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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 253 records · Page 14

Brahman

The Adversary & Interdiction Methods (AIM) program provides training and capability assessment services to government agencies around the country. Interdisciplinary teams equipped with gear and radioactive sources are repeatedly fielded to offsite events to collaborate with law enforcement agencies at all levels of government. AIM has grown rapidly over the past three years. A knowledge management system as evolved along with the program but it has failed to keep pace. A new system is needed. The new system must comply with cybersecurity and information technology solutions already in place at an institutional level. The offsite nature of AIM activities must also be accommodated. Cost and schedule preclude the commissioning of new software and the procurement of expensive hardware. The new system must exploit in-house capabilities and be established quickly. A novel system is proposed. This solution centers on a recently introduced institutional file sharing capability called Syncplicity. AIM-authored software will be combined with a dedicated institutional account to vastly extend the capability of this resource. The new knowledge management system will reduce error and increase efficiency through automation and be accessible offsite via mobile devices.

42 ENGINEERING↗

Compact Models for Defect Diffusivity in Semiconductor Alloys.

Predicting transient effects caused by short - pulse neutron irradiation of electronic devices is an important part of Sandia's mission. For example , predicting the diffusion of radiation - induced point defects is needed with in Sandia's Qualification Alternative to the Sandia Pulsed Reactor (QASPR) pro gram since defect diffusion mediates transient gain recovery in QASPR electronic devices. Recently, the semiconductors used to fabricate radiation - hard electronic devices have begun to shift from silicon to III - V compounds such as GaAs, InAs , GaP and InP . An advantage of this shift is that it allows engineers to optimize the radiation hardness of electronic devices by using alloy s such as InGaAs and InGaP . However, the computer codes currently being used to simulate transient radiation effects in QASP R devices will need to be modified since they presume that defect properties (charge states, energy levels, and diffusivities) in these alloys do not change with time. This is not realistic since the energy and properties of a defect depend on the types of atoms near it and , therefore, on its location in the alloy. In particular, radiation - induced defects are created at nearly random locations in an alloy and the distribution of their local environments - and thus their energies and properties - evolves with time as the defects diffuse through the alloy . To incorporate these consequential effects into computer codes used to simulate transient radiation effects, we have developed procedures to accurately compute the time dependence of defect energies and properties and then formulate them within compact models that can be employed in these computer codes. In this document, we demonstrate these procedures for the case of the highly mobile P interstitial (I P ) in an InGaP alloy. Further dissemination only as authorized to U.S. Government agencies and their contractors; other requests shall be approved by the originating facility or higher DOE programmatic authority.

36 MATERIALS SCIENCE↗

Real-time GIS Programming and Geocomputation

Streaming data generated continuously from sensor networks, mobile devices, social media platforms and other edge devices have posed significant challenges to existing computing platforms for achieving both high throughput and low latency data processing in addition to scalable computing. This entry introduces a real-time computing and programming platform for time-critical GIS (Geographic Information System) applications. In this platform, advanced streaming data processing software, such as Apache Kafka and Spark Streaming, are integrated to enable data analytics in real-time. This computing platform can also be extended to integrate GeoAI (Geospatial Artificial Intelligence) based machine learning models to leverage both historical and streaming data to achieve real-time prediction and intelligent geospatial analytics. Two real-time geospatial applications in terms of flood simulation and climate data visualization are introduced to demonstrate how real-time programming and computing can help tackle real-world problems with important societal impacts.

Liu, Yan↗

Enhanced Lighting Signals for Safety and Efficiency - Experiments with Addressable LEDs

For enhanced roadway safety, clear and immediate visual cues are essential for preventing accidents between drivers and pedestrians. At intersections, however, the line of sight to other roadway users may be obstructed by vehicles and infrastructure. Additionally, adverse conditions, including low visibility, poor weather, or inadequate lighting can increase the potential for collisions. Distracted drivers and pedestrians can further exacerbate the risk of accidents, particularly when using a smartphone, rather than focusing on roadway surroundings. These issues demonstrate the need for infrastructure upgrades that enhance visibility and awareness at crosswalks. A potential solution is through enhanced lighting signals integrated into the roadway infrastructure. One such example is the use of addressable LEDs, individually controllable lights that can change color and brightness instantaneously through programmable microcontrollers. They can be installed and integrated into crosswalks to maintain visibility in conditions where pedestrians may be difficult to see, while also offering peripheral cues to pedestrians who may be distracted by their phones or other objects rather than the road. Such a system (as one example) that is integrated into a traffic intersection digital twin that tracks all roadway users accurately, has the potential to enhance visibility of vulnerable road users, and thus enhance safety. This paper examines the potential implementation and feasibility of this technology, as well as the safety benefits it could provide. Laboratory experiments with addressable LEDs reveal the capabilities and challenges of this technology for roadway infrastructure safety. These findings could pave the way for more integrated lighting in infrastructure for vehicles and pedestrians at intersections, merge and diverge locations, and other areas where complex interactions present safety hazards. Such lighting solutions, enabled by modern computation and communications, could enhance safety and efficiency in our transportation system and improve overall mobility.

24 POWER TRANSMISSION AND DISTRIBUTION↗

An Effective Collaborative Mobile Weighted Clustering Schemes for Energy Balancing in Wireless Sensor Networks

Collaborative strategies for mobile sensor nodes ensure the efficiency and the robustness of data processing, while limiting the required communication bandwidth. In order to solve the problem of pipeline inspection and oil leakage monitoring, a collaborative weighted mobile sensing scheme is proposed. By adopting a weighted mobile sensing scheme, the adaptive collaborative clustering protocol can realize an even distribution of energy load among the mobile sensor nodes in each round, and make the best use of battery energy. A detailed theoretical analysis and experimental results revealed that the proposed protocol is an energy efficient collaborative strategy such that the sensor nodes can communicate with a fusion center and produce high power gain.

42 ENGINEERING↗

Performance of a Kinetic Inductance Traveling-Wave Parametric Amplifier at 4 Kelvin: Toward an Alternative to Semiconductor Amplifiers

Most microwave readout architectures in quantum computing or sensing rely on a semiconductor amplifier at 4 K, typically a high-electron mobility transistor (HEMT). Despite its remarkable noise performance, a conventional HEMT dissipates several milliwatts of power, posing a practical challenge to scale up the number of qubits or sensors addressed in these architectures. As an alternative, we present an amplification chain consisting of a kinetic inductance traveling-wave parametric amplifier (KITWPA) placed at 4 K, followed by a HEMT placed at 70 K, and demonstrate a chain-added noise $T_Σ$ = 6.3 ± 0.5 K between 3.5 and 5.5 GHz. While, in principle, any parametric amplifier can be quantum limited even at 4 K, in practice we find the performance of the KITWPA to be limited by the temperature of its inputs and by an excess of noise $T_{ex}$ = 1.9 K. In this work, the dissipation of the rf pump of the KITWPA constitutes the main power load at 4 K and is about 1% that of a HEMT. These combined noise and power dissipation values pave the way for the use of the KITWPA as a replacement for semiconductor amplifiers.

97 MATHEMATICS AND COMPUTING↗

A Preprocessing Tool for Enhanced Ion Mobility–Mass Spectrometry-Based Omics Workflows

The ability to improve the data quality of ion mobility–mass spectrometry (IM-MS) measurements is of great importance for enabling modular and efficient computational workflows and gaining better qualitative and quantitative insights from complex biological and environmental samples. We developed the PNNL PreProcessor, a standalone and user-friendly software housing various algorithmic implementations to generate new MS-files with enhanced signal quality and in the same instrument format. Different experimental approaches are supported for IM-MS based on Drift-Tube (DT) and Structures for Lossless Ion Manipulations (SLIM), including liquid chromatography (LC) and infusion analyses. The algorithms extend the dynamic range of the detection system, while reducing file sizes for faster and memory-efficient downstream processing. Specifically, multidimensional smoothing improves peak shapes of poorly defined low-abundance signals, and saturation repair reconstructs the intensity profile of high-abundance peaks from various analyte types. Further, other functionalities are data compression and interpolation, IM demultiplexing, noise filtering by low intensity threshold and spike removal, and exporting of acquisition metadata. Several advantages of the tool are illustrated, including an increase of 19.4% in lipid annotations and a two-times faster processing of LC-DT IM-MS data-independent acquisition spectra from a complex lipid extract of a standard human plasma sample. The software is freely available at https://omics.pnl.gov/software/pnnl-preprocessor.

59 BASIC BIOLOGICAL SCIENCES↗

Results of Application Demonstration of Autonomous Offshore Power System Supporting Multiple Mobile and Static Assets

Over the last decade, several technology trends have dominated the innovation cycle within the terrestrial economy. Electrification, cloud computing, decarbonization, digitization, and autonomy are representative examples of macro trends that have had a rapid and fundamental impact; an impact felt not only in user-facing technologies, such as electric vehicles and software-as-a-service, but also in the infrastructure required to deliver those technologies. However, the scale of the impact and rollout has not been felt equally between the terrestrial and ocean economies. Here, the innovation cycle in the ocean economy is significantly slower. What accounts for the difference and are there solutions to this issue?

16 TIDAL AND WAVE POWER↗

Current Trends in the Detection of Sociocultural Signatures: Data-Driven Models

The harvesting of behavioral data and their analysis through evidence-based reasoning enable the detection of sociocultural signatures in their context to support situation awareness and decision making. Harvested data are used as training materials from which to infer computational models of sociocultural behaviors or calibrate parameters for such models. Harvested data also serve as evidence input that the models use to provide insights about observed and future behaviors for targets of interest. The harvested data is often the result of assembling diverse data types and aggregating them into a form suitable for analysis. Data need to be analyzed to bring out the categories of content that are relevant to the domain being addressed in order to train or run a model. If, for example, we are modeling the intent of a group to engage in violent behavior using messages that the group has broadcasted, then these messages need to be processed to extract and measure indicators of violent intent. The extracted indicators and the associated measurements (e.g. rates or counts of occurrence) can then be used to train/calibrate and run computational models that assess the propensity for violence expressed in the source message. Ubiquitous access to the Internet, mobile telephony and technologies such as digital photography and digital video have enabled social media application platforms such as Facebook, YouTube, and Twitter that are altering the nature of human social interaction. The fast increasing pace of online social interaction introduces new challenges and opportunities for gathering sociocultural data. Challenges include the development of harvesting and processing techniques tailored to new data environments and formats (e.g. Twitter, Facebook), the integration of social media content with traditional media content, and the protection of personal privacy. As these and other challenges are addressed, a new wealth of behavioral data and data analysis methods becomes available that are shaping social computing as a strongly data-driven experimental discipline with an increasingly stronger impact on the decision-making process of groups and individuals alike. In this chapter, we review current advances and trends in the detection of sociocultural signatures. Specific embodiments of the issues discussed are provided with respect to the assessment of violent intent and sociopolitical contention. We begin by reviewing current approaches to the detection of sociocultural signatures in these domains. Next, we turn to the review of novel data harvesting methods for social media content. Finally, we discuss the application of sociocultural models to social media content, and conclude by commenting on current challenges and future developments.

Sanfilippo, Antonio P.↗

Motion Planning Algorithms for Safety and Quantum Computing Efficiency

Motion planning remains a fundamental problem in robotics. Sampling-based algorithms use randomization to allow efficient solutions to this complex problem. As mobile robots and autonomous vehicles become more prevalent in everyday life, motion planning must be applied to increasingly challenging scenarios. Safety has become a paramount concern in motion planning for ensuring robotic applications enrich human lives. To date, many motion planning techniques to increase safety in the face of uncertain and dynamic environments have been developed. This dissertation first addresses distributional safety of Rapidly-Exploring Random Trees (RRT) through our algorithm W-Safe RRT. To acknowledge distributional uncertainty and poor modeling, W-Safe RRT uses the Wasserstein metric to provide a probabilistic bound on the distributional distance between a robot and obstacles. Human-interpretable environmental agent classification allows online safety margin adaptation. We propose and analyze an integrating region method for online classification that increases actor labeling accuracy based on behavioral feature values when compared to state of the art methods. The method performs class assignments based on local maximum likelihood in a created behavioral feature-space, allowing a notion of classification uncertainty. Model-based methods with safety guarantees can quickly become computationally in tractable, especially with multiple agents, higher dimensions, and plentiful unknowns. Sampling based algorithms have been parallelized for computation with multi-core computers and GPUs. We consider the use of quantum algorithms and computers for sampling-based motion planning for the first time. Quantum computing performs operations on superpositions of states and can solve certain problems much more efficiently than classical computers, but introduces previously unseen challenges. With Quantum-RRT, we recast the motion planning problem into a database-search structure and use Quantum Amplitude Amplification to find reachable states in the database with a quadratic performance increase over classical methods. We address two error sources with this method: quantum measurement and quantum oracle errors. We then extend this method to Parallel Quantum-RRT, which uses a manager-worker architecture with multiple parallel quantum workers to increase database search efficiency. We compare algorithm architectures and characterize probabilities of multiple workers finding solutions. Lastly, we test in simulation the quantum algorithms against classical versions in a wide variety of scenarios, concluding that a similar parallelization improvement is to be found in the quantum case as was found in the parallelization of classical RRT.

97 MATHEMATICS AND COMPUTING↗

Fluctuating Hydrodynamic Methods for Fluid-Structure Interactions in Confined Channel Geometries

Computational methods are developed for the study of fluid-structure interactions subject to thermal fluctuations when conned within channels having slit-like geometry. The methods take into account the hydrodynamic coupling and diusivity of microstructures when influenced by their proximity to no-slip walls. We develop stochastic numerical methods subject to no-slip boundary conditions using a staggered nite volume discretization. We show that by imposing an exact fluctuation-dissipation condition to discretize the stochastic driving elds combined with using an exact projection method to enforce incompressibility is sucient to ensure results consistent with statistical mechanics. We demonstrate our methods by investigating how the proximity of ellipsoidal colloids to the channel wall eects their active hydrodynamic responses and passive diusivity. We also study the collective dynamics of a large number of particles by considering the intermediate scattering functions for the relaxation of density fluctuations. We expect our introduced stochastic computational methods to be applicable broadly to applications in which confinement effects play an important role in the dynamics of microstructures subject to hydrodynamic coupling and thermal fluctuations. uctuations.

Wang, Yaohong↗

An image-guidance system for dynamic dose calculation in prostate brachytherapy using ultrasound and fluoroscopy

Purpose: Brachytherapy is a standard option of care for prostate cancer patients but may be improved by dynamic dose calculation based on localized seed positions. The American Brachytherapy Society states that the major current limitation of intraoperative treatment planning is the inability to localize the seeds in relation to the prostate. An image-guidance system was therefore developed to localize seeds for dynamic dose calculation. Methods: The proposed system is based on transrectal ultrasound (TRUS) and mobile C-arm fluoroscopy, while using a simple fiducial with seed-like markers to compute pose from the nonencoded C-arm. Three or more fluoroscopic images and an ultrasound volume are acquired and processed by a pipeline of algorithms: (1) seed segmentation, (2) fiducial detection with pose estimation, (3) seed matching with reconstruction, and (4) fluoroscopy-to-TRUS registration. Results: The system was evaluated on ten phantom cases, resulting in an overall mean error of 1.3 mm. The system was also tested on 37 patients and each algorithm was evaluated. Seed segmentation resulted in a 1% false negative rate and 2% false positive rate. Fiducial detection with pose estimation resulted in a 98% detection rate. Seed matching with reconstruction had a mean error of 0.4 mm. Fluoroscopy-to-TRUS registration had a mean error of 1.3 mm. Moreover, a comparison of dose calculations between the authors’ intraoperative method and an independent postoperative method shows a small difference of 7% and 2% forD{sub 90} and V{sub 100}, respectively. Finally, the system demonstrated the ability to detect cold spots and required a total processing time of approximately 1 min. Conclusions: The proposed image-guidance system is the first practical approach to dynamic dose calculation, outperforming earlier solutions in terms of robustness, ease of use, and functional completeness.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Initial clinical evaluation of PET-based ion beam therapy monitoring under consideration of organ motion

Purpose: Intrafractional organ motion imposes considerable challenges to scanned ion beam therapy and demands for a thorough verification of the applied treatment. At the Heidelberg Ion-Beam Therapy Center (HIT), the scanned ion beam delivery is verified by means of postirradiation positron-emission-tomography (PET) imaging. This work presents a first clinical evaluation of PET-based treatment monitoring in ion beam therapy under consideration of target motion. Methods: Three patients with mobile liver lesions underwent scanned carbon ion irradiation at HIT and postirradiation PET/CT (x-ray-computed-tomography) imaging with a commercial scanner. Respiratory motion was recorded during irradiation and subsequent image acquisition. This enabled a time-resolved (4D) calculation of the expected irradiation-induced activity pattern and, for one patient where an additional 4D CT was acquired at the PET/CT scanner after treatment, a motion-compensated PET image reconstruction. For the other patients, PET data were reconstructed statically. To verify the treatment, calculated prediction and reconstructed measurement were compared with a focus on the ion beam range. Results: Results in the current three patients suggest that for motion amplitudes in the order of 2 mm there is no benefit from incorporating respiratory motion information into PET-based treatment monitoring. For a target motion in the order of 10 mm, motion-related effects become more severe and a time-resolved modeling of the expected activity distribution can lead to an improved data interpretation if a sufficient number of true coincidences is detected. Benefits from motion-compensated PET image reconstruction could not be shown conclusively at the current stage. Conclusions: The feasibility of clinical PET-based treatment verification under consideration of organ motion has been shown for the first time. Improvements in noise-robust 4D PET image reconstruction are deemed necessary to enhance the clinical potential.

61 RADIATION PROTECTION AND DOSIMETRY↗

Taming the Wild World of Management, Performance and Communication - 13459

Management has evolved a long way from its original meaning of 'governing a horse'. The industrial revolution fostered 'scientific management'; 1930's Hawthorne studies discovered that people's social interactions could alter productivity; and the dawn of the computer age in the post-war 1950's brought general systems theory into management thinking. Today, mobile wireless connectivity aims to transform ever-changing networks of players, mandates, and markets into something that can be 'managed'. So why is there no clear and simple recipe for how to practice management? We talk about financial management, safety management, and operations management, but surely the 'management' part of those endeavors will share the same set of practices. Instead, we are still arguing for 'management' to include everything from developing people to negotiating contracts. A manager's job may include many things, but one of them, the job of management, needs to be nailed down. Three standard practices for managing in a network are developed: (a) support the dialogues that connect people vital to accomplishing a goal or objective; (b) develop and sustain the scoreboards that serve as a road-map to reach the goal; and (c) control the feedback to 'govern the horse'. These three practices are useful for more than reaching goals, as they also support coordinating across boundaries and running productive meetings. The dialogues for productive relationships, scoreboards for goals and deliverables, and feedback for performance together constitute a recipe for managing in a networked world. (authors)

99 GENERAL AND MISCELLANEOUS↗

EMSL-Computing/PeakDecoder

PeakDecoder is a machine learning (ML)-based metabolite identification algorithm for multidimensional mass spectrometry measurements incorporating liquid chromatography (LC) and ion mobility spectrometry (IM) separations, and collecting extensive fragmentation spectra with data-independent acquisition (DIA) methods: LC-IM-DIA-MS. The algorithm learns to distinguish true co-elution and co-mobility from raw data and calculates metabolite identification error rates.

Bilbao Pena, Aivett↗

Automated Work Package: Initial Wireless Communication Platform Design, Development, and Evaluation

The Department of Energy’s Light Water Reactor Sustainability Program is developing the scientific basis to ensure long-term reliability, productivity, safety, and security of the nuclear power industry in the United States. The Instrumentation, Information, and Control (II&C) pathway of the program aims to increase the role of advanced II&C technologies to achieve this objective. One of the pathway efforts at Idaho National Laboratory (INL) is to improve the work packages execution process by replacing the expensive, inefficient, bulky, complex, and error-prone paper-based work orders with automated work packages (AWPs). An AWP is an automated and dynamic presentation of the work package designed to guide the user through the work process. It is loaded on a mobile device, such as a tablet, and is capable of communicating with plant equipment and systems to acquire plant and procedure states. The AWP replaces those functions where a computer is more efficient and reliable than a human. To enable the automatic acquisition of plant data, it is necessary to design and develop a prototype platform for data exchange between the field instruments and the AWP mobile devices. The development of the platform aims to reveal issues and solutions generalizable to large-scale implementation of a similar system. Topics such as bandwidth, robustness, response time, interference, and security are usually associated with wireless communication. These concerns, along with other requirements, are listed in an earlier INL report. Specifically, the targeted issues and performance aspects in this work are relevant to the communication infrastructure from the perspective of promptness, robustness, expandability, and interoperability with different technologies.

Automated Work Packages↗