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Overview of LaRC's Comprehensive Digital Transformation strategy. Includes foundational items such as modeling & simulation, big data analytics, high performance computing, and advanced information technology. Builds upon the foundation to recommend advanced "virtual capabilities," such as a virtual flight test capability to complement flight testing and wind tunnels.
Currently, the US Government is going through a large-scale data Transformation effort, where the GSA playbook is guiding all agencies to make their processes data-driven with the help of emerging technologies. To address concerns about algorithm sharing, AI adoption, and vendor lock-in, the NASA Langley Research Center Digital Transformation Group has developed the Environment for Data Engineering in Virtual Reality (EnDEVR), a data science ecosystem that allows users to command and investigate customizable data analyses from a VR environment. The system has been evaluated in the Oculus Rift S and Quest environments, two popular VR systems powered by the ARM architecture. Current and future development will employ several AI capabilities to guide research and automation within the environment and to facilitate algorithm sharing. In this talk, we will discuss the results of an initial ethical investigation and recommended considerations for the use of AI within the system.
We take for granted that the advances in technology bring improvements to the conditions in which humans perform activities associated to them. Is that the case for digital alarm systems in nuclear power plants? The answer is not that simple. A review of the related literature, shows that still, the single most significant problem with alarm systems, is the large number of alarm messages presented to the operator at once. This is an issue that affects analog I and C control rooms with conventional annunciators and gets aggravated in digital I and C based control rooms. Digital alarm systems present the alarms in the form of lists in computer screens. This kind of presentation forces the operator to scroll or navigate pages to review the active alarms. Also, the alarm lists do not allow the operator to apply the pattern recognition practices acquired during training when using with fixed position alarm systems. An Alarm Processing and Diagnostic System (APDS) facilitates the alarm monitoring task by applying alarm reduction techniques based on alarm priorities. It allows the operators to focus on the most important alarms during plant upsets. A new generation of APDS should be based in an improved alarm analysis methodology. To develop such methodology, Tecnatom reviewed applicable standards and our own alarm analysis experiences. This paper documents the process and conclusions of the methodology development. (authors)
Nuclear Energy is one of the most possible alternative to fossil energy in large-scale. Nuclear safety is the lifeline of nuclear energy development, and has been an important part of national security, especially after the accident of Fukushima. On the basis of computer codes, reliability engineering and Probabilistic Risk Assessment (PSA) is effective methods to improve the safety of nuclear power plants. After many years of development, the methodologies, applications and relevant soft programs have been quite sufficient in the area of nuclear safety. However, it is still difficult for the current PSA technologies and software to meet the needs of dealing with the problems of quantitatively public risk assessment in the digital society. Especially, there are so many software that adopted different modeling and analyzing methods, which brings difficulties to the comparison, evaluation or verification for different software and models. By using its own academic advantages, the advanced nuclear energy research team, i.e., FDS Team has invested a few hundreds person-years of independent research and development of a reliability and probabilistic safety assessment software system RiskA. The system consists of three main functions: device reliability optimization management, probabilistic safety assessment and instantaneous risk monitoring, and the comprehensive public risk assessment in digital society. RiskA establishes an integrated risk evaluation system for the device reliability, nuclear power plant (NPP) risk monitoring and public risk assessment. Currently, RiskA has successfully been applied in more than 600 organizations and institutes from a variety of fields in 39 countries, involving nuclear, aerospace, defense and so on. For example, RiskA has been used in the safety analysis of International Thermonuclear Experimental Reactor (ITER), FDS series fusion reactor, and the Strategic Priority Research Program of Chinese Academy of Sciences 'the Future Advanced Nuclear Fission Energy - Accelerator Driven Sub-critical (ADS) transmutation system'. Also, RiskA has been used in public risk communication and risk assessment. Among them, Third Qinshan nuclear power plant Risk Monitor (TQRM), which is the China's first domestic nuclear safety analysis software used in the actual online operation, has been highly apprised by renowned experts in the field. Meanwhile, it has been identified as the first domestic nuclear power plant risk monitoring system with completely independent intellectual property rights, and has reached the international advanced level. (authors)
SAND2021-15057 O This code demonstrates server/client authentication using the patented Digital Unclonable Function (DUF) process and protocol. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.
Many types of detectors like stilbene, NE-213 etc. in conjunction with photomultiplier loaded with low working resistance produce pulses of approximately 100 ns length and contain information about deposited particle in the trailing edge. Using fast analog to digital converters (ADC) and field-programmable gate array (FPGA) it is possible to create a spectrometric system working in mixed gamma and neutron fields which is not loaded dead time. The count rate of processed pulses can reach more than one million per second. Such a high count rate of processed pulses can be achieved due to the pulse processing is implemented in FPGA. The output of this pulse processing is amplitude which describes the energy of deposited particle and discrimination parameter whereby it is possible to discriminate photons and neutrons. To increase the dynamic range of energy of detectable particle the signal from photomultiplier is separated into two branches with different amplification. Each branch is digitalized by separate ADC. Components from which the system is composed are so light that the spectrometer can be easily transported. Its weight is less than 3 kilograms. Spectrometer was tested in the research reactor LR-0 in Rez near Prague (Czech Republic). The measured data was processed using deconvolution into a neutron flux density and compared with nowadays used analog spectrometer and simulation result. Measured neutron spectrum of Cf-252 is included. (authors)
Purpose: Alpha-emitting radionuclides exhibit a potential advantage for cancer treatments because they release large amounts of ionizing energy over a few cell diameters (50–80 μm), causing localized, irreparable double-strand DNA breaks that lead to cell death. Radioimmunotherapy (RIT) approaches using monoclonal antibodies labeled with α emitters may thus inactivate targeted cells with minimal radiation damage to surrounding tissues. Tools are needed to visualize and quantify the radioactivity distribution and absorbed doses to targeted and nontargeted cells for accurate dosimetry of all treatment regimens utilizing α particles, including RIT and others (e.g., Ra-223), especially for organs and tumors with heterogeneous radionuclide distributions. The aim of this study was to evaluate and characterize a novel single-particle digital autoradiography imager, the ionizing-radiation quantum imaging detector (iQID) camera, for use in α-RIT experiments. Methods: The iQID camera is a scintillator-based radiation detection system that images and identifies charged-particle and gamma-ray/x-ray emissions spatially and temporally on an event-by-event basis. It employs CCD-CMOS cameras and high-performance computing hardware for real-time imaging and activity quantification of tissue sections, approaching cellular resolutions. In this work, the authors evaluated its characteristics for α-particle imaging, including measurements of intrinsic detector spatial resolutions and background count rates at various detector configurations and quantification of activity distributions. The technique was assessed for quantitative imaging of astatine-211 ({sup 211}At) activity distributions in cryosections of murine and canine tissue samples. Results: The highest spatial resolution was measured at ∼20 μm full width at half maximum and the α-particle background was measured at a rate as low as (2.6 ± 0.5) × 10{sup −4} cpm/cm{sup 2} (40 mm diameter detector area). Simultaneous imaging of multiple tissue sections was performed using a large-area iQID configuration (ø 11.5 cm). Estimation of the {sup 211}At activity distribution was demonstrated at mBq/μg-levels. Conclusions: Single-particle digital autoradiography of α emitters has advantages over traditional film-based autoradiographic techniques that use phosphor screens, in terms of spatial resolution, sensitivity, and activity quantification capability. The system features and characterization results presented in this study show that the iQID is a promising technology for microdosimetry, because it provides necessary information for interpreting alpha-RIT outcomes and for predicting the therapeutic efficacy of cell-targeted approaches using α emitters.
This is the final report for this project that was performed in the period: October1, 2009 to June 30, 2013. In this project, a fully distributed high-fidelity dynamic state estimator (DSE) that continuously tracks the real time dynamic model of a wide area system with update rates better than 60 times per second is achieved. The proposed technology is based on GPS-synchronized measurements but also utilizes data from all available Intelligent Electronic Devices in the system (numerical relays, digital fault recorders, digital meters, etc.). The distributed state estimator provides the real time model of the system not only the voltage phasors. The proposed system provides the infrastructure for a variety of applications and two very important applications (a) a high fidelity generating unit parameters estimation and (b) an energy function based transient stability monitoring of a wide area electric power system with predictive capability. Also the dynamic distributed state estimation results are stored (the storage scheme includes data and coincidental model) enabling an automatic reconstruction and “play back” of a system wide disturbance. This approach enables complete play back capability with fidelity equal to that of real time with the advantage of “playing back” at a user selected speed. The proposed technologies were developed and tested in the lab during the first 18 months of the project and then demonstrated on two actual systems, the USVI Water and Power Administration system and the New York Power Authority’s Blenheim-Gilboa pumped hydro plant in the last 18 months of the project. The four main thrusts of this project, mentioned above, are extremely important to the industry. The DSE with the achieved update rates (more than 60 times per second) provides a superior solution to the “grid visibility” question. The generator parameter identification method fills an important and practical need of the industry. The “energy function” based transient stability monitoring opens up new ways to protect the power grid, better manage disturbances, confine their impact and in general improve the reliability and security of the system. Finally, as a by-product of the proposed research project, the developed system is able to “play back” disturbances by a click of a mouse. The importance of this by-product is evident by considering the tremendous effort exerted after the August 2003 blackout to piece together all the disturbance recordings, align them and recreate the sequence of events. This project has moved the state of art from fault recording by individual devices to system wide disturbance recording with “play back” capability.
Cancer exhibits substantial heterogeneity, manifesting as distinct morphological and molecular variations across tumors, which frequently undermines the efficacy of conventional oncological treatments. Developments in multiomics and sequencing technologies have paved the way for unraveling this heterogeneity. Nevertheless, the complexity of the data gathered from these methods cannot be fully interpreted through multimodal data analysis alone. Mathematical modeling plays a crucial role in delineating the underlying mechanisms to explain sources of heterogeneity using patient-specific data. Intra-tumoral diversity necessitates the development of precision oncology therapies utilizing multiphysics, multiscale mathematical models for cancer. This review discusses recent advancements in computational methodologies for precision oncology, highlighting the potential of cancer digital twins to enhance patient-specific decision-making in clinical settings. We review computational efforts in building patient-informed cellular and tissue-level models for cancer and propose a computational framework that utilizes agent-based modeling as an effective conduit to integrate cancer systems models that encode signaling at the cellular scale with digital twin models that predict tissue-level response in a tumor microenvironment customized to patient information. Furthermore, we discuss machine learning approaches to building surrogates for these complex mathematical models. These surrogates can potentially be used to conduct sensitivity analysis, verification, validation, and uncertainty quantification, which is especially important for tumor studies due to their dynamic nature.
The digital time-resolved spot diagnostic (D-TRSD) is intended to be a fast-response, time-dependent beam diagnostic for measuring the spot size emitted from radiographic x-ray sources. It will measure spot sizes from submillimeters up to several millimeters for photon energies in the range of 150 keV to 20 MeV with doses as low as 0.03 rad up to 500 rad. The D-TRSD performs fast data acquisition as radiographic x-ray sources typically produce pulses in the tens of nanosecond ranges. The system will be optimized to capture multiple individual pulses in time within the same data record. The data collected will be used to support beam tuning and source optimization with on-the-fly evaluation of radiographic source performance. The diagnostic is based on penumbral imaging techniques. A scintillating fiber array of parallel aligned fibers is positioned in the beam path with a high-Z rolled edge inserted between the source and the array, thereby creating the penumbral x-ray signal that is captured by the D-TRSD system. The light from the scintillation conversion is recorded by individual avalanche photodiode detectors integrated into custom digitizer electronics. The penumbra is used to calculate the spot of the beam on the axis orthogonal to the fiber array based on the magnification from the rolled edge, the resolution of the spaced fibers, and the rotation of the array normal to the beam path. Many arrays can be used to capture additional spot widths about different rotations. The D-TRSD system is modular, software-driven, and easier to use than legacy TRSD systems.
This is the second quarter of the third and final year of this project. Much of this quarter was taken up with completing and submitting the comprehensive paper and the hardware paper for publication, as well as working out some of the intellectual property issues for working with the pulse digitizer company, Struck.
The mechanism, effects, and modelling of multipath propagation, caused by rough earth reflection, are examined for aerospace communication. Emphasis is on binary digital signalling for aircraft and hybrid vehicles, such as Shuttle. The cases of direct Air-Ground and satellite relay (Aerosat) are treated. The recursive, adaptive, coherent Bayes detector for binary phase-shift-keying in nonselective multipath is presented. The derivation for the frequency-shift-keying detector is indicated.
To address the concern for cellular phone electromagnetic interference to aircraft radios, a radiated emission measurement process was developed for two dominant digital standards of wireless handsets. Spurious radiated emissions were efficiently characterized from devices tested in either a semi-anechoic or reverberation chamber, in terms of effective radiated power. Eight representative handsets (four from each digital standard) were commanded to operate while varying their radio transmitter parameters (power, modulation, etc.). This report provides a detailed description of the measurement process and resulting data, which may subsequently be used by others as a basis of consistent evaluation of other portable transmitters using a variety of wireless transmission protocols. Aircraft interference path loss and navigation radio interference threshold data from numerous reference documents, standards, and NASA partnerships were compiled. Using these data, a preliminary risk assessment is provided for wireless phone interference to aircraft Localizer, Glideslope, Very High Frequency Omni directional Range, and Global Positioning Satellite radio receivers on typical transport airplanes. The report identifies where existing data for device emissions, interference path loss, and navigation radio interference thresholds need to be extended for an accurate risk assessment for wireless transmitters in aircraft.
Digital Information Platform Sub-Project under ATM-X is having a virtual information session to share response summary for the Request for Information (Notice ID: NARC21DIP-RFI). The purpose of this session is to share the valuable inputs from the RFI responses on data & service needs for airspace operations, recommended use cases for DIP collaborative demos, and potential data and technology services that can be provided by the DIP platform through NASA-industry collaboration.
This study focused on developing a robust artificial intelligence (AI) model capable of detecting and characterizing advanced malware in Internet of Things (IoT) devices using network data. By analyzing network traffic with various machine learning (ML) models, our AI model can identify and characterize malicious activities to significantly improve malware detection accuracy and reliability as compared to traditional methods. The developed AI/ML model was trained using network data from IoT devices, leveraging classifiers such as Random Forest, Gradient Boosting, AdaBoost, and others to optimize detection performance. This project demonstrates a scalable framework for real-time malware detection and characterization in IoT networks, capable of identifying infected devices and facilitating the necessary steps to remove or isolate them, thereby preventing further infections. Although digital twin (DT) integration is not yet implemented in the current model, it represents a promising future enhancement. By creating a virtual replica of physical IoT devices, DT technology would allow for real-time monitoring and analysis without directly accessing operational technology, thus reducing the risk of compromising or reducing the performance of actual devices. This integration would further enhance the security of IoT ecosystems, combining AI technology to better flag and detect indications of malware-infected devices within a nuclear system environment.
TRADITIONAL TECHNIQUES OT/IT Concepts Operational Technology (OT) and Information Technology (IT) concepts can often be difficult to visualize Teaching Methods Traditional teaching methods lack the intuitive & immersive aspects of hands-on activities Caveat: Unless taught by Team B! Physical Limitations Digital Twins require existing systems/hardware to mirror UPDATED TECHNIQUES Virtual Environment By making use of a virtual environment, we can represent abstract concepts in a more approachable and digestible way Increased Engagement Students are more engaged with the activities and are more likely to retain the information they are given. New/Emerging Technologies As the system is currently growing and developing, the technologies in use, as well as those represented by the system, stay up-to-date.
The goal of the project was to develop a compact, large active area, high spatial resolution, high dynamic range, charge-coupled device (CCD) camera to replace film for digital imaging of visible light, ultraviolet radiation, and soft to penetrating X-rays. The camera head and controller needed to be capable of operation within a vacuum environment and small enough to be fielded within the small vacuum target chambers at LLNL.