Results for “software behavior computation” — Page 26

DOE OSTI2015

SU-E-T-235: Data Mining for Evaluating Treatment Performances Over a Large Quantity of Data to Monitor and Improve SBRT Workflow

Purpose: To quality assure a large quantity of retrospective treatment cases for treatment performances by randomly sampling is inefficient. Here we provide a method to efficiently monitor and investigate the QA of SBRT workflow over Mosaiq. Methods: The code developed with Microsoft SQL Server Management Studio 2008R2 and VBA was used for retrieving and sorting data from Mosaiq (version 2.3–2.6 during 2012–2015). SBRT patients were filtered by fractional dose over 350cGy and total fraction number less than 6, which SBRT prescriptions were defined. The quality assurance on the SBRT workflow was focused on the treatment deliveries such as patient positioning setup, CBCT indicated offsets and couch shifted corrections. The treatment delivery were done by Varian Truebeam systems and the record/verify by Mosaiq. Results: Total 82 SBRT patients corresponding to 103 courses and 854 CBCT images were found by the retrieval query. Most centers record daily pre-treatment (Pre-Tx: before treatment shift) image-guided shifts along treatment course for inter-fraction motion record, and it is useful to also verify it with post-treatment imaging (Post-Tx: after treatment CBCT verification) to verify intra-fraction motion. Analyzing the details of daily recorded shifts can reveals the information of patient-setup and staff’s record/verify behaviors. 3 examples were provided as solid evidences and on-going rectification for preventing future mistakes. Conclusions: The report gave feasible examples for inspector to verify a large amount of data during site investigation. This program can also be extended to a scheduled data mining with software to periodical analyze the timely records in Mosaiq, for example, a various control charts for different QA purposes. As the current trend of automation in radiation therapy field, the data mining would be a necessary tool in the future, just as the automatic plan quality evaluation has been under development in Eclipse.

60 APPLIED LIFE SCIENCES↗

NASA NTRSDate not supplied

ARCTRON: A Rapid Experimental Proving Ground for TPS Experiments and Arcjet Technology Development

Innovation in high-enthalpy facilities is fundamentally limited by the cost and risk of experimentation. New concepts for plasma control, diagnostics, facility components, and plasma-material interaction often require repeated iterations that are impractical to perform in production arcjets. As a result, promising ideas may remain unexplored or reach operational facilities only after significant development effort. ARCTRON is being developed as a rapid experimental proving ground where new ideas in plasma science, arcjet engineering, diagnostics, and material response can be conceived, tested, and quantitatively evaluated before transition to large-scale facilities. The platform combines radio-frequency (RF) and DC arc plasma generation, externally applied magnetic fields, configurable gas composition, reduced-pressure operation, laser heating, electrical biasing, and modular diagnostic access. These capabilities permit the plasma source, applied forcing, test article, and measurement configuration to be modified independently, allowing individual physical mechanisms to be isolated more readily than in a traditional test environment. One class of investigations addresses fundamental plasma-surface interaction physics. Conventional material tests often expose a specimen simultaneously to convective heating, reactive species, pressure, shear, radiation, and surface-current effects. The resulting material response may be measured accurately, while the contribution of each mechanism remains difficult to identify. ARCTRON is designed to vary these effects selectively. Plasma chemistry can be changed independently through configurable gas mixtures; magnetic fields and electrical biasing can modify charged-particle transport; laser heating can provide a non-plasma thermal input; and pressure, flow, and discharge mode can be varied over a broad operating space. This enables controlled tests of hypotheses involving surface catalycity, reactive-species transport, plasma-assisted oxidation, electromagnetic effects, shear, and the relative contributions of thermal and chemical loading. A second class of investigations enabled by this approach concerns the engineering of high-enthalpy facilities themselves. Arc-heated facilities are limited by electrode erosion, unstable arc attachment, localized heating, and damage to nozzles and other plasma-facing components. ARCTRON provides a lower-cost environment for testing concepts intended to mitigate these limitations. Candidate investigations include the use of applied magnetic fields to alter current paths and reduce plasma interaction with nozzle walls, ExB forcing to introduce controlled plasma rotation, magnetic or geometric approaches for distributing arc attachment, and alternative electrode or discharge configurations intended to reduce erosion and improve stability. Because the platform is reconfigurable, these concepts can be evaluated through repeated design--build--test cycles before they are considered for implementation in operational facilities. The platform also supports the development and validation of diagnostics that may be difficult to introduce initially into a large arcjet. Current and planned measurements include spatially resolved optical emission spectroscopy, electrostatic probes, fast imaging, pyrometry, calorimetry, laser-induced fluorescence, and absorption spectroscopy. These diagnostics are intended not merely to document a nominal operating condition, but to constrain the local plasma state and its relationship to component or material response. The modular facility geometry allows diagnostic concepts to be tested, calibrated, and compared under repeatable conditions before deployment in more demanding environments. ARCTRON is also supported by an integrated software suite. Automated control and data acquisition allow discharge parameters, gas composition, magnetic fields, diagnostic timing, and test configuration to be recorded as part of each experiment (STARDAC - Software for Testing, Analysis, Research Data, and Control). The Backend for Experiment Analysis, Storage, and Traceability (BEAST) is a database that provides the infrastructure needed to associate heterogeneous measurements with facility configuration, specimen identity, calibration state, geometry, and analysis provenance. This backend is particularly important for exploratory campaigns, in which many related configurations may be tested, and the value of an individual experiment depends on its connection to earlier and subsequent iterations. Complementary analysis capabilities, including computer-vision-based transient response measurements (arcjetCV), three-dimensional surface reconstruction (STARSCAN), and model-based Bayesian inference (SHIELD), and tomography data analysis (TOMATO, PuMA) can be incorporated when required by a specific hypothesis without becoming the focus of every campaign. The central objective of ARCTRON is therefore not to maximize heat flux or reproduce a complete flight environment. Its purpose is to reduce the cost and time required to ask consequential questions about plasma behavior, plasma-facing materials, diagnostics, and arcjet technology. By providing a controlled environment for rapid reconfiguration, mechanism isolation, quantitative measurement, and iterative engineering, ARCTRON can help mature concepts that would otherwise remain too speculative or too risky for evaluation in production facilities. The resulting knowledge can then guide the design of material models, focus test objectives in larger arcjets, reduce facility-development risk, and improve the physical basis of high-enthalpy ground testing. This work will present the ARCTRON architecture, operating modes, diagnostic suite, and digital experimental workflow. Initial experimental results from the first integrated operation of the facility will be presented, including flow characterization, power limitations, and deployment of the initial diagnostic suite. Ongoing development efforts aimed at catalycity characterization, magnetic plasma control, and advanced optical diagnostics will also be discussed, illustrating how the platform supports rapid iteration from concept to experiment.

experimental diagnostics↗

NASA NTRSDate not supplied

ARCTRON: A Rapid Experimental Proving Ground for TPS Experiments and Arcjet Technology Development

Innovation in high-enthalpy facilities is fundamentally limited by the cost and risk of experimentation. New concepts for plasma control, diagnostics, facility components, and plasma-material interaction often require repeated iterations that are impractical to perform in production arcjets. As a result, promising ideas may remain unexplored or reach operational facilities only after significant development effort. ARCTRON is being developed as a rapid experimental proving ground where new ideas in plasma science, arcjet engineering, diagnostics, and material response can be conceived, tested, and quantitatively evaluated before transition to large-scale facilities. The platform combines radio-frequency (RF) and DC arc plasma generation, externally applied magnetic fields, configurable gas composition, reduced-pressure operation, laser heating, electrical biasing, and modular diagnostic access. These capabilities permit the plasma source, applied forcing, test article, and measurement configuration to be modified independently, allowing individual physical mechanisms to be isolated more readily than in a traditional test environment. One class of investigations addresses fundamental plasma-surface interaction physics. Conventional material tests often expose a specimen simultaneously to convective heating, reactive species, pressure, shear, radiation, and surface-current effects. The resulting material response may be measured accurately, while the contribution of each mechanism remains difficult to identify. ARCTRON is designed to vary these effects selectively. Plasma chemistry can be changed independently through configurable gas mixtures; magnetic fields and electrical biasing can modify charged-particle transport; laser heating can provide a non-plasma thermal input; and pressure, flow, and discharge mode can be varied over a broad operating space. This enables controlled tests of hypotheses involving surface catalycity, reactive-species transport, plasma-assisted oxidation, electromagnetic effects, shear, and the relative contributions of thermal and chemical loading. A second class of investigations enabled by this approach concerns the engineering of high-enthalpy facilities themselves. Arc-heated facilities are limited by electrode erosion, unstable arc attachment, localized heating, and damage to nozzles and other plasma-facing components. ARCTRON provides a lower-cost environment for testing concepts intended to mitigate these limitations. Candidate investigations include the use of applied magnetic fields to alter current paths and reduce plasma interaction with nozzle walls, ExB forcing to introduce controlled plasma rotation, magnetic or geometric approaches for distributing arc attachment, and alternative electrode or discharge configurations intended to reduce erosion and improve stability. Because the platform is reconfigurable, these concepts can be evaluated through repeated design--build--test cycles before they are considered for implementation in operational facilities. The platform also supports the development and validation of diagnostics that may be difficult to introduce initially into a large arcjet. Current and planned measurements include spatially resolved optical emission spectroscopy, electrostatic probes, fast imaging, pyrometry, calorimetry, laser-induced fluorescence, and absorption spectroscopy. These diagnostics are intended not merely to document a nominal operating condition, but to constrain the local plasma state and its relationship to component or material response. The modular facility geometry allows diagnostic concepts to be tested, calibrated, and compared under repeatable conditions before deployment in more demanding environments. ARCTRON is also supported by an integrated software suite. Automated control and data acquisition allow discharge parameters, gas composition, magnetic fields, diagnostic timing, and test configuration to be recorded as part of each experiment (STARDAC - Software for Testing, Analysis, Research Data, and Control). The Backend for Experiment Analysis, Storage, and Traceability (BEAST) is a database that provides the infrastructure needed to associate heterogeneous measurements with facility configuration, specimen identity, calibration state, geometry, and analysis provenance. This backend is particularly important for exploratory campaigns, in which many related configurations may be tested, and the value of an individual experiment depends on its connection to earlier and subsequent iterations. Complementary analysis capabilities, including computer-vision-based transient response measurements (arcjetCV), three-dimensional surface reconstruction (STARSCAN), and model-based Bayesian inference (SHIELD), and tomography data analysis (TOMATO, PuMA) can be incorporated when required by a specific hypothesis without becoming the focus of every campaign. The central objective of ARCTRON is therefore not to maximize heat flux or reproduce a complete flight environment. Its purpose is to reduce the cost and time required to ask consequential questions about plasma behavior, plasma-facing materials, diagnostics, and arcjet technology. By providing a controlled environment for rapid reconfiguration, mechanism isolation, quantitative measurement, and iterative engineering, ARCTRON can help mature concepts that would otherwise remain too speculative or too risky for evaluation in production facilities. The resulting knowledge can then guide the design of material models, focus test objectives in larger arcjets, reduce facility-development risk, and improve the physical basis of high-enthalpy ground testing. This work will present the ARCTRON architecture, operating modes, diagnostic suite, and digital experimental workflow. Initial experimental results from the first integrated operation of the facility will be presented, including flow characterization, power limitations, and deployment of the initial diagnostic suite. Ongoing development efforts aimed at catalycity characterization, magnetic plasma control, and advanced optical diagnostics will also be discussed, illustrating how the platform supports rapid iteration from concept to experiment.

experimental diagnostics↗

DOE OSTI2016

HyRAM (Hydrogen Risk Assessment Models) v. 1.0

HyRAM is a software toolkit for conducting quantitative risk assessment (QRA) and consequence modeling for hydrogen infrastructure and transportation systems. HyRAM contains validated, simplified hydrogen behavior models, a standardized QRA approach, and engineering models and generic data relevant to hydrogen installations. HyRAM 1.0 was developed by Sandia National Laboratories for the U. S. Department of Energy to increase access to technical data about hydrogen and to enable the use of that data to support development and revision of national and international codes and standards with risk assessment and consequence modeling. The HyRAM toolkit integrates analytical and probabilistic models for quantifying accident scenarios, predicting physical effects, and characterizing the impact of hydrogen hazards (including thermal effects from jet fires and overpressure effects from deflagrations in confined areas) on people and structures. HyRAM incorporates generic probabilities for equipment failures for nine types of components, and probabilistic models for the impact of heat flux on humans and structures, with computationally and experimentally validated analytical first order models of hydrogen release and flame physics. Version 1 can be used to quantify the risk and consequences associated with gaseous hydrogen releases from user-defined hydrogen installations.

Groth, Katrina M.↗

DOE OSTI2017

XPRESS: eXascale PRogramming Environment and System Software

The XPRESS project is the research and development of a complete software architecture for Exascale computing. The four major R&D thrusts include: 1) an Exascale lightweight kernel operating system (LXK), based on the Kitten operating system (OS), to manage billion way hardware parallelism, management of faults and power, management of global virtual name space, and other features of future system architectures; 2) a runtime system (HPX-5), co-designed with LXK, based on the ParalleX execution model that supports dynamic resource management and task scheduling; 3) system interfaces for interoperability between the runtime system and both the OS and the runtime system (RIOS); 4) compilation strategies and systems to translate MPI and OpenMP legacy codes to a form that can be run with performance at least as good as a native code implementation. The software architecture development has been driven by performance evaluation of mini-applications developed at Department of Energy Co-Design Centers as well as ancillary in-house developed applications and benchmarks. Research on the ParalleX execution model has been driven by the development of formal semantics and model checkers for the execution model. The major components of the software architecture are: ParalleX execution model – guiding principles for co-design of components of the system stack with advances in locality management and task prioritization through introspection; HPX runtime system – support of application dynamic adaptive resource management, task scheduling, and introspective control policies; LXK operating system – lightweight kernel operating system for order-constant scalability and low/no noise to manage resources; RIOS – a realm of Exascale system operation unique in the XPRESS project that includes the relationship between the new generation of lightweight kernel operating systems and runtime system software; XPI advanced programming model – intermediate form and low-level (readable) programming interface reflecting the ParalleX model, providing a target for source-to- source high level parallel language translation, and supporting early direct programming experimentation and measurement; Performance models & metrics – providing parameters and their mutual sensitivities to guide co-design and quantify operational behavior; Legacy migration – ensuring seamless transition of legacy codes and programming methods to the future generation of ParalleX-based Exascale systems; . Experiments and evaluation – critical to determining degree of effectiveness and likelihood of ultimate success as well as guiding corrective design changes to achieve DOE objectives; and Applications – collaborations with Co-Design Centers and other mission critical codes. The exemplar implementation of the ParalleX execution model, HPX-5, has been released along with five fully ported applications (LULESH, HPCG, SSSP, WAMR, and DASHMM) and multiple microbenchmarks. Using these applications, the system architecture demonstrated dynamic load balancing through active migration, legacy code migration, and data-driven approaches to for graph-like applications. Crucially for Exascale and billion way parallelism, the needs and patterns of irregular applications in HPX-5 were addressed using local flow control rather than relying on globally synchronized data structures.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1987

Expert system technology

The expert system is a computer program which attempts to reproduce the problem-solving behavior of an expert, who is able to view problems from a broad perspective and arrive at conclusions rapidly, using intuition, shortcuts, and analogies to previous situations. Expert systems are a departure from the usual artificial intelligence approach to problem solving. Researchers have traditionally tried to develop general modes of human intelligence that could be applied to many different situations. Expert systems, on the other hand, tend to rely on large quantities of domain specific knowledge, much of it heuristic. The reasoning component of the system is relatively simple and straightforward. For this reason, expert systems are often called knowledge based systems. The report expands on the foregoing. Section 1 discusses the architecture of a typical expert system. Section 2 deals with the characteristics that make a problem a suitable candidate for expert system solution. Section 3 surveys current technology, describing some of the software aids available for expert system development. Section 4 discusses the limitations of the latter. The concluding section makes predictions of future trends.

Prince, Mary Ellen↗

NASA NTRS2007

Analysis of Complex Valve and Feed Systems

A numerical framework for analysis of complex valve systems supports testing of propulsive systems by simulating key valve and control system components in the test loop. In particular, it is designed to enhance the analysis capability in terms of identifying system transients and quantifying the valve response to these transients. This system has analysis capability for simulating valve motion in complex systems operating in diverse flow regimes ranging from compressible gases to cryogenic liquids. A key feature is the hybrid, unstructured framework with sub-models for grid movement and phase change including cryogenic cavitations. The multi-element unstructured framework offers improved predictions of valve performance characteristics under steady conditions for structurally complex valves such as pressure regulator valve. Unsteady simulations of valve motion using this computational approach have been carried out for various valves in operation at Stennis Space Center such as the split-body valve and the 10-in. (approx.25.4-cm) LOX (liquid oxygen) valve and the 4-in. (approx.10 cm) Y-pattern valve (liquid nitrogen). Such simulations make use of variable grid topologies, thereby permitting solution accuracy and resolving important flow physics in the seat region of the moving valve. An advantage to this software includes possible reduction in testing costs incurred due to disruptions relating to unexpected flow transients or functioning of valve/flow control systems. Prediction of the flow anomalies leading to system vibrations, flow resonance, and valve stall can help in valve scheduling and significantly reduce the need for activation tests. This framework has been evaluated for its ability to predict performance metrics like flow coefficient for cavitating venturis and valve coefficient curves, and could be a valuable tool in predicting and understanding anomalous behavior of system components at rocket propulsion testing and design sites.

Ahuja, Vineet↗

DOE OSTI2017

Estimating a Service-Life Distribution Based on Production Counts and a Failure Database

A manufacturer wanted to compare the service-life distributions of two similar products. These concern product lifetimes after installation (not manufacture). For each product, there were available production counts and an imperfect database providing information on failing units. In the real case, these units were expensive repairable units warrantied against repairs. Failure (of interest here) was relatively rare and driven by a different mode/mechanism than ordinary repair events (not of interest here). Approach: Data models for the service life based on a standard parametric lifetime distribution and a related limited failure population were developed. These models were used to develop expressions for the likelihood of the available data that properly accounts for information missing in the failure database. Results: A Bayesian approach was employed to obtain estimates of model parameters (with associated uncertainty) in order to investigate characteristics of the service-life distribution. Custom software was developed and is included as Supplemental Material to this case study. One part of a responsible approach to the original case was a simulation experiment used to validate the correctness of the software and the behavior of the statistical methodology before using its results in the application, and an example of such an experiment is included here. Because of confidentiality issues that prevent use of the original data, simulated data with characteristics like the manufacturer’s proprietary data are used to illustrate some aspects of our real analyses. Lastly, we also note that, although this case focuses on rare and complete product failure, the statistical methodology provided is directly applicable to more standard warranty data problems involving typically much larger warranty databases where entries are warranty claims (often for repairs) rather than reports of complete failures.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1991

Mechanical behavior of a ceramic matrix composite material

Monolithic ceramic materials have been used in industry for hundreds of years. These materials have proven their usefulness in many applications, yet, their potential for critical structural applications is limited. The existence of an imperfection in a monolithic ceramic on the order of several microns in size may be critical, resulting in catastrophic failure. To overcome this extreme sensitivity to small material imperfections, reinforced ceramic materials were developed. A ceramic matrix which has been reinforced with continuous fibers is not only less sensitive to microscopic flaws, but is also able to sustain significant damage without suffering catastrophic failure. A borosilicate glass reinforced with several layers of plain weave silicon carbide cloth (Nicalon) was studied. The mechanical testing which was performed included both flexural and tensile loading configurations. This testing was done not only to determine the material properties, but also to initiate a controlled amount of damage within each specimen. Several nondestructive testing techniques, including acousto-ultrasonics (AU), were performed on the specimens periodically during testing. The AU signals were monitored through the use of an IBM compatible personal computer with a high speed data acquisition board. Software was written which manipulates the AU signals in both the time and frequency domains, resulting in quantitative measures of the mechanical response of the material. The measured AU parameters are compared to both the mechanical test results and data from other nondestructive methods including ultrasonic C-scans and penetrant enhanced x ray radiography.

Grosskopf, Paul P.↗

NASA NTRS1990

Modeling and simulation of the space platform power system

A comprehensive computer-aided modeling and simulation technique for the space platform power system is described. Large-signal and small-signal modeling is presented for the system components. The component models have been integrated to form the complete power system model. The system model is shown to be a powerful tool in simulating the behavior of the system with variation of illumination level and load. It can be used to study the bus regulation in each mode and to observe mode changes as the solar array is subjected to transitions from sunlight to eclipse and back to sunlight. System simulations show how the bus regulation is maintained by activating the shunt switching unit, the charger, or the discharger, depending on the available illumination level. The system model is suitable for verifying hardware results of for analyzing the performance of a proposed system where hardware testing is not feasible. The EASY5 dynamic analysis program is used as the host software for the modeling and simulation.

Patil, A. R.↗

DOE OSTI2023

Architecture-Preserving Provable Repair of Deep Neural Networks

Deep neural networks (DNNs) are becoming increasingly important components of software, and are considered the state-of-the-art solution for a number of problems, such as image recognition. However, DNNs are far from infallible, and incorrect behavior of DNNs can have disastrous real-world consequences. This paper addresses the problem of architecture-preserving V-polytope provable repair of DNNs. A V-polytope defines a convex bounded polytope using its vertex representation. V-polytope provable repair guarantees that the repaired DNN satisfies the given specification on the infinite set of points in the given V-polytope. An architecture-preserving repair only modifies the parameters of the DNN, without modifying its architecture. The repair has the flexibility to modify multiple layers of the DNN, and runs in polynomial time. It supports DNNs with activation functions that have some linear pieces, as well as fully-connected, convolutional, pooling and residual layers. To the best our knowledge, this is the first provable repair approach that has all of these features. We implement our approach in a tool called APRNN. Using MNIST, ImageNet, and ACAS Xu DNNs, we show that it has better efficiency, scalability, and generalization compared to PRDNN and REASSURE, prior provable repair methods that are not architecture preserving.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2026

Holistic Transportation and Energy Modeling

This project advances the development and application of the TEMPO transportation energy systems model to support DOE analysis of evolving mobility futures. Recent work has focused on improving model transparency, performance, and fidelity through a redesigned software architecture and updated technology adoption scenarios aligned with the latest data and assumptions. Ongoing efforts aim to expand TEMPO's ability to assess transportation affordability and consumer decision-making, including vehicle ownership dynamics and distributional impacts across households. These enhancements position TEMPO to better inform policy and R&D decisions by providing more behaviorally realistic and policy-relevant insights into transportation energy use, technology adoption, and system-level outcomes.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2018

First Principles Prediction of Structure, Structure Selectivity, and Thermodynamic Stability under Realistic Conditions

Novel materials are often the enabler for new energy technologies. In ab-initio computational materials science, method are developed to predict the behavior of materials starting from the laws of physics, so that properties can be predicted before compounds have to be synthesized and tested. As such, a virtual materials laboratory can be constructed, saving time and money. The objectives of this program were to develop first-principles theory to predict the structure and thermodynamic stability of materials. Since its inception the program focused on the development of the cluster expansion to deal with the increased complexity of complex oxides. This research led to the incorporation of vibrational degrees of freedom in ab-initio thermodynamics, developed methods for multi-component cluster expansions, included the explicit configurational degrees of freedom of localized electrons, developed the formalism for stability in aqueous environments, and culminated in the first ever approach to produce exact ground state predictions of the cluster expansion. Many of these methods have been disseminated to the larger theory community through the Materials Project, pymatgen software, or individual codes. We summarize three of the main accomplishments.

36 MATERIALS SCIENCE↗

DOE OSTI2016

SU-F-T-490: Separating Effects Influencing Detector Response in Small MV Photon Fields

Purpose: Different detector properties influence their responses especially in field sizes below the lateral electron range. Due to the finite active volume, the detector density and electron perturbation at other structural parts, the response factor is in general field size dependent. We aimed to visualize and separate the main effects contributing to detector behavior for a variety of detector types. This was achieved in an experimental setup, shielding the field center. Thus, effects caused by scattered radiation could be examined separately. Methods: Signal ratios for field sizes down to 8 mm (SSD 90 cm, water depth 10 cm) of a 6MV beam from a Siemens Primus LINAC were recorded with several detectors: PTW microDiamond and PinPoint ionization chamber, shielded diodes (PTW P-60008, IBA PFD and SNC Edge) and unshielded diodes (PTW E-60012 and IBA SFD). Measurements were carried out in open fields and with an aluminum pole of 4 mm diameter as a central block. The geometric volume effect was calculated from profiles obtained with Gafchromic EBT3 film, evaluated using FilmQA Pro software (Ashland, USA). Results: Volume corrections were 1.7% at maximum. After correction, in small open fields, unshielded diodes showed a lower response than the diamond, i.e. diamond detector over-response seems to be higher than that for unshielded diodes. Beneath the block, this behavior was amplified by a factor of 2. For the shielded diodes, the overresponse for small open fields could be confirmed. However their lateral response behavior was strongly type dependent, e.g. the signal ratio dropped from 1.02 to 0.98 for the P-60008 diode. Conclusion: The lateral detector response was experimentally examined. Detector volume and density alone do not fully account for the field size dependence of detector response. Detector construction details play a major role, especially for shielded diodes.

61 RADIATION PROTECTION AND DOSIMETRY↗

NASA NTRS2004

Multisensor Arrays for Greater Reliability and Accuracy

Arrays of multiple, nominally identical sensors with sensor-output-processing electronic hardware and software are being developed in order to obtain accuracy, reliability, and lifetime greater than those of single sensors. The conceptual basis of this development lies in the statistical behavior of multiple sensors and a multisensor-array (MSA) algorithm that exploits that behavior. In addition, advances in microelectromechanical systems (MEMS) and integrated circuits are exploited. A typical sensor unit according to this concept includes multiple MEMS sensors and sensor-readout circuitry fabricated together on a single chip and packaged compactly with a microprocessor that performs several functions, including execution of the MSA algorithm. In the MSA algorithm, the readings from all the sensors in an array at a given instant of time are compared and the reliability of each sensor is quantified. This comparison of readings and quantification of reliabilities involves the calculation of the ratio between every sensor reading and every other sensor reading, plus calculation of the sum of all such ratios. Then one output reading for the given instant of time is computed as a weighted average of the readings of all the sensors. In this computation, the weight for each sensor is the aforementioned value used to quantify its reliability. In an optional variant of the MSA algorithm that can be implemented easily, a running sum of the reliability value for each sensor at previous time steps as well as at the present time step is used as the weight of the sensor in calculating the weighted average at the present time step. In this variant, the weight of a sensor that continually fails gradually decreases, so that eventually, its influence over the output reading becomes minimal: In effect, the sensor system "learns" which sensors to trust and which not to trust. The MSA algorithm incorporates a criterion for deciding whether there remain enough sensor readings that approximate each other sufficiently closely to constitute a majority for the purpose of quantifying reliability. This criterion is, simply, that if there do not exist at least three sensors having weights greater than a prescribed minimum acceptable value, then the array as a whole is deemed to have failed.

Immer, Christopher↗

NASA NTRS1996

Evaluation of an Anthropometric Human Body Model for Simulated EVA Task Assessment

One of the more mission-critical tasks performed in space is extravehicular activity (EVA) which requires the astronaut to be external to the station or spacecraft, and subsequently at risk from the many threats posed by space. These threats include, but are not limited to: no significant atmosphere, harmful electromagnetic radiation, micrometeoroids, and space debris. To protect the astronaut from this environment, a special EVA suit is worn which is designed to maintain a sustainable atmosphere (at 1/3 atmosphere) and provide protection against the hazards of space. While the EVA suit serves these functions well, it does impose limitations on the astronaut as a consequence of the safety it provides. Since the astronaut is in a virtual vacuum, any atmospheric pressure inside the suit serves to pressurize the suit and restricts mobility of flexible joints (such as fabric). Although some of the EVA suit joints are fixed, rotary-style joints, most of the mobility is achieved by the simple flexibility of the fabric. There are multiple layers of fabric, each of which serves a special purpose in the safety of the astronaut. These multiple layers add to the restriction of motion the astronaut experiences in the space environment. Ground-based testing is implemented to evaluate the capability of EVA-suited astronauts to perform the various tasks in space. In addition to the restriction of motion imposed by the EVA suit, most EVA activity is performed in a micro-gravity (weight less) environment. To simulate weightlessness EVA-suited testing is performed in a neutral buoyancy simulator (NBS). The NBS is composed of a large container of water (pool) in which a weightless environment can be simulated. A subject is normally buoyant in the pressurized suit; however he/she can be made neutrally buoyant with the addition of weights. In addition, most objects the astronaut must interface with in the NBS sink in water and flotation must be added to render them "weightless". The implementation of NBS testing has proven to invaluable in the assessment of EVA activities performed with the Orbiter and is considered to be a key step in the construction of the International Space Station (ISS). While the NBS testing is extremely valuable, it does require considerable overhead to maintain and operate. It has been estimated that the cost of utilizing the facility is approximately $10,000 per day. Therefore it is important to maximize the utility of NBS testing for optimal results. One important aspect to consider in any human/worksite interface is the considerable wealth of anthropometric and ergonomic data available. A subset of this information specific to EVA activity is available in NASA standard 3000. The difficulty in implementing this data is that most of the anthropometric information is represented in a two-dimensional format. This poses some limitations in complete evaluation of the astronaut's capabilities in a three-dimensional environment. Advances in computer hardware and software have provided for three-dimensional design and implementation of hardware with the advance of computer aided design (CAD) software. There are a number of CAD products available and most companies and agencies have adopted CAD as a fundamental aspect of the design process. Another factor which supports the use of CAD is the implementation of computer aided manufacturing (CAM) software and hardware which provides for rapid prototyping and decreases the time to product in the design process. It is probable that most hardware to be accessed by astronauts in EVA or IVA (intravehicular activity) has been designed by a CAD system, and is therefore represented in three-dimensional space for evaluation. Because of the implementation of CAD systems and the movement towards early prototyping, a need has arisen in industry and government for tools which facilitate the evaluation of ergonomic consideration in a three-dimensional environment where the hardware has been designed by the CAD tools. One such product is Jack which was developed by the University of Pennsylvania with funding from several government agencies, including NASA. While the primary purpose of Jack is to model human figures in a ground-based (gravity) environment, it can be utilized to evaluate EVA-suited activities as well. The effects of simulated gravity must be turned off by turning off "behaviors". Although Jack provides human figures for manipulation, the primary instrument to be evaluated for EVA mobility is the work envelope provided by the EVA suit. An EVA Jack suit model has been developed by NASA-JSC and was utilized in this study. This suit model provided a more restrictive motion environment as expected for an EVA suited subject. As part of this study, the anthropometric dimensions for a 50th percentile male were compared with basic anthropometric data and were found to be representative for the population group expected in the NASA flight program. The joints for the suit were created in a manner which provided consistent performance with EVA reach envelopes published in NASA standard #3000.

Etter, Brad↗

NASA NTRS2016

Serious Gaming for Test & Evaluation of Clean-Slate (Ab Initio) National Airspace System (NAS) Designs

Incremental approaches to air transportation system development inherit current architectural constraints, which, in turn, place hard bounds on system capacity, efficiency of performance, and complexity. To enable airspace operations of the future, a clean-slate (ab initio) airspace design(s) must be considered. This ab initio National Airspace System (NAS) must be capable of accommodating increased traffic density, a broader diversity of aircraft, and on-demand mobility. System and subsystem designs should scale to accommodate the inevitable demand for airspace services that include large numbers of autonomous Unmanned Aerial Vehicles and a paradigm shift in general aviation (e.g., personal air vehicles) in addition to more traditional aerial vehicles such as commercial jetliners and weather balloons. The complex and adaptive nature of ab initio designs for the future NAS requires new approaches to validation, adding a significant physical experimentation component to analytical and simulation tools. In addition to software modeling and simulation, the ability to exercise system solutions in a flight environment will be an essential aspect of validation. The NASA Langley Research Center (LaRC) Autonomy Incubator seeks to develop a flight simulation infrastructure for ab initio modeling and simulation that assumes no specific NAS architecture and models vehicle-to-vehicle behavior to examine interactions and emergent behaviors among hundreds of intelligent aerial agents exhibiting collaborative, cooperative, coordinative, selfish, and malicious behaviors. The air transportation system of the future will be a complex adaptive system (CAS) characterized by complex and sometimes unpredictable (or unpredicted) behaviors that result from temporal and spatial interactions among large numbers of participants. A CAS not only evolves with a changing environment and adapts to it, it is closely coupled to all systems that constitute the environment. Thus, the ecosystem that contains the system and other systems evolves with the CAS as well. The effects of the emerging adaptation and co-evolution are difficult to capture with only combined mathematical and computational experimentation. Therefore, an ab initio flight simulation environment must accommodate individual vehicles, groups of self-organizing vehicles, and large-scale infrastructure behavior. Inspired by Massively Multiplayer Online Role Playing Games (MMORPG) and Serious Gaming, the proposed ab initio simulation environment is similar to online gaming environments in which player participants interact with each other, affect their environment, and expect the simulation to persist and change regardless of any individual player's active participation.

Allen, B. Danette↗

DOE OSTI2020

Vulnerabilities in Artificial Intelligence and Machine Learning Applications and Data

Artificial intelligence (AI) applications driven by machine learning (ML) are transformational technologies within the international nuclear security regime. Advancements realized by AI—faster and improved data insights, more efficient and automated processes, reductions in human error—enable nuclear security applications such as behavior analysis for insider threat mitigation, source tracking of stolen nuclear material, and facial recognition software for physical protection. In addition to the advantages, however, there are also inherent vulnerabilities and threats associated with its use and risk mitigations must be built into any AI/ML-enabled systems. This work provides a background on AI and ML and different data types used in the field, including open-source intelligence information (OSINT) that is discoverable by AI tools and application data that are used by AI tools for decision-making and automation. Current and potential AI applications and vulnerabilities related to their use within the nuclear security regime are also discussed.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗