applications.
This paper is a progress report on the utilization of AI technology for assisting users locating and understanding technical information in manuals used for planning and conducting wind tunnel test. The specific goal is to create an Intelligent Hypertext System (IHS) for wind tunnel testing which combines the computerized manual in the form of hypertext and an advisory system that stores experts' knowledge and experiences. A prototype IHS for conducting transonic wind tunnel testing has been constructed with limited knowledge base. The prototype is being evaluated by potential users.
The six studies which are addressed are entitled: Design Modularity and Commonality; Modification of Existing Hardware (COTS) vs. New Hardware Build Cost Analysis; Automation Cost vs. Crew Utilization; Hardware Miniaturization versus Cost; Space Station Freedom/Spacelab Modules Compatibility vs. Cost; and Prototype Utilization in the Development of Space Hardware. The product of these six studies was intended to provide a knowledge base and methodology that enables equipment produced for the Space Biology Initiative program to meet specific design and functional requirements in the most efficient and cost effective form consistent with overall mission integration parameters. Each study promulgates rules of thumb, formulas, and matrices that serves has a handbook for the use and guidance of designers and engineers in design, development, and procurement of Space Biology Initiative (SBI) hardware and software.
The six studies which are the subjects of this report are entitled: Design Modularity and Commonality; Modification of Existing Hardware (COTS) vs. New Hardware Build Cost Analysis; Automation Cost vs. Crew Utilization; Hardware Miniaturization versus Cost; Space Station Freedom/Spacelab Modules Compatibility vs. Cost; and Prototype Utilization in the Development of Space Hardware. The product of these six studies was intended to provide a knowledge base and methodology that enables equipment produced for the Space Biology Initiative program to meet specific design and functional requirements in the most efficient and cost effective form consistent with overall mission integration parameters. Each study promulgates rules of thumb, formulas, and matrices that serves as a handbook for the use and guidance of designers and engineers in design, development, and procurement of Space Biology Initiative (SBI) hardware and software.
This paper describes the development of mathematical theory and software to analyze specifications that are developed using decision tables. A decision table is a tabular format for specifying a complex set of rules that chooses one of a number of alternative actions. The report also describes a prototype tool, called TBell, that automates certain types of analysis.
We present a logical framework in which abstract interpretations can be naturally specified and then verified. Our approach is based on membership equational logic which extends equational logics by membership axioms, asserting that a term has a certain sort. We represent an abstract interpretation as a membership equational logic specification, usually as an overloaded order-sorted signature with membership axioms. It turns out that, for any term, its least sort over this specification corresponds to its most concrete abstract value. Maude implements membership equational logic and provides mechanisms to calculate the least sort of a term efficiently. We first show how Maude can be used to get prototyping of abstract interpretations "for free." Building on the meta-logic facilities of Maude, we further develop a tool that automatically checks and abstract interpretation against a set of user-defined properties. This can be used to select an appropriate abstract interpretation, to characterize the specified loss of information during abstraction, and to compare different abstractions with each other.
A monolithic microwave integrated circuit (MMIC) that includes a high-electron-mobility transistor (HEMT) has been developed as a prototype of improved frequency doublers for generating signals at frequencies greater than 100 GHz. Signal sources that operate in this frequency range are needed for a variety of applications, notably including general radiometry and, more specifically, radiometric remote sensing of the atmosphere. Heretofore, it has been common practice to use passive (diode-based) frequency multipliers to obtain frequencies greater than 100 GHz. Unfortunately, diode-based frequency multipliers are plagued by high DC power consumption and low conversion efficiency. Moreover, multiplier diodes are not easily integrated with such other multiplier-circuit components as amplifiers and oscillators. The goals of developing the present MMIC HEMT frequency doubler were (1) to utilize the HEMT as an amplifier to increase conversion efficiency (more precisely, to reduce conversion loss), thereby increasing the output power for a given DC power consumption or, equivalently, reducing the DC power consumption for a given output power; and (2) to provide for the integration of amplifier and oscillator components on the same chip. The MMIC frequency doubler (see Figure 1) contains an AlInAs/GaInAs/InP HEMT biased at pinch-off to make it function as a class-B amplifier (meaning that it conducts in half-cycle pulses). Grounded coplanar waveguides (GCPWs) are used as impedance-matching transmission lines. Air bridges are placed at discontinuities to suppress undesired slot electromagnetic modes. Another combination of GCPWs also serves both as a low-pass filter to suppress undesired oscillations at frequencies below 60 GHz and as a DC blocker. Large decoupling capacitors and epitaxial resistors are added in the drain and gate lines to suppress bias oscillations. At the output terminal, the fundamental frequency is suppressed by a quarter-wave open stub, which presents a short circuit at the fundamental frequency and an open circuit at the second harmonic. At an input power of 7 mW, the output power and conversion loss at an output frequency of 164 GHz were found to be 5 dBm (approximately equal to 3.2 mW) and 2 dB, respectively, with a 3-dB output-power bandwidth of 14 GHz. This is the best performance reported to date for an MMIC HEMT frequency doubler above 100 GHz.
Results from previous shell buckling studies are presented that illustrate some of the unique and powerful capabilities in the STAGS finite element analysis code that have made it an indispensable tool in structures research at NASA over the past few decades. In particular, prototypical results from the development and validation of high-fidelity buckling simulations are presented for several unstiffened thin-walled compression-loaded graphite-epoxy cylindrical shells along with a discussion on the specific methods and user-defined subroutines in STAGS that are used to carry out the high-fidelity simulations. These simulations accurately account for the effects of geometric shell-wall imperfections, shell-wall thickness variations, local shell-wall ply-gaps associated with the fabrication process, shell-end geometric imperfections, nonuniform applied end loads, and elastic boundary conditions. The analysis procedure uses a combination of nonlinear quasi-static and transient dynamic solution algorithms to predict the prebuckling and unstable collapse response characteristics of the cylinders. Finally, the use of high-fidelity models in the development of analysis-based shell-buckling knockdown (design) factors is demonstrated.
Using state-of-the-art artificial intelligence (AI)frameworks onboard spacecraft is challenging because common spacecraft processors cannot provide comparable performance to datacenters with server-grade CPUs and GPUs available for terrestrial applications and advanced deep-learning networks. This limitation makes small, lo w-p o we r AI microchip architectures, such as the Google Coral Edge Tensor Processing Unit (TPU), attractive for space missions where the application-specific design enables both high-performance and power-efficient computing for AI applications. To address these challenging considerations for space deployment, this research introduces the design and capabilities of a CubeSat-sized Edge TPU-based co-processor card, known as the SpaceCube Low-power Ed g e Artificial Intelligence Resilient Node (SC-LEARN). This design conforms to NASA’s CubeSat Card Specification (CS2) for integration into next-generation SmallSat and CubeSat systems. This paper describes the overarching architecture and design of the SC-LEARN, as well as, the supporting test card designed for rapid prototyping and evaluation. The SC-LEARN was developed with three operational modes: (1) a high-performance parallel-processing mode,(2)a fault-tolerant mode for onboard resilience, and (3) a power-saving mode with cold spares. Importantly, this research also elaborates on both training and quantization of Tensor Flow models for the SC-LEARN for use onboard with representative, open-source datasets. Lastly, we describe future research plans, including radiation-beam testing and flight demonstration.
Engineering is an interactive process that requires intelligent interaction at many levels. My thesis [1] advances an engineering discipline for high-level synthesis and architectural decomposition that integrates perspicuous representation, designer interaction, and mathematical rigor. Starfish, the software prototype for the design method, implements a table-centric transformation system for reorganizing control-dominated system expressions into high-level architectures. Based on the digital design derivation (DDD) system a designer-guided synthesis technique that applies correctness preserving transformations to synchronous data flow specifications expressed as co- recursive stream equations Starfish enhances user interaction and extends the reachable design space by incorporating four innovations: behavior tables, serialization tables, data refinement, and operator retiming. Behavior tables express systems of co-recursive stream equations as a table of guarded signal updates. Developers and users of the DDD system used manually constructed behavior tables to help them decide which transformations to apply and how to specify them. These design exercises produced several formally constructed hardware implementations: the FM9001 microprocessor, an SECD machine for evaluating LISP, and the SchemEngine, garbage collected machine for interpreting a byte-code representation of compiled Scheme programs. Bose and Tuna, two of DDD s developers, have subsequently commercialized the design derivation methodology at Derivation Systems, Inc. (DSI). DSI has formally derived and validated PCI bus interfaces and a Java byte-code processor; they further executed a contract to prototype SPIDER-NASA's ultra-reliable communications bus. To date, most derivations from DDD and DRS have targeted hardware due to its synchronous design paradigm. However, Starfish expressions are independent of the synchronization mechanism; there is no commitment to hardware or globally broadcast clocks. Though software back-ends for design derivation are limited to the DDD stream-interpreter, targeting synchronous or real-time software is not substantively different from targeting hardware.
This study was set up to assure that operation of the shuttle orbiter communications systems met the program requirements when subjected to electrical conditions similar to those which will be encountered during the operational mission. The test program intended to implement an integrated test bed, consisting of applicable orbiter, EVA, payload simulator, STDN, and AF/SCF, as well as the TDRSS equipment. The stated intention of Task 501 Program was to configure the test bed with prototype hardware for a system development test and production hardware for a system verification test. In case of TDRSS when the hardware was not available, simulators whose functional performance was certified to meet appropriate end item specification were used.
Experimental designs in life-size mock-up form for the wardroom facility for the Space Station Habitability Module are explored and developed. In Phase 1, three preliminary concepts for the wardroom configuration are fabricated and evaluated. In Phase 2, the results of Phase 1 are combined with a specific range of program design requirements to provide the design criteria for the fabrication of an innovative medium-fidelity mock-up of a wardrobe configuration. The study also focuses on the design and preliminary prototyping of selected equipment items including crew exercise compartments, a meal/meeting table and a portable workstation. Design criteria and requirements are discussed and documented. Preliminary and final mock-ups and equipment prototypes are described and illustrated.
High-quality, wide-aperture optical access is usually required for the advanced laser diagnostics that can now make a wide variety of non-intrusive measurements of combustion processes. Specially processed and mounted sapphire windows are proposed to provide this optical access to extreme environment. Through surface treatments and proper thermal stress design, single crystal sapphire can be a mechanically equivalent replacement for high strength steel. A prototype sapphire window and mounting system have been developed in a successful NASA SBIR Phase 1 project. A large and reliable increase in sapphire design strength (as much as 10x) has been achieved, and the initial specifications necessary for these gains have been defined. Failure testing of small windows has conclusively demonstrated the increased sapphire strength, indicating that a nearly flawless surface polish is the primary cause of strengthening, while an unusual mounting arrangement also significantly contributes to a larger effective strength. Phase 2 work will complete specification and demonstration of these windows, and will fabricate a set for use at NASA. The enhanced capabilities of these high performance sapphire windows will lead to many diagnostic capabilities not previously possible, as well as new applications for sapphire.
There are three issues to consider when building an embedded training system for a task domain involving the operation of complex equipment: (1) how skill is acquired in the task domain; (2) how the training system should be designed to assist in the acquisition of the skill, and more specifically, how an intelligent tutor could aid in learning; and (3) whether it is feasible to incorporate the resulting training system into the operational environment. This paper describes how these issues have been addressed in a prototype training system that was developed for operations in NASA's Deep Space Network (DSN). The first two issues were addressed by building an executable cognitive model of problem solving and skill acquisition of the task domain and then using the model to design an intelligent tutor. The cognitive model was developed in Soar for the DSN's Link Monitor and Control (LMC) system; it led to several insights about learning in the task domain that were used to design an intelligent tutor called REACT that implements a method called 'impasse-driven tutoring'. REACT is one component of the LMC training system, which also includes a communications link simulator and a graphical user interface. A pilot study of the LMC training system indicates that REACT shows promise as an effective way for helping operators to quickly acquire expert skills.
Lightweight high efficiency electric motors are needed across a wide range of space applications from - thrust vector actuator control for launch and flight applications to - general vehicle, base camp habitat and experiment control for various mechanisms to - robotics for various stationary and mobile space exploration missions. QM Power?s Parallel Path Magnetic Technology Motors have slowly proven themselves to be a leading motor technology in this area; winning a NASA Phase II for "Lightweight High Efficiency Electric Motors and Actuators for Low Temperature Mobility and Robotics Applications" a US Army Phase II SBIR for "Improved Robot Actuator Motors for Medical Applications", an NSF Phase II SBIR for "Novel Low-Cost Electric Motors for Variable Speed Applications" and a DOE SBIR Phase I for "High Efficiency Commercial Refrigeration Motors" Parallel Path Magnetic Technology obtains the benefits of using permanent magnets while minimizing the historical trade-offs/limitations found in conventional permanent magnet designs. The resulting devices are smaller, lower weight, lower cost and have higher efficiency than competitive permanent magnet and non-permanent magnet designs. QM Power?s motors have been extensively tested and successfully validated by multiple commercial and aerospace customers and partners as Boeing Research and Technology. Prototypes have been made between 0.1 and 10 HP. They are also in the process of scaling motors to over 100kW with their development partners. In this paper, Parallel Path Magnetic Technology Motors will be discussed; specifically addressing their higher efficiency, higher power density, lighter weight, smaller physical size, higher low end torque, wider power zone, cooler temperatures, and greater reliability with lower cost and significant environment benefit for the same peak output power compared to typically motors. A further discussion on the inherent redundancy of these motors for space applications will be provided.
We describe a framework for symbolically evaluating iterative C code using a deductive approach that automatically discovers and proves program properties. Although verification is not performed, the method can infer detailed program behavior. Software engineering work flows could be enhanced by this type of analysis. Floyd-Hoare verification principles are applied to synthesize loop invariants, using a library of iteration-specific deductive knowledge. When needed, theorem proving is interleaved with evaluation and performed on the fly. Evaluation results take the form of inferred expressions and type constraints for values of program variables. An implementation using PVS (Prototype Verification System) is presented along with results for sample C functions.
This document examines the challenges inherent in designing and regulating to support human-automation interaction for new technologies that will deployed into complex systems. A key question for new technologies, is how work will be accomplished by the human and machine agents. This question has traditionally been framed as how functions should be allocated between humans and machines. Such framing misses the coordination and synchronization that is needed for the different human and machine roles in the system to accomplish their goals. Coordination and synchronization demands are driven by the underlying human-automation architecture of the new technology, which are typically not specified explicitly by the designers. The human machine interface (HMI) which is intended to facilitate human-machine interaction and cooperation, however, typically is defined explicitly and therefore serves as a proxy for human-automation cooperation requirements with respect to technical standards for technologies. Unfortunately, mismatches between the HMI and the coordination and synchronization demands of the underlying human-automation architecture, can lead to system breakdowns. A methodology is needed that both designers and regulators can utilize to evaluate the expected performance of a new technology given potential human-automation architectures. Three experiments were conducted to inform the minimum HMI requirements a detect and avoid system for unmanned aircraft systems (UAS). The results of the experiments provided empirical input to specific minimum operational performance standards that UAS manufacturers will have to meet in order to operate UAS in the National Airspace System (NAS). These studies represent a success story for how to objectively and systematically evaluate prototype technologies as part of the process for developing regulatory requirements. They also provide an opportunity to reflect on the lessons learned from a recent research effort in order to improve the methodology for defining technology requirements for regulators in the future. The biggest shortcoming of the presented research program was the absence of the explicit definition, generation and analysis of potential human-automation architectures. Failure to execute this step in the research process resulted in less efficient evaluation of the candidate prototypes technologies in addition to the complete absence of different approaches to human-automation cooperation. For example, all of the prototype technologies that were evaluated in the research program assumed a human-automation architecture that relied on serial processing from the automation to the human. While this type of human-automation architecture is typical across many different technologies and in many different domains, it ignores different architectures where humans and automation work in parallel. Defining potential human-automation architectures a priori also allows regulators to develop scenarios that will stress the performance boundaries of the technology during the evaluation phase. The importance of adding this step of generating and evaluating candidate human-automation architectures prior to formal empirical evaluation is discussed.
There are three issues to consider when building an embedded training system for a task domain involving the operation of complex equipment: (1) how skill is acquired in the task domain; (2) how the training system should be designed to assist in the acquisition of the skill, and more specifically, how an intelligent tutor could aid in learning; and (3) whether it is feasible to incorporate the resulting training system into the operational environment. This paper describes how these issues have been addressed in a prototype training system that was developed for operations in NASA's Deep Space Network (DSN). The first two issues were addressed by building an executable cognitive model of problem solving and skill acquisition of the task domain and then using the model to design an intelligent tutor.