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NASA NTRSDate not supplied

A Survey of Autonomous Navigation Techniques Applicable to Lunar Surface Exploration

As humanity returns to the Moon, and more and more attention is being paid to lunar surface operations, there is a greater need than ever for methods of surface navigation. These could be methods of computer-assisted orienteering for astronauts exploring on foot during an Extra-Vehicular Activity (EVA), or methods of solving the Lost-on-the-Moon problem to initialize a crewed or autonomous rover’s state estimate. It may also be necessary to process navigation data associated with surface samples or other surface operations a posteriori to better understand where that analysis occurred. Autonomous rover operation will also require Hazard Detection and Avoidance (HDA) and terrain-aware pathfinding. While navigation on the surface of the Moon will likely rely on Earth-based assets such as the Deep Space Network (DSN) or communication with other spacecraft (e.g., LunaNet, LCRNS, pre-deployed moon beacons, a nearby lander) it may be necessary to navigate in a loss-of-communication scenario. This paper analyzes the methods of surface navigation used on other celestial bodies, such as those used during the Apollo missions and autonomous exploration of Mars, as well as novel methods which have been studied but not yet implemented which may prove useful. It is shown that the navigator has myriad options when processing data from an Inertial Measurement Unit (IMU), a star tracker, (rover) wheel encoders, optical cameras, and LIght Detection and Ranging (LIDAR) sensors. The intention of this paper is to provide a broad overview of what has been done and what could be done, to aid those designing vehicles and/or missions to the lunar surface.

Paul McKee↗
DOE OSTI2013

Direct-Reaction Studies by Particle-Gamma Coincidence Spectroscopy Using HPGe-CsI and HPGe-Si Arrays

Particle- and particle- - coincidence spectroscopy has several advantages in the study of direct reactions(particularly in inverse kinematics) since it can generally allow determination of: decay paths; high-precision level energies; multipolarities of transitions; and cross sections. Techniques for studying direct reactions by particle- coincidence spectroscopy are presented for two cases: (1) heavy-ion reactions with HPGe-CsI, and (2) light-ion reactions with HPGe-Si. Future direct-reaction studies with radioactive ion beams (RIBs) will mostly involve low beam intensities and inverse kinematics (i.e., Abeam>Atarget), which eliminates the traditional use of magnetic spectrometers. Particle- coincidence spectroscopy currently provides the most viable method to study direct reactions with nuclei of any level density. In the present study, the capabilities and limitations of the technique are explored.

Allmond, James M↗
DOE OSTI2013

Adaptive Sampling Algorithms for Probabilistic Risk Assessment of Nuclear Simulations

Nuclear simulations are often computationally expensive, time-consuming, and high-dimensional with respect to the number of input parameters. Thus exploring the space of all possible simulation outcomes is infeasible using finite computing resources. During simulation-based probabilistic risk analysis, it is important to discover the relationship between a potentially large number of input parameters and the output of a simulation using as few simulation trials as possible. This is a typical context for performing adaptive sampling where a few observations are obtained from the simulation, a surrogate model is built to represent the simulation space, and new samples are selected based on the model constructed. The surrogate model is then updated based on the simulation results of the sampled points. In this way, we attempt to gain the most information possible with a small number of carefully selected sampled points, limiting the number of expensive trials needed to understand features of the simulation space. We analyze the specific use case of identifying the limit surface, i.e., the boundaries in the simulation space between system failure and system success. In this study, we explore several techniques for adaptively sampling the parameter space in order to reconstruct the limit surface. We focus on several adaptive sampling schemes. First, we seek to learn a global model of the entire simulation space using prediction models or neighborhood graphs and extract the limit surface as an iso-surface of the global model. Second, we estimate the limit surface by sampling in the neighborhood of the current estimate based on topological segmentations obtained locally. Our techniques draw inspirations from topological structure known as the Morse-Smale complex. We highlight the advantages and disadvantages of using a global prediction model versus local topological view of the simulation space, comparing several different strategies for adaptive sampling in both contexts. One of the most interesting models we propose attempt to marry the two by obtaining a coarse global representation using prediction models, and a detailed local representation based on topology. Our methods are validated on several analytical test functions as well as a small nuclear simulation dataset modeled after a simplified Pressurized Water Reactor.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

Using Models to Provide Predicted Ranges for Building-Human Interfaces: Preprint

Most building energy consumption dashboards provide only a snapshot of building performance; whereas some provide more detailed historic data with which to compare current usage. This paper will discuss the Building Agent(tm) platform, which has been developed and deployed in a campus setting at the National Renewable Energy Laboratory as part of an effort to maintain the aggressive energyperformance achieved in newly constructed office buildings and laboratories. The Building Agent(tm) provides aggregated and coherent access to building data, including electric energy, thermal energy, temperatures, humidity, and lighting levels, and occupant feedback, which are displayed in various manners for visitors, building occupants, facility managers, and researchers. This paper focuseson the development of visualizations for facility managers, or an energy performance assurance role, where metered data are used to generate models that provide live predicted ranges of building performance by end use. These predicted ranges provide simple, visual context for displayed performance data without requiring users to also assess historical information or trends. Several energymodelling techniques were explored including static lookup-based performance targets, reduced-order models derived from historical data using main effect variables such as solar radiance for lighting performance, and integrated energy models using a whole-building energy simulation program.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Data-Driven Operator Theoretic Methods for Global Phase Space Learning

In this work, we propose to apply the recently developed Koopman operator techniques to explore the global phase space of a nonlinear system from time-series data. In particular, we address the problem of identifying various invariant subsets of a phase space from the spectral properties of the associated Koopman operator constructed from time-series data. Moreover, in the case when the system evolution is known locally in various invariant subspaces, then a phase space stitching result is proposed that can be applied to identify a global Koopman operator. A biological system, bistable toggle switch and a second-order nonlinear system example are considered to illustrate the proposed results. The construction of this global Koopman operator is very helpful in experimental works as multiple experiments can't be run at the same time starting from several initial conditions.

Nandanoori, Sai Pushpak↗
DOE OSTI2022

Search For Excited Cascade Hypersons (¿*-) Using the CLAS12 Spectrometer at Jefferson Laboratory

The number of experimentally observed doubly strange Cascade states to date is far fewer than has been predicted theoretically. The CLAS12 Very Strange physics program (E12- 11-005A) at the Thomas Jefferson National Accelerator Facility aims to study the electroproduction of these states using the newly upgraded CEBAF Large Acceptance Spectrometer for 12 GeV (CLAS12) in experimental Hall B. In this project, the reaction ep ! e0K+K+??? ! e0K+K+K?(?=?0) is studied using CLAS12 Run Group A (RG-A) data sets taken by impinging electron beams of 10:2 and 10:6 GeV energies on an LH2 target. Scattered electrons are detected with either the Forward Detector (FD), covering a polar angle range of 5? to 35? to study electroproduction, or with the Forward Tagger (FT), covering a polar angle range of 2:5? to 4:5?, to study quasi-real photoproduction. The CLAS12 detector with nearly a 4? solid angle coverage is used to detect scattered electrons and charged kaons in the ?final state. ?=?0 hyperons are reconstructed using the missing mass technique to explore intermediate doubly-strange hyperons (???) that decay to K? and ?=?0. No statistically significant ??? states other than the ???(1530) were found in the missing mass spectra based on the currently available statistics in the CLAS12-FD acceptance only. A maximum log-likelihood method is implemented to determine the statistical significance and the upper limits on the ???(1820) electroproduction cross section by constructing 95% confidence level boundaries on the ???(1820) yields. Additional research was conducted to investigate the upper limit electroproduction cross section of the reaction ep ! e0K+K+??? ! e0K+K+K?(?=?0) as a function of the electroproduced ??? mass and the differential cross section ( d?dMM(e0K+K+) ) as a function of missing mass MM(e0K+K+) for electroproduction and quasi-real photoproduction processes.

Khanal, Achyut↗
DOE OSTI2024

Trends in Cybersecurity Threats to Clean Energy

As deployments of clean energy generation and storage assets continue to grow, the increased attack surface creates a greater risk for cyber threats, but is clean energy truly a target for cyber adversaries? This poster will present research on the trends in cyber incidents that have affected clean energy companies and assets as well as the trends in disclosed and exploited vulnerabilities. From a series of ransomware attacks on European wind manufacturers, to vulnerabilities exploited in solar assets to turn controllers into botnets, to attacks on communication infrastructure that have resulted in extended outages of remote control and monitoring, we explore the techniques used and the impacts to the clean energy sector. Key takeaways include understanding of how OT-focused malware is becoming more flexible and more destructive, how known vulnerabilities are being exploited, the growing number of IT and OT attacks that use built in tools and functionalities. Additionally, we highlight the presumed motivations and targeted sectors for various identified cyber adversaries. Viewers will leave with an understanding of how recent headlines fit into the development of cyberattack trends and what preventions they may need to take to protect against increasingly popular tactics.

14 SOLAR ENERGY↗
DOE OSTI2024

A Simulation Modeling Approach to Optimizing Nuclear Waste Dispositioning

The dispositioning of nuclear waste generated at facilities across the country is an ongoing battle that affects us all. National laboratories and research centers dealing in medical research, clean energy, and other nuclear activities such as the Department of Energy (DOE) facilities face the need to properly manage and dispose of nuclear waste. A dynamic modeling solution would enable the DOE and others to make decisions on waste disposal and technological options. In doing so, this research explores modeling techniques using available data to address these situations. The focus being on developing an initial robust and adaptable discrete event model using the ExtendSim tool. This modeling effort will target the dispositioning of transuranic waste at the Savannah River National Laboratory (SRNL) which can be expanded to represent the current state of disposition process for waste generated at other DOE facilities. The model aims to assess resource allocation and waste processing options to stabilize productivity and cut the backlog of nuclear waste. By assessing the results of different scenarios, this research aims to provide actionable insights for the DOE. This approach has the potential to significantly improve the management of radioactive waste, offering the capability of evaluating options for optimizing the process for nuclear waste disposal. The findings of this study can serve as a valuable resource for decision-makers and other national laboratories, or research entities engaged in nuclear operations by enabling them to make more informed choices.

Andaverde, Alexis↗
DOE OSTI2024

Backend Nuclear Fuel Cycle Radiation Chemistry

Given global commitments to significantly increase nuclear energy capacity, it is now more important than ever to develop efficient used nuclear fuel management strategies to improve resource utilization, energy security, and waste minimization. Here, an overview of nuclear energy, backend fuel cycle challenges, and advances in used nuclear fuel reprocessing radiation chemistry will be presented. More specifically, the use of electron pulse irradiation techniques to explore radiation-induced reaction mechanisms in actinide containing solutions and solvent systems.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2022

A survey on processing-in-memory techniques: Advances and challenges

Processing-in-memory (PIM) techniques have gained much attention from computer architecture researchers, and significant research effort has been invested in exploring and developing such techniques. Increasing the research activity dedicated to improving PIM techniques will hopefully help deliver PIM’s promise to solve or significantly reduce memory access bottleneck problems for memory-intensive applications. We also believe it is imperative to track the advances made in PIM research to identify open challenges and enable the research community to make informed decisions and adjust future research directions. In this survey, we analyze recent studies that explored PIM techniques, summarize the advances made, compare recent PIM architectures, and identify target application domains and suitable memory technologies. We also discuss proposals that address unresolved issues of PIM designs (e.g., address translation/mapping of operands, workload analysis to identify application segments that can be accelerated with PIM, OS/runtime support, and coherency issues that must be resolved to incorporate PIM). We believe this work can serve as a useful reference for researchers exploring PIM techniques.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1977

Application of standard photogeologic techniques to LANDSAT imagery for mineral exploration in the basin and range province of Utah and Nevada

The author has identified the following significant results. Standard photogeologic techniques were applied to LANDSAT imagery of the basin and range province of Utah and Nevada to relate linear, tonal, textural, drainage, and geomorphic features to known mineralized areas in an attempt to develop criteria for the location of mineral deposits. No consistent correlation was found between lineaments, mapped according to specified criteria, and locations of mines, mining districts, or intrusive outcrops. Tonal and textural patterns were more closely related to geologic outcrop patterns than to mineralization. A statistical study of drainage azimuths of various length classes as measured on LANDSAT showed significant correlation with mineralized districts in the length class of 3-6 km. Alignments of outcrops of basalt, a rock type highly visible on LANDSAT imagery, appear to be colinear with acidic and intermediate intrusive centers in some areas and may assist on the recognition of regional fracture systems for mineral exploration.

Lattman, L. H.↗
NASA NTRS1986

Flight control synthesis for flexible aircraft using Eigenspace assignment

The use of eigenspace assignment techniques to synthesize flight control systems for flexible aircraft is explored. Eigenspace assignment techniques are used to achieve a specified desired eigenspace, chosen to yield desirable system impulse residue magnitudes for selected system responses. Two of these are investigated. The first directly determines constant measurement feedback gains that will yield a close-loop system eigenspace close to a desired eigenspace. The second technique selects quadratic weighting matrices in a linear quadratic control synthesis that will asymptotically yield the close-loop achievable eigenspace. Finally, the possibility of using either of these techniques with state estimation is explored. Application of the methods to synthesize integrated flight-control and structural-mode-control laws for a large flexible aircraft is demonstrated and results discussed. Eigenspace selection criteria based on design goals are discussed, and for the study case it would appear that a desirable eigenspace can be obtained. In addition, the importance of state-space selection is noted along with problems with reduced-order measurement feedback. Since the full-state control laws may be implemented with dynamic compensation (state estimation), the use of reduced-order measurement feedback is less desirable. This is especially true since no change in the transient response from the pilot's input results if state estimation is used appropriately. The potential is also noted for high actuator bandwidth requirements if the linear quadratic synthesis approach is utilized. Even with the actuator pole location selected, a problem with unmodeled modes is noted due to high bandwidth. Some suggestions for future research include investigating how to choose an eigenspace that will achieve certain desired dynamics and stability robustness, determining how the choice of measurements effects synthesis results, and exploring how the phase relationships between desired eigenvector elements effects the synthesis results.

Davidson, J. B.↗
DOE OSTI2014

SU-C-BRD-05: Implementation of Incident Learning in the Safety and Quality Management of Radiotherapy: The Primary Experience in a New Established Program with Advanced Techniques

Purpose: To explore the implementation and effectiveness of incident learning for the safety and quality of radiotherapy in a new established radiotherapy program with advanced technology. Methods: Reference to the consensus recommendations by American Association of Physicist in Medicine, an incident learning system was specifically designed for reporting, investigating, and learning of individual radiotherapy incidents in a new established radiotherapy program, with 4D CBCT, Ultrasound guided radiotherapy, VMAT, gated treatment delivered on two new installed linacs. The incidents occurring in external beam radiotherapy from February, 2012 to January, 2014 were reported. Results: A total of 33 reports were analyzed, including 28 near misses and 5 incidents. Among them, 5 originated in imaging for planning, 25 in planning, 1 in plan transfer, 1 in commissioning and 1 in treatment delivery. Among them, three near misses originated in the safety barrier of the radiotherapy process. In terms of error type, 1 incident was classified as wrong patient, 7 near misses/incidents as wrong site, 6 as wrong laterality, 5 as wrong dose, 7 as wrong prescription, and 7 as suboptimal plan quality. 5 incidents were all classified as grade 1/2 of dosimetric severity, 1 as grade 0, and the other 4 as grade 1 of medical severity. For the causes/contributory factors, negligence, policy not followed, inadequate training, failure to develop an effective plan, and communication contributed to 19, 15, 12, 5 and 3 near misses/incidents, respectively. The average incident rate per 100 patients treated was 0.4; this rate fell to 0.28% in the second year from 0.56% in the first year. The rate of near miss fell to 1.24% from 2.22%. Conclusion: Effective incident learning can reduce the occurrence of near miss/incidents, enhance the culture of safety. Incident learning is an effective proactive method for improving the quality and safety of radiotherapy.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2017

Review of X-ray Tomography and X-ray Fluorescence Spectroscopy

This literature review will focus on both laboratory and synchrotron based X-ray tomography of materials and highlight the inner workings of these instruments. X-ray fluorescence spectroscopy will also be reviewed and applications of the tandem use of these techniques will be explored. The real world application of these techniques during the internship will also be discussed.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1986

Assessment of pilot workload - Converging measures from performance based, subjective and psychophysiological techniques

This study explores the relationship between the P300 component of the event-related brain potential (ERP) and the processing demands of a complex real-world task. Seven male volunteers enrolled in an Instrument Flight Rule (IFR) aviation course flew a series of missions in a single engine fixed-based simulator. In dual task conditions subjects were also required to discriminate between two tones differing in frequency. ERPs time-locked to the tones, subjective effort ratings and overt performance measures were collected during two 45 min flights differing in difficulty (manipulated by varying both atmospheric conditions and instrument reliability). The more difficult flight was associated with poorer performance, increased subjective effort ratings, and smaller secondary task P300s. Within each flight, P300 amplitude was negatively correlated with deviations from command headings indicating that P300 amplitude was a sensitive workload metric both between and within the flight missions.

Kramer, Arthur F.↗
DOE OSTI2024

From oxide epitaxy to freestanding membranes: Opportunities and challenges

Motivated by the growing demand to integrate functional oxides with dissimilar materials, numerous studies have been undertaken to detach a functional oxide film from its original substrate, effectively forming a membrane, which can then be affixed to the desired host material. This review article is centered on the synthesis of functional oxide membranes, encompassing various approaches to their synthesis, exfoliation, and transfer techniques. First, we explore the characteristics of thin-film growth techniques with emphasis on molecular beam epitaxy. We then examine the fundamental principles and pivotal factors underlying three key approaches of creating membranes: (i) chemical lift-off, (ii) the two-dimensional layer–assisted lift-off, and (iii) spalling. We review the methods of exfoliation and transfer for each approach. Last, we provide an outlook into the future of oxide membranes, highlighting their applications and emerging properties.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Machine Learning for Improved Availability of the SNS Klystron High Voltage Converter Modulators

Beam availability has increased at the SNS, however, the targeted availability is greater than 95 %, while the SNS has failed to meet lower targets in the past. The HVCM used to power the linac klystrons have been one source of lost beam time and was chosen to explore using AI/ML techniques to improve reliability. Among the possibilities being explored are automating the tuning of HVCMs and predicting component failures such as capacitor aging, rectifier assemblies containing hundreds of diodes, and insulating oil degradation. The methodology pursued includes data cleaning, de-noising, post-analysis data labeling, and machine learning model development. We explore using Long Short-Term Memory and autoencoders for anomaly detection and prognostication used to schedule maintenance. We evaluate the use of model regularizers and constraints to improve the performance of the model and investigate methods to estimate the uncertainty of the models to provide a robust prediction with statistical interoperability. This paper describes the operational experience and known failures of the HVCMs and the proposed ML methodology and the preliminary results of training the AI/ML algorithms.

Pappas, G. C.↗