This report serves as a comprehensive summary of the work completed by the "Advanced WEC Dynamics and Controls projecr during the period of 2013-2019. This project was first envisioned to simply consider the question of designing a controller for wave energy converters (WECs), without a complete recognition of the broader considerations that such a task must necessarily examine. This document describes both the evolution of the project scope and the key findings produced. The basic goal of the project has been to deliver tractable methodologies and work flows that WEC designers can use to improve the performance of their machines. Engineering solutions, which may offer 80% of the impact, but require 20% of the effort compared to a perfect result (which may be many years of development down the road) were preferred. With this doctrine, the work of the project often involved translating existing methods that have been successfully developed and applied for other fields, into the application area of wave energy.
Legged robots promise radical mobility for challenging environments, but must be made more energy efficient to be practical. Historically, legged robot design has required efficiency to be traded against versatility. Much energy is lost in actuators and transmissions because few actuation systems are capable of operating efficiently across the wide range of operating conditions (e.g. different joint speeds and torques) required for legged locomotion. We describe a drivetrain topology that overcomes many of these limitations. Our approach combines high-torque electromagnetic motors and low-loss transmissions with a tailored and adjustable set of joint-specific passive mechanisms called support elements, which modulate the energy flow between motors and joints to minimize the electrical energy consumed. We present an optimization-based design method that draws on available bipedal gait data to select optimal support element configurations and parameters. Simple adjustments may be made to support elements at certain joints to enable a wide variety of locomotion with high efficiency. We present results, specific to the 3D humanoid bipedal STEPPR robot, in which support elements are co-optimized across a library of several gaits, converging on a set of designs that predict an average reduction of electrical energy of more than 50% across a set of 15 gaits, with energy savings reaching as much as 85% for some gaits. Concepts were prototyped and tested on a bench testbed, validating the predicted energy savings. Support elements were implemented on STEPPR, and energy savings of more than 35% were demonstrated.
The goal of this project is to produce an intense neutron pulse on HERMES III using the beam-target method with an intense proton beam. The potential advantage of proton use is that the generated neutron spectrum contains significantly more high-energy neutrons than that produced by electron-beam generated photoneutrons using the same facility. And compared to (D,T) facilities such as NIF, no tritium (or deuterium) is required for this process. To achieve the mid ~1010 neutrons/cm2 at a test object location listed as the goal in the Proposal, it was proposed that a radial ion diode previously developed and fielded at the 6 MeV - level be extended in performance to the full-power level on HERMES, with proton energies in the neighborhood of 15 MeV. This Report details the successful development of the radial ion diode at full power, which required more durable hardware which could be fielded at a one shot/day basis with minimal debris and activation (an important concern), and which could be substituted quickly into the normal negative-polarity bremsstrahlung source experiments without compromising the main HERMES validation mission. As direct measurement of proton beam characteristics proved challenging, the Project relied on an extensive series of simulations, LSP for beam dynamics and MCNP to characterize neutron output. Simulation results will be discussed, including the conclusion that neutron measurements made are consistent with an MCNP-predicted proton beam of 16 MeV peak energy, and 200 kA peak current. This Project also contributes to physics understanding of the use of inductive voltage adder (IVA) platforms to drive diode loads. Since such diodes operate independently of the physics of IVAs, the IVA-diode coupling requires matching of the MITL flow to the requirements of ion diode operation.
Unmanned aircraft systems (UASs) have grown significantly within the private sector with ease of acquisition and platform capabilities far outstretching what previously existed. Where once the operation of these platforms was limited to skilled individuals, increased computational power, manufacturing techniques, and increased autonomy allows inexperienced individuals to skillfully maneuver these devices. With this rise in consumer use of UAS comes an increased security concern regarding their use for malicious intent.The focus area of counter UAS (CUAS) remains a challenging space due to a small cross-sectioned UAS's ability to move in all three dimensions, attain very high speeds, carry payloads of notable weight, and avoid standard delay techniques.We examine frequency analysis of pixel fluctuation over time to exploit the temporal frequency signature present in UAS imagery. This signature allows for lower pixels-on-target detection [1]. The methodology also acts as a method of assessment due to the distinct frequency signatures of UAS when examined against the standard nuisance alarms such as birds. The temporal frequency analysis (TFA) method demonstrates a UAS detection and assessment method. In this paper we discuss signal processing and Fourier filter optimization methodologies that increase UAS contrast.
Conference Record - Asilomar Conference on Signals, Systems and Computers
Elkanishy, Abdelrahman; Badawy, Abdel H.A.; Boucheron, Laura E.; Michael, Christopher
Manufacturers often buy and/or license communication ICs from third-party suppliers. These communication ICs are then integrated into a complex computational system, resulting in a wide range of potential hardware-software security issues. This work proposes a compact supervisory circuit to classify the Bluetooth profile operation of a Bluetooth System-on-Chip (SoC) at low frequencies by monitoring the radio frequency (RF) output power of the Bluetooth SoC. The idea is to inexpensively manufacture an RF envelope detector to monitor the RF output power and a profile classification algorithm on a custom low-frequency integrated circuit in a low-cost legacy technology. When the supervisory circuit observes unexpected behavior, it can shut off power to the Bluetooth SoC. In this preliminary work, we proto-type the supervisory circuit using off-the-shelf components to collect a sufficient data set to train 11 different Machine Learning models. We extract smart descriptive time-domain features from the envelope of the RF output signal. Then, we train the machine learning models to classify three different Bluetooth operation profiles: sensor, hands-free, and headset. Our results demonstrate 100% classification accuracy with low computational complexity.∼
Few of those who read the 1963 research note by Graeme A. Bird in Physics of Fluids could have imagined that 50 years later the proposed new numerical technique would have become the dominant numerical technique in molecular gas dynamics. The introduction of the Direct Simulation Monte Carlo (DSMC) method not only has altered the field of molecular gas dynamics but also has influenced fields such as physical chemistry, mathematics, computer science, and aerothermodynamics. Further, the DSMC method has been used to probe into previously uninvestigated theoretical aspects of the Boltzmann equation and has also served as a platform for the development of nonequilibrium chemistry models. The DSMC method’s most noteworthy achievement is that molecular gas dynamics became a practical tool in the hands of aerospace engineers in many situations of spacecraft design and mission analysis.
An important part of a navigation system for a moving platform is the estimation of the rate of travel. This document presents a method for estimating the platform velocity in 3-dimensions using multiple antenna subarrays which could be used to augment navigation in a GPS-degraded environment. An advantage of this technique is that it does not require any knowledge of a positions of any landmarks. Results from radar data collected by the Sandia National Laboratories demonstration radar system are presented to illustrate the promise of this technique.
Fundamental results and an efficient algorithm for constructing eigenvectors corresponding to non-zero eigenvalues of matrices with zero rows and/or columns are developed. The formulation is based on the relation between eigenvectors of such matrices and the eigenvectors of their submatrices after removing all zero rows and columns. While being easily implemented, the algorithm decreases the computation time needed for numerical eigenanalysis, and resolves potential numerical eigensolver instabilities.
Wilks’ non-parametric method for setting tolerance limits using order statistics has recently become popular in the nuclear industry. The method allows analysts to predict a desired tolerance limit with some confidence that the estimate is conservative. The method is popular because it is simple and fits well into established regulatory frameworks. A critical analysis of the underlying statistics is presented in this work, including a derivation, analytical and statistical verification, and a broad discussion. Possible impacts of the underlying assumptions for application to computational tools are discussed. An in-depth discussion of the order statistic rank used in Wilks’ formula is provided, including when it might be necessary to use a higher rank estimate.
Obtaining information about burning characteristics and flame structures by analyzing experimental data is an important issue for understanding combustion processes and pursuing combustion modeling approaches. It has been shown that Raman/Rayleigh measurements of major species and temperature can be used to approximate the local heat release rate and the chemical explosive mode, and that these results are sufficiently accurate for a qualitative assessment of the relative importance of different heat release zones within the same overall flame structure in laminar and mildly turbulent partially premixed flames [1,2]. The present study uses data from direct numerical simulation (DNS) to extend and quantify the understanding of the approximation method with respect to premixed and stratified-premixed flames with significant turbulence–chemistry interaction (high Karlovitz number). The accuracy of the approximation procedure is assessed as previously applied, using just major species and temperature, as well as with the OH radical included as an additional experimentally accessible species. The accuracy of the local chemical explosive mode and the local heat release rate results from the approximation are significantly improved with OH included, yielding quantitative agreement with the DNS results. Further, a global sensitivity analysis is applied to identify the sensitivity of the heat release rate and chemical explosive mode to experimental uncertainties imprinted upon the DNS data prior to the approximation procedure.
A hierarchical solver is proposed for solving sparse ill-conditioned linear systems in parallel. The solver is based on a modification of the LoRaSp method, but employs a deferred-compression technique, which provably reduces the approximation error and significantly improves efficiency. Moreover, the deferred-compression technique introduces minimal overhead and does not affect parallelism. As a result, the new solver achieves linear computational complexity under mild assumptions and excellent parallel scalability. To demonstrate the performance of the new solver, we focus on applying it to solve sparse linear systems arising from ice sheet modeling. The strong anisotropic phenomena associated with the thin structure of ice sheets creates serious challenges for existing solvers. To address the anisotropy, we additionally developed a customized partitioning scheme for the solver, which captures the strong-coupling direction accurately. In general, the partitioning can be computed algebraically with existing software packages, and thus the new solver is generalizable for solving other sparse linear systems. Our results show that ice sheet problems of about 300 million degrees of freedom have been solved in just a few minutes using 1024 processors.
Proceedings of PAW-ATM 2019: Parallel Applications Workshop, Alternatives to MPI+X, Held in conjunction with SC 2019: The International Conference for High Performance Computing, Networking, Storage and Analysis
Pei, Yu; Bosilca, George; Yamazaki, Ichitaro; Ida, Akihiro; Dongarra, Jack
To minimize data movement, many parallel ap-plications statically distribute computational tasks among the processes. However, modern simulations often encounters ir-regular computational tasks whose computational loads change dynamically at runtime or are data dependent. As a result, load imbalance among the processes at each step of simulation is a natural situation that must be dealt with at the programming level. The de facto parallel programming approach, flat MPI (one process per core), is hardly suitable to manage the lack of balance, imposing significant idle time on the simulation as processes have to wait for the slowest process at each step of simulation. One critical application for many domains is the LU factor-ization of a large dense matrix stored in the Block Low-Rank (BLR) format. Using the low-rank format can significantly reduce the cost of factorization in many scientific applications, including the boundary element analysis of electrostatic field. However, the partitioning of the matrix based on underlying geometry leads to different sizes of the matrix blocks whose numerical ranks change at each step of factorization, leading to the load imbalance among the processes at each step of factorization. We use BLR LU factorization as a test case to study the programmability and performance of five different programming approaches: (1) flat MPI, (2) Adaptive MPI (Charm++), (3) MPI + OpenMP, (4) parameterized task graph (PTG), and (5) dynamic task discovery (DTD). The last two versions use a task-based paradigm to express the algorithm; we rely on the PaRSEC run-time system to execute the tasks. We first point out programming features needed to efficiently solve this category of problems, hinting at possible alternatives to the MPI+X programming paradigm. We then evaluate the programmability of the different approaches, detailing our experience implementing the algorithm using each of the models. Finally, we show the performance result on the Intel Haswell-based Bridges system at the Pittsburgh Supercomputing Center (PSC) and analyze the effectiveness of the implementations to address the load imbalance.
The following discussion contains a detailed description of how to interface and operate Radiation Effects Sciences (RES) Data Acquisition v1.0.0 software application. It describes the input required to run the application and actions to take for troubleshooting.
This is the first in a series of three papers documenting two large-scale human reliability analysis (HRA) empirical studies – the International HRA Empirical Study and the US HRA Empirical Study. The two studies are the first major efforts in recent years to benchmark HRA methods by comparing HRA method predictions against actual operator performance in responding to accidents simulated on nuclear power plant (NPP) full-scale simulators. The studies aimed to gain knowledge and insights concerning the strengths and weaknesses of the studied HRA methods and the factors contributing to inter-analyst (or intra-method) variability. In addition, the studies also compared the results of the same HRA method applied by different analysis teams. This paper provides the background and motivation of the studies, the overall study design, the simulation scenarios and human failure events to be analyzed, and concluding remarks concerning lessons learned on benchmarking HRA methods with crew performance of scenarios on NPP simulators.
Personnel at Sandia National Laboratories (hereinafter referred to as Sandia) comply with United States Department of Energy (DOE) Policy 450.4A, Chg 1, Integrated Safety Management Policy, and implement an Integrated Safety Management System (ISMS) to ensure safe operations. Sandia personnel integrate safety into management and work practices at all levels so missions are accomplished while protecting Members of the Workforce, the public, and the environment. As a result, safety is effectively integrated into all facets of work planning and execution. Thus the management of safety functions becomes an integral part of mission accomplishment and meets the requirements outlined in the DOE Acquisition Regulation (DEAR) 970.5223-1, Integration of Environment, Safety, and Health into Work Planning and Execution, clause incorporated by reference into the Prime Contract. The DEAR 970.5223-1, Integration of Environment, Safety, and Health into Work Planning and Execution, clause requires DOE contractors to manage and perform work in accordance with a documented Safety Management System that fulfills conditions of the DEAR clause at a minimum. For purposes of this clause, safety encompasses environment, safety, and health (ES&H), including pollution prevention and waste minimization.
This is the last in a series of three papers documenting two large-scale human reliability analysis (HRA) empirical studies – the International HRA Empirical Study and the US HRA Empirical Study. The goal of the two studies was to develop an empirically-based understanding of the performance, strengths, and weaknesses of HRA methods by comparing HRA method predictions against actual operator performance in simulated accident scenarios on nuclear power plant (NPP) simulators. This paper first addresses areas where there is convergence between the two studies and where differences lie. Then it summarizes the combined insights and conclusions, including key findings on HRA in general through lessons learned about the HRA methods assessed in the studies and specific recommendations for improving guidance, practice and methods. Then it discusses the relevance and usefulness of simulator data for HRA in general. Finally, it presents the key achievements and overall conclusions of the two studies taken together.
It has been widely believed that crystalline TlBr can surpass CdZnTe to become the leading semiconductor for γ- and X- radiation detection. The major hurdle to this transition is the rapid aging of TlBr under the operating electrical field. Here, while ionic migration of vacancies has been traditionally the root cause for property degradation, quantum mechanical calculations indicated that the vacancy concentration needed to cause the observed aging must be orders of magnitude higher than the usual theoretical estimate. Recent molecular dynamics simulations and X-ray diffract ion experiments have shown that electrical fields can drive the motion of edge dislocations in both slip and climb directions. Furthermore, these combined motions eject a large number of vacancies. Both dislocation mot ion and vacancy ejection can account for the rapid aging of the TlBr detectors. Based on these new discoveries, the present work applies molecular dynamics simulations to “develop” aging-resistant TlBr crystals by inhibiting dislocation motions.
Islam, Zahabul; Paoletta, Angela L.; Monterrosa, Anthony M.; Schuler, Jennifer D.; Rupert, Timothy J.; Hattar, Khalid M.; Glavin, Nicholas; Haque, Aman
We investigate the effects of ion irradiation on AlGaN/GaN high electron mobility electron transistors using in-situ transmission electron microscopy. The experiments are performed inside the microscope to visualize the defects, microstructure and interfaces of ion irradiated transistors during operation and failure. Experimental results indicate that heavy ions such as Au4+ can create a significant number of defects such as vacancies, interstitials and dislocations in the device layer. It is hypothesized that these defects act as charge traps in the device layer and the resulting charge accumulation lowers the breakdown voltage. Sequential energy dispersive X-ray spectroscopy mapping allows us to track individual chemical elements during the experiment, and the results suggest that the electrical degradation in the device layer may originate from oxygen and nitrogen vacancies.
We statistically infer fluid flow and transport properties of porous materials based on their geometry and connectivity, without the need for detailed We summarize structure by persistent homology and then determines the similarity of structures using image analysis and statistics. Longer term, this may enable quick and automated categorization of rocks into known archetypes. We first compute persistent homology of binarized 3D images of material subvolume samples. The persistence parameter is the signed Euclidean distance from inferred material interfaces, which captures the distribution of sizes of pores and grains. Each persistence diagram is converted into an image vector. We infer structural similarity by calculating image similarity. For each image vector, we compute principal components to extract features. We fit statistical models to features estimates material permeability, tortuosity, and anisotropy. We develop a Structural SIMilarity index to determine statistical representative elementary volumes.
In practical applications of automated terrain classification from high-resolution polarimetric synthetic aperture radar (PolSAR) imagery, different terrain types may inherently contain a high level of internal variability, as when a broadly defined class (e.g., 'trees') contains elements arising from multiple subclasses (pine, oak, and willow). In addition, real-world factors such as the time of year of a collection, the moisture content of the scene, the imaging geometry, and the radar system parameters can all increase the variability observed within each class. Such variability challenges the ability of classifiers to maintain a high level of sensitivity in recognizing diverse elements that are within-class, without sacrificing their selectivity in rejecting out-of-class elements. In an effort to gauge the degree to which classifiers respond robustly in the presence of intraclass variability and generalize to untrained scenes and conditions, we compare the performance of a suite of classifiers across six broad terrain categories from a large set of polarimetric synthetic aperture radar (PolSAR) image sets. The main contributions of this article are as follows: 1) an analysis of the robustness of a variety of current state-of-the art classification algorithms to intraclass variability found in PolSAR image sets, and 2) the associated PolSAR image and feature data that Sandia is releasing to the research community with this publication. The analysis of the classification algorithms we provide will serve as a benchmark of performance for the future PolSAR terrain classification algorithm research and development enabled by the image sets and data provided. By sharing our analysis and high-resolution fully polarimetric Sandia data with the research community, we enable others to develop and assess a new generation of robust terrain classification algorithms for PolSAR.
Pennington, Heather M.; Kraus, Terrence D.; Tenney, Craig M.; Faucett, Christopher; Brooks, Dusty
Nuclear fission produces more than 1,000 radioactive isotopes, each having different half-lives and producing unique characteristic emissions (e.g., alpha, beta, gamma), which makes it challenging to quickly and accurately assess radiological impacts resulting from sabotage (e.g., atmospheric transport, projected dose). Since many of the radionuclides produced by nuclear fission contribute an insignificant dose compared to other radionuclides, identifying the top dose-producing radionuclides will accelerate and simplify radiological assessments of research and test reactor releases. Here, we identify the fission radionuclides that contribute significant dose, enabling assessors to conduct consistent, simple, rapid and accurate radiological assessments.