Rapid Process Design - A System Engineering Design Method
A rapid method has been developed for the design of computing system capabilities and/or human.
SEARCH · Engineering Papers
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
A rapid method has been developed for the design of computing system capabilities and/or human.
This report details our development fo a computer controlled spotlight with four actuated degrees-of-freedom for pan, tilt, linear movement and beam focusing. We review the mechanical structure, kinematic model, calibration data, and control algorithm.
The Maestro Science Activity Planner is a computer program that assists human users in planning operations of the Mars Explorer Rover (MER) mission and visualizing scientific data returned from the MER rovers. Relative to its predecessors, this program is more powerful and easier to use. This program is built on the Java Eclipse open-source platform around a Web-browser-based user-interface paradigm to provide an intuitive user interface to Mars rovers and landers. This program affords a combination of advanced display and simulation capabilities. For example, a map view of terrain can be generated from images acquired by the High Resolution Imaging Science Explorer instrument aboard the Mars Reconnaissance Orbiter spacecraft and overlaid with images from a navigation camera (more precisely, a stereoscopic pair of cameras) aboard a rover, and an interactive, annotated rover traverse path can be incorporated into the overlay. It is also possible to construct an overhead perspective mosaic image of terrain from navigation-camera images. This program can be adapted to similar use on other outer-space missions and is potentially adaptable to numerous terrestrial applications involving analysis of data, operations of robots, and planning of such operations for acquisition of scientific data.
Solving large (and sparse) system of simultaneous linear equations has been (and continues to be) a major challenging problem for many real-world engineering/science applications [1-2]. For many practical/large-scale problems, the sparse, Symmetrical and Positive Definite (SPD) system of linear equations can be conveniently represented in matrix notation as [A] {x} = {b} , where the square coefficient matrix [A] and the Right-Hand-Side (RHS) vector {b} are known. The unknown solution vector {x} can be efficiently solved by the following step-by-step procedures [1-2]: Reordering phase, Matrix Factorization phase, Forward solution phase, and Backward solution phase. In this research work, a Game-Based Learning (GBL) approach has been developed to help engineering students to understand crucial details about matrix reordering and factorization phases. A "chess-like" game has been developed and can be played by either a single player, or two players. Through this "chess-like" open-ended game, the players/learners will not only understand the key concepts involved in reordering algorithms (based on existing algorithms), but also have the opportunities to "discover new algorithms" which are better than existing algorithms. Implementing the proposed "chess-like" game for matrix reordering and factorization phases can be enhanced by FLASH [3] computer environments, where computer simulation with animated human voice, sound effects, visual/graphical/colorful displays of matrix tables, score (or monetary) awards for the best game players, etc. can all be exploited. Preliminary demonstrations of the developed GBL approach can be viewed by anyone who has access to the internet web-site [4]!
Mercury (http://mercury.ornl.gov) is a set of tools for federated harvesting, searching, and retrieving metadata, particularly spatiotemporal metadata. Version 3.0 of the Mercury toolset provides orders of magnitude improvements in search speed, support for additional metadata formats, integration with Google Maps for spatial queries, facetted type search, support for RSS (Really Simple Syndication) delivery of search results, and enhanced customization to meet the needs of the multiple projects that use Mercury. It provides a single portal to very quickly search for data and information contained in disparate data management systems, each of which may use different metadata formats. Mercury harvests metadata and key data from contributing project servers distributed around the world and builds a centralized index. The search interfaces then allow the users to perform a variety of fielded, spatial, and temporal searches across these metadata sources. This centralized repository of metadata with distributed data sources provides extremely fast search results to the user, while allowing data providers to advertise the availability of their data and maintain complete control and ownership of that data. Mercury periodically (typically daily) harvests metadata sources through a collection of interfaces and re-indexes these metadata to provide extremely rapid search capabilities, even over collections with tens of millions of metadata records. A number of both graphical and application interfaces have been constructed within Mercury, to enable both human users and other computer programs to perform queries. Mercury was also designed to support multiple different projects, so that the particular fields that can be queried and used with search filters are easy to configure for each different project.
Long-duration space flight carries the risk of developing Visual Impairment and Intracranial Pressure (VIIP) syndrome, a spectrum of ophthalmic changes including posterior globe flattening, choroidal folds, distension of the optic nerve sheath (ONS), optic nerve kinking and potentially permanent degradation of visual function. The slow onset of VIIP, its chronic nature, and certain clinical features strongly suggest that biomechanical factors acting on the ONS play a role in VIIP. Here we measure several relevant ONS properties needed to model VIIP biomechanics. The ONS (meninges) of fresh porcine eyes (n7) was reflected, the nerve proper was truncated near the sclera, and the meninges were repositioned to create a hollow cylinder of meningeal connective tissue attached to the posterior sclera. The distal end was cannulated, sealed, and pressure clamped (mimicking cerebrospinal fluid [CSF] pressure), while the eye was also cannulated for independent control of intraocular pressure (IOP). The meninges were inflated (CSF pressure cycling 7-50 mmHg) while ONS outer diameter was imaged. In another set of experiments (n4), fluid permeation rate across the meninges was recorded by observing the drainage of an elevated fluid reservoir (30 mmHg) connected to the meninges. The ONS showed behavior typical of soft tissues: viscoelasticity, with hysteresis in early preconditioning cycles and repeatable behavior after 4 cycles, and nonlinear stiffening, particularly at CSF pressures 15 mmHg (Figure). Tangent moduli measured from the loading curve were 372 101, 1199 358, and 2050 379 kPa (mean SEM) at CSF pressures of 7, 15 and 30 mmHg, respectively. Flow rate measurements through the intact meninges at 30mmHg gave a permeability of 1.34 0.46 lmincm2mmHg (mean SEM). The ONS is a tough, strain-stiffening connective tissue that is surprisingly permeable. The latter observation suggests that there could be significant CSF drainage through the ONS into the orbit, likely important for CSF transport in the optic nerve. These experimental measurements, extended to human eyes, are informing computational models of the pathophysiology and biomechanics of the ONS in VIIP syndrome.
Long-duration space flight carries the risk of developing Visual Impairment and Intracranial Pressure (VIIP) syndrome, a spectrum of ophthalmic changes including posterior globe flattening, choroidal folds, distension of the optic nerve sheath (ONS), optic nerve kinking and potentially permanent degradation of visual function. The slow onset of VIIP, its chronic nature, and certain clinical features strongly suggest that biomechanical factors acting on the ONS play a role in VIIP. Here we measure several relevant ONS properties needed to model VIIP biomechanics. The ONS (meninges) of fresh porcine eyes (n7) was reflected, the nerve proper was truncated near the sclera, and the meninges were repositioned to create a hollow cylinder of meningeal connective tissue attached to the posterior sclera. The distal end was cannulated, sealed, and pressure clamped (mimicking cerebrospinal fluid [CSF] pressure), while the eye was also cannulated for independent control of intraocular pressure (IOP). The meninges were inflated (CSF pressure cycling 7-50 mmHg) while ONS outer diameter was imaged. In another set of experiments (n4), fluid permeation rate across the meninges was recorded by observing the drainage of an elevated fluid reservoir (30 mmHg) connected to the meninges. The ONS showed behavior typical of soft tissues: viscoelasticity, with hysteresis in early preconditioning cycles and repeatable behavior after 4 cycles, and nonlinear stiffening, particularly at CSF pressures 15 mmHg (Figure). Tangent moduli measured from the loading curve were 372 101, 1199 358, and 2050 379 kPa (mean SEM) at CSF pressures of 7, 15 and 30 mmHg, respectively. Flow rate measurements through the intact meninges at 30mmHg gave a permeability of 1.34 0.46 lmincm2mmHg (mean SEM). The ONS is a tough, strain-stiffening connective tissue that is surprisingly permeable. The latter observation suggests that there could be significant CSF drainage through the ONS into the orbit, likely important for CSF transport in the optic nerve. These experimental measurements, extended to human eyes, are informing computational models of the pathophysiology and biomechanics of the ONS in VIIP syndrome.
NASA is working to develop an integrated set of advanced technologies to enable efficient arrival operations in high-density terminal airspace for the Next Generation Air Transportation System. This integrated arrival solution is being validated and verified in laboratories and transitioned to a field prototype for an operational demonstration at a major U.S. airport. Within NASA, this is a collaborative effort between Ames and Langley Research Centers involving a multi-year iterative experimentation process. Designing and analyzing a series of sequential batch computer simulations and human-in-the-loop experiments across multiple facilities and simulation environments involves a number of statistical challenges. Experiments conducted in separate laboratories typically have different limitations and constraints, and can take different approaches with respect to the fundamental principles of statistical design of experiments. This often makes it difficult to compare results from multiple experiments and incorporate findings into the next experiment in the series. A statistical engineering approach is being employed within this project to support risk-informed decision making and maximize the knowledge gained within the available resources. This presentation describes a statistical engineering case study from NASA, highlights statistical challenges, and discusses areas where existing statistical methodology is adapted and extended.
INTRODUCTION As with most computational analyses, a tradeoff exists between problem complexity, resource availability and response accuracy when modeling radiation transport from the source to a detector. The largest amount of analyst time for setting up an analysis is often spent ensuring that any simplifications made have minimal impact on the results. The vehicle shield geometry of interest is typically simplified from the original CAD design in order to reduce computation time, but this simplification requires the analyst to "re-draw" the geometry with a limited set of volumes in order to accommodate a specific radiation transport software package. The resulting low-fidelity geometry model cannot be shared with or compared to other radiation transport software packages, and the process can be error prone with increased model complexity. The work presented here demonstrates the use of the DAGMC (Direct Accelerated Geometry for Monte Carlo) Toolkit from the University of Wisconsin, to model the impacts of several space radiation sources on a CAD drawing of the US Lab module. METHODS The DAGMC toolkit workflow begins with the export of an existing CAD geometry from the native CAD to the ACIS format. The ACIS format file is then cleaned using SpaceClaim to remove small holes and component overlaps. Metadata is then assigned to the cleaned geometry file using CUBIT/Trelis from csimsoft (Registered Trademark). The DAGMC plugin script removes duplicate shared surfaces, facets the geometry to a specified tolerance, and ensures that the faceted geometry is water tight. This step also writes the material and scoring information to a standard input file format that the analyst can alter as desired prior to running the radiation transport program. The scoring results can be transformed, via python script, into a 3D format that is viewable in a standard graphics program. RESULTS The CAD model of the US Lab module of the International Space Station, inclusive of all the racks and components, was simplified to remove holes and volume overlaps. Problematic features within the drawing were also removed or repaired to prevent runtime issues. The cleaned drawing was then run through the DAGMC workflow to prepare for analysis. Pilot tests modeling transport of 1GeV proton and 800MeV/A oxygen sources show that reasonable results are converged upon in an acceptable amount of overall computation time from drawing preparation to data analysis. The FLUKA radiation transport code will next be used to model both a GCR and a trapped radiation source. These results will then be compared with measurements that have been made by the radiation instrumentation deployed inside the US Lab module. DISCUSSION Early analyses have indicated that the DAGMC workflow is a promising toolkit for running vehicle geometries of interest to NASA through multiple radiation transport codes. In addition, recent work has shown that a realistic human phantom, provided via a subcontract with the University of Florida, can be placed inside any vehicle geometry for a combinatorial analysis. This added functionality gives the user the ability to score various parameters at the organ level, and the results can then be used as input for cancer risk models.
Rendering a complex spacecraft trajectory in high fidelity can be an expensive endeavor, both computationally and from a human time/cost standpoint. However, in many cases, a low-fidelity trajectory that reasonably approximates a high-fidelity counterpart is much easier to obtain. Thus, it is important to have an efficient process for converting a trajectory from lower-fidelity model to high fidelity. We present a method for converting low-fidelity trajectories into high fidelity that relies on multiple shooting, nonlinear programming, and numerical integration. The procedure converts any zero-radius sphere-of-influence gravity-assist events to fully integrated flyby events. Several numerical examples are presented that showcase the flexibility of the high-fidelity rendering process across multiple mission types and flight regimes.
This panel identifies the challenges of supporting medical events in deep space using integrated systems software to augment existing capabilities during increasingly Earth-independent missions where an asynchronous communication environment becomes routine. An interdisciplinary team of software designers, physicians, human factors engineers, and computational modelers applied their respective expertise to develop a roadmap for supporting the crew making medical decisions in more autonomous fashion with time-delayed ground support. The first presentation describes predictive modeling implemented to assist medical system design and address risk reduction using robust clinical decision support software. The second presentation details how operational and environmental challenges guide assumptions and, in turn, by what means requirements for medical decision-making in deep space are derived. The third presentation describes and defines the skills and capabilities an exploration spaceflight medical officer will need to perform effectively during extended-duration spaceflight missions. The fourth presentation covers the potential models and function of the software element for supporting clinical decisions. The final presentation covers how these elements may work together with ground support to provide comprehensive care despite deep space travel's extreme challenges and limitations.
Explore the source record for details and available documents.
The rapid evolution of electronics has heralded countless benefits to humanity, enabling increases in computing power while decreasing costs. However, the constantly changing semiconductor device landscape proves to be an immense challenge for the reliability community, especially for those concerned with radiation effects on microelectronics. Changes in device manufacturing, from device structure to processing steps, may and often do change the way the device responds to radiation. While radiation hardened parts are not as much of a reliability concern, they also lag behind commercial off-the-shelf, or COTS, parts in terms of computing capabilities, some by over a decade. Many missions may have no choice but to utilize COTS. As such, these missions need to ensure their parts are reliable in the face of total ionizing dose (TID). However, part and testing facility costs limit the amount of testing possible.
The Medical Extensible Dynamic Probabilistic Risk Assessment Tool (MEDPRAT) is a computational model that provides human health and medical risk predictions for crewed spaceflight missions. MEDPRAT utilizes discrete event modeling and dynamic probabilistic simulation to predict critical mission outcomes (total medical events, crew health index, quality time lost, loss of crew life, removal to definitive care), condition occurrences, and resource consumption. Input parameters for MEDPRAT include crew attributes (e.g., sex), types of mission activities (e.g., whether and where crew members perform an extravehicular activity (EVA)), available resources, treatment information, and probability distributions for medical conditions. As an evolution of the Integrated Medical Model (IMM), MEDPRAT provides enhanced capabilities and higher fidelity, and incorporates more appropriate assumptions for long-duration spaceflight. IMM is the currently accepted standard for quantifying spaceflight mission medical risk in NASA operations that uses a probabilistic risk assessment (PRA) approach. MEDPRAT builds on the same logical foundation as IMM but implements the model architecture through highly optimized Monte Carlo sampling methods. An analysis is performed comparing the outputs from IMM with those from MEDPRAT V1.0 and V2.0 for the same reference missions in order to quantify similarities and differences in the model outcomes. The juxtaposition between IMM and MEDPRAT V1.0 and 2.0 shown in this report demonstrates that these two models generate very similar results; where differences in outcomes are shown, these are in accordance with the underlying assumptions and differences in the model architectures. This validation effort further establishes the credibility and reliability of the MEDPRAT software.
The critical mission tasks assessments effort seeks to determine the physical performance requirements that astronauts must meet in order to safely and successfully accomplish lunar exploration missions. These assessments will determine astronaut preflight strength, fitness, and flexibility requirements, and the extent to which exercise and other countermeasures must prevent the physical deconditioning associated with prolonged weightlessness. The purpose is to determine the flexibility and strength that crewmembers must possess in order to reach Crew Exploration Vehicle controls during maneuvers that result in sustained acceleration levels ranging from 3.7G to 7.8G. An industry standard multibody dynamics application was used to create human models representing a 5th percentile female, a 50th percentile male, and a 95th percentile male. The additional mass of a space suit sleeve was added to the reaching arm to account for the influence of the suit mass on the reaching effort. The human model was merged with computer models of a pilot seat and control panel for the Crew Exploration Vehicle. Three dimensional paths were created that guided the human models hand from a starting position alongside its thigh to three control targets: a joystick, a keyboard, and an overhead switch panel. The reaching motion to each target was repeated under four vehicle acceleration conditions: nominal ascent (3.7G), two ascent aborts (5.5G and 7.8G) and lunar reentry (4.6G). Elbow and shoulder joint angular excursions were analyzed to assess range of motion requirements. Mean and peak elbow and shoulder joint torques were determined and converted to equivalent resistive exercise loads to assess strength requirements. Angular excursions for the 50th and 95th percentile male models remained within joint range of motion limits. For the 5th percentile female, both the elbow and the shoulder exceeded range of motion limits during the overhead reach. Elbow joint torques ranged from 10 N-m (nominal ascent) to 60 N-m (ascent abort). Shoulder joint torques ranged from 65 N-m (nominal ascent) to 280 N-m (ascent abort). Maximal equivalent exercise loads reached 30 lb in tricep extension, 9 lb in bicep curl, 110 lb in unilateral pullover and unilateral bench press for nominal conditions (lunar reentry), and 188 lb in unilateral pullover and unilateral bench press. The location of the pilot seat was found to be inadequately located to allow a 5th percentile female to reach the switches on the overhead panel. Elbow strength requirements were found to be well within population norms. Shoulder strength was found to be a limiting factor. Reaching under nominal ascent and lunar reentry conditions was found to require near maximal shoulder strength. Reaching under ascent abort conditions requires shoulder strength well beyond population norms. Pilot seats must adjust to accomodate a 5th percentile female. Exercise countermeasures must maintain maximal pullover and bench press strength to allow pilots to reach and operate controls during lunar reentry. Reaching will not be possible during ascent abort conditions. Flight controls should be built into armrests or flight control must be accomplished by autonomous systems during acceleration exceeding 4.6G.
Compared to equipment designed to perform the same function over and over, humans are just not as reliable. Computers and machines perform the same action in the same way repeatedly getting the same result, unless equipment fails or a human interferes. Humans who are supposed to perform the same actions repeatedly often perform them incorrectly due to a variety of issues including: stress, fatigue, illness, lack of training, distraction, acting at the wrong time, not acting when they should, not following procedures, misinterpreting information or inattention to detail. Why not use robots and automatic controls exclusively if human error is so common? In an emergency or off normal situation that the computer, robotic element, or automatic control system is not designed to respond to, the result is failure unless a human can intervene. The human in the loop may be more likely to cause an error, but is also more likely to catch the error and correct it. When it comes to unexpected situations, or performing multiple tasks outside the defined mission parameters, humans are the only viable alternative. Human Reliability Assessments (HRA) identifies ways to improve human performance and reliability and can lead to improvements in systems designed to interact with humans. Understanding the context of the situation that can lead to human errors, which include taking the wrong action, no action or making bad decisions provides additional information to mitigate risks. With improved human reliability comes reduced risk for the overall operation or project.
The Spartan Attitude Control System (ACS) contains a command and control computer. This computer is optimized for the activities of the flight and contains very little human interface hardware and software. The computer system provides the technicians testing of Spartan ACS with a convenient command-oriented interface to the flight ACS computer. The system also decodes and time tags data automatically sent out by the flight computer as key events occur. The duration and magnitude of all system maneuvers is also derived and displayed by this system. The Ground Support Computer is also the primary Ground Support Equipment for the flight sequencer which controls all payload maneuvers, and long term program timing.
CMOS-based computing systems that employ the von Neumann architecture are relatively limited when it comes to parallel data storage and processing. In contrast, the human brain is a living computational signal processing unit that operates with extreme parallelism and energy efficiency. Although numerous neuromorphic electronic devices have emerged in the last decade, most of them are rigid or contain materials that are toxic to biological systems. In this work, we report on biocompatible bilayer graphene-based artificial synaptic transistors (BLAST) capable of mimicking synaptic behavior. The BLAST devices leverage a dry ion-selective membrane, enabling long-term potentiation, with ~50 aJ/µm 2 switching energy efficiency, at least an order of magnitude lower than previous reports on two-dimensional material-based artificial synapses. The devices show unique metaplasticity, a useful feature for generalizable deep neural networks, and we demonstrate that metaplastic BLASTs outperform ideal linear synapses in classic image classification tasks. With switching energy well below the 1 fJ energy estimated per biological synapse, the proposed devices are powerful candidates for bio-interfaced online learning, bridging the gap between artificial and biological neural networks.