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This presentation provides an overview of de-risking the field deployment of controller and power hardware technologies.
Abstract The Idaho National Laboratory (INL) has implemented laboratory-based micro-X-ray computed tomography in a laboratory equipped for the examination of highly radioactive samples. This capability provides nondestructive three-dimensional volumetric information on samples to inform subsequent traditional destructive examinations as well as real-world inputs for high-fidelity scientific modeling. Samples can be imaged with spatial resolutions ranging from several hundred nm/voxel up to ~ 100 µm/voxel. The best usable spatial resolution achieved to date is 384 nm/voxel with this instrument, while the highest radiological dose rate of a sample imaged is ~ 60 R/h β/γ on contact. Advanced data analysis, including custom tomographic reconstruction and segmentation methods, have also been developed to support this capability. In addition to traditional digital X-ray radiography and tomography, this instrument is also able to visualize in situ tensile and compression testing as well as perform diffraction contrast tomography. This work describes the X-ray computed tomography post-irradiation examination capabilities at INL, as well as detailing a variety of applications this instrument has examined.
Abstract Metastasis is the leading cause of death in patients with cancer, driving considerable scientific and clinical interest in immunosurveillance of micrometastases. We investigated this process by creating a multiscale mathematical model to study the interactions between the immune system and the progression of micrometastases in general epithelial tissue. We analyzed the parameter space of the model using high-throughput computing resources to generate over 100,000 virtual patient trajectories. We demonstrated that the model could recapitulate a wide variety of virtual patient trajectories, including uncontrolled growth, partial response, and complete immune response to tumor growth. We classified the virtual patients and identified key patient parameters with the greatest effect on the simulated immunosurveillance. We highlight the lessons derived from this analysis and their impact on the nascent field of cancer patient digital twins (CPDTs). While CPDTs could enable clinicians to systematically dissect the complexity of cancer in each individual patient and inform treatment choices, our work shows that key challenges remain before we can reach this vision. In particular, we show that there remain considerable uncertainties in immune responses, unreliable patient stratification, and unpredictable personalized treatment. Nonetheless, we also show that in spite of these challenges, patient-specific models suggest strategies to increase control of clinically undetectable micrometastases even without complete parameter certainty.
Systems and methods performed for generating authentication information for an image using optical computing are provided. When a user takes a photo of an object, an optical authentication system receives light reflected and/or emitted from the object. The system also receives a random key from an authentication server. The system converts the received light to plenoptic data and uploads it to the authentication server. In addition, the system generates an optical hash of the received light using the random key, converts the generated optical hash to a digital optical hash, and uploads the digital optical hash to the authentication server. When the authentication server receives the upload, it verifies whether the time of the upload is within a certain threshold time from the sending of the random key and whether the digital optical hash was generated from the same light as the plenoptic data.
Purpose: To develop a method for improving sharpness of images reproduced on liquid-crystal displays (LCDs) by compensating for the degradation of modulation transfer function (MTF) of the LCD. Methods: The inherent MTF of a color LCD (display MTF) was measured using a commercially available color digital camera. The frequency responses necessary to compensate for the resolution property of the LCD were calculated from the inverses of the display MTFs in both the horizontal and vertical directions. In addition, the inverses of the display MTFs were combined with the response of the human eye. The finite impulse response (FIR) filters were computed by taking the inverse Fourier transform of the frequency responses, and the effects of the FIR filtering on both the resolution and noise properties of the displayed images were verified by measuring the MTF and Wiener spectrum (WS), respectively. The FIR filtering was then applied to the representation of digital bone and chest radiographs. Results: The FIR filtering improved the MTF values by up to almost 1.0 or greater over the frequency range of interest, while it minimally increased the WS values. Combining the inverses of the display MTFs with the response of the human eye led to further refinement of the MTF. Our method was successfully and beneficially applied to the image interpretation of bone radiographs. The resolution enhancement of chest radiographs, which include larger scattered radiation than bone radiographs, was easily perceived by incorporating the response of the human eye. In addition, no artifacts were observed on the processed images. Conclusion: Our proposed method to compensate for the degradation of the resolution properties of LCDs has the potential to improve the observer performance of radiologists when reading digital radiographs. This work was supported in part by grant from EIZO Corporation.
Predicting the mechanical behavior of the chopped carbon fiber Sheet Molding Compound (SMC) due to spatial variations in local material properties is critical for the structural performance analysis but is computationally challenging. Such spatial variations are induced by the material flow in the compression molding process. In this work, a new multiscale SMC modeling framework and the associated computational techniques are developed to provide accurate and efficient predictions of SMC mechanical performance. The proposed multiscale modeling framework contains three modules. First, a stochastic algorithm for 3D chip-packing reconstruction is developed to efficiently generate the SMC mesoscale Representative Volume Element (RVE) model for Finite Element Analysis (FEA). A new fiber orientation tensor recovery function is embedded in the reconstruction algorithm to match reconstructions with the target characteristics of fiber orientation distribution. Second, a metamodeling module is established to improve the computational efficiency by creating the surrogates of mesoscale analyses. Third, the macroscale behaviors are predicted by an efficient multiscale model, in which the spatially varying material properties are obtained based on the local fiber orientation tensors. Our approach is further validated through experiments at both meso- and macro-scales, such as tensile tests assisted by Digital Image Correlation (DIC) and mesostructure imaging.
Transmission of information using ultrasonic elastic waves on existing metallic pipes provides an alternative communication option across physical barriers in a highly partitioned industrial complex, such as a nuclear facility. This work investigates the feasibility of the transmission of digital images over metallic pipes. Ultrasonic communication systems for transmission of images on a nuclear-grade stainless steel pipe were assembled for bench-scale demonstration. Information carriers in this system are refracted shear waves transmitted and received with piezoelectric transducers (PZTs) operating at 2-MHz nominal frequency. The refraction and propagation of ultrasonic shear waves were modeled with COMSOL software. An amplitude shift keying (ASK) communication protocol for image transmission was developed and implemented in the GNURadio software-defined radio (SDR) environment. Digital information was converted to analog ultrasonic signals using Red Pitaya electronic boards. The performance of the ASK protocol is evaluated at the output of every block in the GNURadio program by monitoring the transmission of select characters. Using the ASK communication protocol, the transmission of the 32-KB image was demonstrated at 2-Kbps bitrate across 6-ft-long stainless steel pipe. Finally, preliminary evaluation of ultrasonic communication on the piping of a nuclear facility, such as signal transmission on bent pipes, was performed with COMSOL computer simulations.
Quantum computers are believed to have the ability to process huge data sizes, which can be seen in machine learning applications. In these applications, the data, in general, are classical. Therefore, to process them on a quantum computer, there is a need for efficient methods that can be used to map classical data on quantum states in a concise manner. On the other hand, to verify the results of quantum computers and study quantum algorithms, we need to be able to approximate quantum operations into forms that are easier to simulate on classical computers with some errors. Motivated by these needs, in this paper, we study the approximation of matrices and vectors by using their tensor products obtained through successive Schmidt decompositions. We show that data with distributions such as uniform, Poisson, exponential, or similar to these distributions can be approximated by using only a few terms, which can be easily mapped onto quantum circuits. The examples include random data with different distributions, the Gram matrices of iris flower, handwritten digits, 20newsgroup, and labeled faces in the wild. Similarly, some quantum operations, such as quantum Fourier transform and variational quantum circuits with a small depth, may also be approximated with a few terms that are easier to simulate on classical computers. Furthermore, we show how the method can be used to simplify quantum Hamiltonians: In particular, we show the application to randomly generated transverse field Ising model Hamiltonians. The reduced Hamiltonians can be mapped into quantum circuits easily and, therefore, can be simulated more efficiently.
The political push to increase power generation from renewable sources such as solar energy requires knowing the best places to site new solar power plants with respect to the applicable regulatory, operational, engineering, environmental, and socioeconomic criteria. Therefore, in this paper, we present applications of remote sensing data for mapping suitability areas for concentrated solar power plants. Our approach uses digital elevation model derived from NASA s Shuttle Radar Topographic Mission (SRTM) at a resolution of 3 arc second (approx. 90m resolution) for estimating global solar radiation for the study area. Then, we develop a computational model built on a Geographic Information System (GIS) platform that divides the study area into a grid of cells and estimates site suitability value for each cell by computing a list of metrics based on applicable siting requirements using GIS data. The computed metrics include population density, solar energy potential, federal lands, and hazardous facilities. Overall, some 30 GIS data are used to compute eight metrics. The site suitability value for each cell is computed as an algebraic sum of all metrics for the cell with the assumption that all metrics have equal weight. Finally, we color each cell according to its suitability value. Furthermore, we present results for concentrated solar power that drives a stream turbine and parabolic mirror connected to a Stirling Engine.
Mitigation of the intense heat flux to the divertor is one of the outstanding problems in fusion energy. One technique that has shown promise is impurity seeding, i.e., the injection of low-Z gaseous impurities (typically N 2 or Ne) to radiate and dissipate the power before it arrives to the divertor target plate. To this end, the Alcator C-Mod team has created a first-of-its-kind feedback system to control the injection of seed gas based on real-time surface heat flux measurements. Surface thermocouples provide real-time measurements of the surface temperature response to the plasma heat flux. The surface temperature measurements are inputted into an analog computer that “solves” the 1-D heat transport equation to deliver accurate, real-time signals of the surface heat flux. The surface heat flux signals are sent to the C-Mod digital plasma control system, which uses a proportional–integral–derivative (PID) algorithm to control the duty cycle demand to a pulse width modulated piezo valve, which in turn controls the injection of gas into the private flux region of the C-Mod divertor. This paper presents the design and implementation of this new feedback system as well as initial results using it to control divertor heat flux.
The new standard ISO 17636–2:2013 “NDT of welds: Radiographic testing - Part 2: X- and gamma ray techniques with digital detectors” describes a complex procedure for film replacement by phosphor imaging plates and digital detector arrays. RT modeling software should consider these detector types, X-ray film, and the standard requirements for image quality. Practitioners expect the same visibility of image quality indicators (IQI) in the simulated radiographs as in the experimental exposures. The proposed benchmark test is based on the comparison of experimental radiographs taken at BAM with modeled ones of participants. The experimental setup and the determination of the equivalent penetrameter sensitivity (EPS) as described in the procedure of ASTM E 746 are used for quantitative evaluation of the achievable contrast sensitivity for step hole IQIs as considered in Annex B of ISO 17636–2. System classification data for Computed Radiography (CR) and film systems will be provided by BAM according to ISO 11699–1 for selected film systems and according to ASTM E 2446 for selected CR systems. The classification of films and digital detectors is based on the measurement of the dose response function, the basic spatial resolution (SR{sub b}) of the image, and the measured image noise, which depends on the detector efficiency, the quantum statistics, and the detector fixed pattern noise.
Recent research and development in exploiting quantum phenomenon have solidified the creation of large-scale quantum computers as a reality. These machines will have the ability to solve intractable problems defined on conventional computers. This has a significant impact on current cryptographic systems. A viable quantum computer will require an increase in symmetric key sizes and the replacement of asymmetric cryptographic schemes. Specifically, new constructs for public key cryptosystems must be established in order to continue to ensure the security that digital signatures and key exchange protocols provide. Understanding the post-quantum landscape is critical to applying Sandia-developed capabilities to post-quantum cyber areas. Developing a cohort of experts in this challenging and volatile space has enabled our ability to adapt to the new challenges in various customer mission areas.
Under the Department of Energy’s Light Water Reactor Sustainability Program, within the Plant Modernization research pathway, the Digital I&C Qualification Project is identifying new methods that would be beneficial in qualifying digital I&C systems and devices for safety-related usage. One such method that would be useful in qualifying field components such as sensors and actuators is the concept of testability. The Nuclear Regulatory Commission (NRC) considers testability to be one of two design attributes sufficient to eliminate consideration of software-based or software logic-based common cause failure (the other being diversity). The NRC defines acceptable “testability” as follows: Testability – A system is sufficiently simple such that every possible combination of inputs and every possible sequence of device states are tested and all outputs are verified for every case (100% tested). [NUREG 0800, Chapter 7, Branch Technical Position (BTP) 7-19] This qualification method has never proven to be practical in view of the very large number of combinations of inputs and sequences of device states for a typical I&C device. However, many of these combinations are not unique in the sense that they represent the same state space or in that that they represent state space that would not affect the critical design basis functions of the device. Therefore, the state space of interest might possibly be reduced to a manageable dimension through such analysis. This project will focus on a representative I&C device similar in design, function, and complexity to the types of devices that would likely be deployed in nuclear power plants as digital or software based sensors and actuators (e.g. Smart Sensors). Analysis will be conducted to determine the feasibility of testing this device in a manner consistent with the NRC definition. This report describes the development of test process for Bounded Exhaustive Testing with respect to Combinatorial Test (CT) methods. The report describes the candidate Device Under Test SW – the VCU smart sensor, conceptual experimental methods for stated test objectives, description of the process, tools, resources, and computing. This information will be used to fully develop a detailed test plan (based on statistical measure needs) and test environment for conducting an I&C device testability demonstration study. The future planed experimental study of this project is to demonstrate digital qualification via Bounded Exhaustive Testability with respect to Common Cause Failure.
Cooperative Computing implemented as Cooperative Computing System (CCS) in grid has been proved a considerably reliable technique to execute the tasks with real time constraints in a grid environment. This technique can be applied in many high performance distributed computing applications. HPC has a large number of applications in various fields of physics. One such application in radiation physics is X-ray tomography. X-Ray tomography contains numerous applications in various fields of science, technology and research. As the technology is changing from analog to digital in almost all the scenarios, this paper presents an idea towards the attachment of X-ray tomography assembly to HPC environment so as to obtain the highly reliable optimization.
Electronic synaptic devices are important building blocks for neuromorphic computational systems that can go beyond the constraints of von Neumann architecture. Although two-terminal memristive devices are demonstrated to be possible candidates, they suffer from several shortcomings related to the filament formation mechanism including nonlinear switching, write noise, and high device conductance, all of which limit the accuracy and energy efficiency. Electrochemical three-terminal transistors, in which the channel conductance can be tuned without filament formation provide an alternative platform for synaptic electronics. In this work, an all-solid-state electrochemical transistor made with Li ion–based solid dielectric and 2D α-phase molybdenum oxide (α-MoO 3 ) nanosheets as the channel is demonstrated. These devices achieve nonvolatile conductance modulation in an ultralow conductance regime (<75 nS) by reversible intercalation of Li ions into the α-MoO 3 lattice. Based on this operating mechanism, the essential functionalities of synapses, such as short- and long-term synaptic plasticity and bidirectional near-linear analog weight update are demonstrated. Simulations using the handwritten digit data sets demonstrate high recognition accuracy (94.1%) of the synaptic transistor arrays. These results provide an insight into the application of 2D oxides for large-scale, energy-efficient neuromorphic computing networks.
The field of nuclear instrumentation covers a wide range of applications, including counting, spectrometry, pulse shape discrimination and multi-channel coincidence. These applications are the topic of many researches, new algorithms and implementations are constantly proposed thanks to advances in digital signal processing. However, these improvements are not yet implemented in instrumentation devices. This is especially true for neutron-gamma discrimination applications which traditionally use charge comparison method while literature proposes other algorithms based on frequency domain or wavelet theory which show better performances. Another example is pileups which are generally rejected while pileup correction algorithms also exist. These processes are traditionally performed offline due to two issues. The first is the Poissonian characteristic of the signal, composed of random arrival pulses which requires to current architectures to work in data flow. The second is the real-time requirement, which implies losing pulses when the pulse rate is too high. Despite the possibility of treating the pulses independently from each other, current architectures paralyze the acquisition of the signal during the processing of a pulse. This loss is called dead-time. These two issues have led current architectures to use dedicated solutions based on re-configurable components like Field Programmable Gate Arrays (FPGAs) to overcome the need of performance necessary to deal with dead-time. However, dedicated hardware algorithm implementations on re-configurable technologies are complex and time-consuming. For all these reasons, a programmable Digital pulse Processing (DPP) architecture in a high level language such as Cor C++ which can reduce dead-time would be worthwhile for nuclear instrumentation. This would reduce prototyping and test duration by reducing the level of hardware expertise to implement new algorithms. However, today's programmable solutions do not meet the need of performance to operate online and not allow scaling with the increase in the number of measurement channel. That is why an innovative DPP architecture is proposed in this paper. This architecture is able to overcome dead-time while being programmable and is flexible with the number of measurement channel. Proposed architecture is based on an innovative execution model for pulse processing applications which can be summarized as follow. The signal is not composed of pulses only, consequently, pulses processing does not have to operate on the entire signal. Therefore, the first step of our proposal is pulse extraction by the use of dedicated components named pulse extractors. The triggering step can be achieved after the analog-to-digital conversion without any signal shaping or filtering stages. Pileup detection and accurate pulse time stamping are done at this stage. Any application downstream this step can work on adaptive variable-sized array of samples simplifying pulse processing methods. Then, once the data flow is broken, it is possible to distribute pulses on Functional Units (FUs) which perform processing. As the date of each pulse is known, they can be processed individually out-of-order to provide the results. To manage the pulses distribution, a scheduler and an interconnection network are used. pulses are distributed on the first FU which is not busy without congesting the interconnection network. For this reason, the process duration does not result anymore in dead-time if there are enough FUs. FUs are designed to be standalone and to comprises at least a programmable general purpose processor (ARM, Microblaze) allowing the implementation of complex algorithms without any modification of the hardware. An acquisition chain is composed of a succession of algorithms which lead to organize our FUs as a software macro-pipeline, A simple approach consists in assigning one algorithm per FU. Consequently, the global latency becomes the worst latency of algorithms execution on FU. Moreover, as algorithms are executed locally - i.e. on a FU - this approach limits shared memory requirement. To handle multichannel, we propose FUs sharing, this approach maximize the chance to find a non-busy FU to process an incoming pulse. This is possible since each channel receive random event independently, the pulse extractors associated to them do not necessarily need to access simultaneously to all Computing resources at the same time to distribute their pulses. The major contribution of this paper is the proposition of an execution model and its associated hardware programmable architecture for digital pulse processing that can handle multiple acquisition channels while maintaining the scalability thanks to the use of shared resources. This execution model and associated architecture are validated by simulation of a cycle accurate architecture SystemC model. Proposed architecture shows promising results in terms of scalability while maintaining zero dead-time. This work also permit the sizing of hardware resources requirement required for a predefined set of applications. Future work will focus on the interconnection network and a scheduling policy that can exploit the variable-length of pulses. Then, the hardware implementation of this architecture will be performed and tested for a representative set of application.
Residual stresses induced in the layer-by-layer fabrication process of additively manufactured parts have significant impact on their mechanical properties and dimensional accuracy. This work aims here to characterize the residual stress and deformation in specimens based on unreinforced acrylonitrile-butadiene-styrene (ABS), carbon nanotube reinforced ABS and short carbon fiber reinforced ABS. The shrinkage and displacement fields were obtained, respectively, by thermal treatment as well as Digital Image Correlation observation of specimens before and after sectioning. The microstructure and porosity of additively manufactured specimens were also examined using X-ray micro-computed tomography. Specimen shrinkage and porosity content were significantly influenced by the process parameters of raster angle and printing speed, as well as material types. Faster printing speed led to larger porosity and residual stress, as well as higher shrinkage after specimen thermal treatment. Raster angle had a greater influence on specimen shrinkage and porosity as comparing to printing speed. Composite printing wires based on carbon nanotube and short carbon fiber in ABS greatly reduced specimen shrinkage and deformation, while increased the porosity, especially for carbon fiber reinforced ABS specimens.
Archaeological data and demographic modelling suggest that the peopling of Sahul required substantial populations, occurred rapidly within a few thousand years and encompassed environments ranging from hyper-arid deserts to temperate uplands and tropical rainforests. How this migration occurred and how humans responded to the physical environments they encountered have, however, remained largely speculative. By constructing a high-resolution digital elevation model for Sahul and coupling it with fine-scale viewshed analysis of landscape prominence, least-cost pedestrian travel modelling and high-performance computing, here we create over 125 billion potential migratory pathways, whereby the most parsimonious routes traversed emerge. Our analysis revealed several major pathways—superhighways—transecting the continent, that we evaluated using archaeological data. These results suggest that the earliest Australian ancestors adopted a set of fundamental rules shaped by physiological capacity, attraction to visually prominent landscape features and freshwater distribution to maximize survival, even without previous experience of the landscapes they encountered.