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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 1,045 records · Page 58
All sourcesNASA NTRSDOE OSTI
DOE OSTI2013

Design Optimization of Innovative High-Level Waste Pipeline Unplugging Technologies - 13341

Florida International University (FIU) is currently working on the development and optimization of two innovative pipeline unplugging methods: the asynchronous pulsing system (APS) and the peristaltic crawler system (PCS). Experiments were conducted on the APS to determine how air in the pipeline influences the system's performance as well as determine the effectiveness of air mitigation techniques in a pipeline. The results obtained during the experimental phase of the project, including data from pipeline pressure pulse tests along with air bubble compression tests are presented. Single-cycle pulse amplification caused by a fast-acting cylinder piston pump in 21.8, 30.5, and 43.6 m pipelines were evaluated. Experiments were conducted on fully flooded pipelines as well as pipelines that contained various amounts of air to evaluate the system's performance when air is present in the pipeline. Also presented are details of the improvements implemented to the third generation crawler system (PCS). The improvements include the redesign of the rims of the unit to accommodate a camera system that provides visual feedback of the conditions inside the pipeline. Visual feedback allows the crawler to be used as a pipeline unplugging and inspection tool. Tests conducted previously demonstrated a significant reduction of the crawler speed with increasing length of tether. Current improvements include the positioning of a pneumatic valve manifold system that is located in close proximity to the crawler, rendering tether length independent of crawler speed. Additional improvements to increase the crawler's speed were also investigated and presented. Descriptions of the test beds, which were designed to emulate possible scenarios present on the Department of Energy (DOE) pipelines, are presented. Finally, conclusions and recommendations for the systems are provided. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Carbohydrate-Containing Conjugated Polymers: Solvent-Resistant Materials for Greener Organic Electronics

Organic semiconducting polymers are exciting materials for electronic applications because of their good mechanical and optoelectronic properties. A major advantage of organic semiconductors is their solution processability. This allows access to a variety of simple and cost-effective device fabrication methods compared to the expensive, high-temperature processing methods required for silicon-based electronics. However, these materials often have low solubility, which limits their processing to toxic halogenated solvents. Also, their limited solubility often leads to interfacial mixing during device fabrication. Herein, this work explores the incorporation of environmentally friendly carbohydrate side chains in conjugated polymers to enhance processability in eco-friendly solvents. Moreover, a mild postprocessing treatment was designed to enable solvent resistance. Isoindigo-based polymers with varied ratios of acetyl-protected galactose side chains were synthesized to improve solubility in o-anisole in the protected state, while inducing solvent resistance through intramolecular hydrogen bonding in the deprotected state. Solvent resistance was confirmed both visually upon submersion in various solvents and using UV–visible spectroscopy. Importantly, the mild basic treatment to achieve solvent resistance has no negative impact on the electronic performance of these materials in organic field-effect transistors, even after subsequent submersion in various solvents, making them a valuable platform for the production of green processable multilayer electronics.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Strym: A Python Package for Real-time CAN Data Logging, Analysis and Visualization to Work with USB-CAN Interface

In this report, we describe a data analysis tool developed for decoding and analyzing vehicle data obtained from a passenger vehicle’s onboard controller area network (CAN) bus. The tool developed in this paper provides a timeseries framework to perform domain-specific analysis at scale when interpreting data from a vehicle or a collection of vehicles in light of how to design intelligent vehicle applications. The tool, called Strym, exploits the CAN bus mechanism of modern vehicles to capture data using commercially available CAN-to-USB hardware Comma.ai Panda devices, managed through open-source software Libpanda. Strym permits the decoding of vendor-specific CAN messages in a vehicle-agnostic manner. Through this, a researcher can characterize data throughput, assess data quality, and perform analyses. Such analyses are useful in a number of research such as studying human driving behavior in mixed-autonomy, new driver models, rare-event detection, traffic flow estimation, and custom control of vehicles.

Performance evaluation, Smart cities, Intelligent ↗
DOE OSTI2013

GridOPTICS(TM) A Novel Software Framework for Integrating Power Grid Data Storage, Management and Analysis

This paper describes the architecture and design of GridOPTICSTM, a novel software framework to integrate a collection of software tools developed by PNNL’s Future Power Grid Initiative (FPGI) into a coherent, powerful operations and planning tool for the power grid of the future. GridOPTICSTM enables plug-and-play of various analysis, modeling and visualization software tools for fast and accurate control of the power grid. To bridge the data access for different control purposes, GridOPTICSTM provides a scalable and thin layer of event processing that hides the complexity of data storage and management. The initial prototype of GridOPTICSTM was demonstrated with several use cases from PNNL’s FPGI.

GridOPTICS, power grid, software framework↗
DOE OSTI2012

Establishing a Comprehensive Wind Energy Program

This project was directed at establishing a comprehensive wind energy program in Indiana, including both educational and research components. A graduate/undergraduate course ME-514 - Fundamentals of Wind Energy has been established and offered and an interactive prediction of VAWT performance developed. Vertical axis wind turbines for education and research have been acquired, instrumented and installed on the roof top of a building on the Calumet campus and at West Lafayette (Kepner Lab). Computational Fluid Dynamics (CFD) calculations have been performed to simulate these urban wind environments. Also, modal dynamic testing of the West Lafayette VAWT has been performed and a novel horizontal axis design initiated. The 50-meter meteorological tower data obtained at the Purdue Beck Agricultural Research Center have been analyzed and the Purdue Reconfigurable Micro Wind Farm established and simulations directed at the investigation of wind farm configurations initiated. The virtual wind turbine and wind turbine farm simulation in the Visualization Lab has been initiated.

17 WIND ENERGY↗
DOE OSTI2018

The Strategic Value of Human Factors Engineering in Control Room Modernization

Control room modernization is one of the most challenging and complex upgrade projects that a nuclear power plant can undertake. It can have almost as big an impact on operations as, for example, turbine replacement. The challenges of migrating an analog control system to a distributed control system are already well known and a number of nuclear utilities have embarked upon various levels of effort to upgrade some of the systems in the control room. When planning for control room upgrades, plants have to deal with a multitude of engineering, operational, and regulatory impacts. This will inevitably include several human factors considerations, such as workstation ergonomics, viewing angles, lighting, seating, new interaction modalities, new communication requirements, and new concepts of operation. In helping nuclear power utilities to deal with these challenges, the United States Department of Energy researchers located at Idaho National Laboratory (INL) have developed research-based human factors design and evaluation methods to be used in the development of end-state concepts for modernized control rooms and to manage the various phases of the upgrade life cycle. The methodology includes interactive sessions with operators in INL’s Human System Simulation Laboratory, three-dimensional modeling to visualize control board changes and operator-system interaction, and development of human-system prototypes to evaluate various aspects of proposed modifications. This methodology has been applied at a number of U.S. nuclear power plants where modernization projects are underway, including Exelon’s Braidwood and Byron plants, and Arizona Public Service's Palo Verde plant. It was demonstrated that including this methodology in the plant’s engineering process helps to ensure an integrated and cohesive outcome that is consistent with human factors engineering principles and provide substantial improvement in operator performance.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2022

The Exploitation of Data Reduction for Visualization

The disparity between the computational speed and storage bandwidth, as demonstrated in Figure 1, is a well known problem that grows with each successive generation. The visualization community is principally responding to this issue by using in situ to reduce which data must be written to storage. However, other communities are taking different, possibly complementary approaches. In particular, data compression is a common general approach to reduce storage demands. Data compression technologies are typically not designed with post processing in mind. The principal metrics measured are compression ratio, the improved bandwidth to storage, and the error introduced. It is assumed that data is inflated to its full size before any post processing can happen. Although when talking about bandwidth disparities, HPC’s dirty little secret is that no part of the memory nor interconnect hardware is increasing at the rate of computation. For example, the Summit supercomputer has a peak computation rate almost 10 times its predecessor, Titan, but only about 4 times the memory, less than twice the aggregate memory bandwidth, and almost no improvement in the interconnect bisection bandwidth. Naively inflating data for post processing does not help with limitations in the memory and interconnect systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

VERAView Programmer’s Manual

VERAView’s component-based design facilitates its extension and integration into other applications and systems. In addition to describing VERAView’s architecture and components, this document provides details on the component application programming interfaces (APIs), illustrates how to use the APIs independently of VERAView itself, and explains how to extend VERAView with custom visualizations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Combining Particle Tracking with Electromagnetic Radiation Showers: Merging GPT and Geant4 with Visualization

Field emitted electrons can seriously affect the operation of high-field, high-duty factor electron accelerators. Accelerated field emission can result in high average power beams which can radiation damage beamline components. In addition, localized losses generate thermal hot spots whose outgassing degrades the ultra-high vacuum required in photoinjectors and cryomodules. However, despite their importance, the effects of field emission are rarely included in the design and engineering of electron injectors. This work attempts to remedy this situation by combining two well-known and well-documented programs, GPT and Geant4, to track electrons and their losses in an injector beamline. This paper describes a system of programs which simulates electron paths and losses along the beamline. In addition, the tracking results can be zoomed and panned along and about the beampipe envelope using an open-source 3D CAD program. The scattering albedo calculations of the combined program, GPT-Geant4, are shown to be in good agreement with the literature albedos. The paper concludes with a dark current simulation for the LCLS-II injector from the cathode to the collimator at 1.5 m from the cathode.

Dowell, David H.↗
DOE OSTI2015

Water Network Tool for Resilience v. 1.0

WNTR is a python package designed to simulate and analyze resilience of water distribution networks. The software includes: - Pressure driven and demand driven hydraulic simulation - Water quality simulation to track concentration, trace, and water age - Conditional controls to simulate power outages - Models to simulate pipe breaks - A wide range of resilience metrics - Analysis and visualization tools

Source record↗
DOE OSTI2025

Determining Drying Conditions to Mitigate Hanford Transfer Line Corrosion

Radioactive waste is stored in underground, carbon-steel double-shell tanks at the Department of Energy Hanford site.1,2,3 The underground transfer lines are used to transfer the waste between the tanks and other assets at the Hanford tank farm facilities. The transfer lines constructed before 1990 are pipe-in-pipe design with most of the lines having carbon steel carrier pipe and carbon steel encasements. The lines constructed after 1990 have a stainless-steel carrier with a carbon steel encasement. The carrier lines, which are in contact with the waste, provide a critical confinement function, while the encasements provide secondary containment to reduce the risk of a release and contamination to the environment. In 2022, a visual inspection of the annulus between the encasement and the carrier for one of the pre-1990 transfer lines revealed standing liquid in contact with the carrier pipe. Additionally, a significant build-up of corrosion products on the exterior of the carrier pipe and the interior of the encasement pipe was observed. To assess the extent of condition, borescope inspections were performed in the encasement space of additional transfer lines in the facility to provide a baseline. The inspection revealed that of the lines inspected, 29 had either moisture present or evidence that moisture had been present in the past (e.g., waterline corrosion where the pipe had been exposed to standing water). Additional inspections indicated several instances of pitting corrosion on the interior of the encasement and exterior the carrier transfer lines. An image of the carrier pipe with several pits is presented in Figure 1(a) and the profiled image of the transfer line section along with the pit depths are presented Figure 1(b). As seen in the figure, the deepest pit was 73 mils on the pipe section. These lines were designated as “do-not-use” until further compensatory actions are implemented to return the lines to service.

Shukla, Pavan K. [Savannah River National Laborato↗
DOE OSTI2026

Data Summarization and Inference at Scale

This is the final report for the DOE ASCR grant SC-0022260, Data Summarization and Inference at Scale, PI: Alex Pothen, Purdue University. The goal of the project was to solve data-intensive and compute-intensive problems in the physical sciences, engineering, information science, data science, etc. by designing and implementing new algorithms that could work with a subset of the data. The four subgoals were: (a) The solution of problems where the data is too large to be stored in the memory of a computer. In this streaming model of computation, the data arrives as a stream of elements to the computer, each element is processed as it arrives, and a decision is made to discard the data or to store it; only a small subset of the data proportional to the size of the output solution is stored, and when all the data has been streamed, a solution to the problem is computed from the stored subset. (b) The use of machine learning methods to compute solutions to data-intensive problems. The use of GPUs is critical to obtain high performance on machine learning tasks, but their memory sizes are smaller relative to that of CPUs. For large-scale problems, the data is sampled many times, and small samples are used with repetition, for robustness, to compute solutions to inference tasks. This sampling reduces the memory required to solve the problem, but attention is needed to avoid slow convergence to the solutions, and reduced accuracy of inference. We propose submodular optimization, Large Language Models, and physics-informed neural networks to enable GPU computations here. (c) Modeling and visualization of high-dimensional data using interpretable features. Clinical proteomic data sets from immunology for the detection of cancer and other diseases are temporal and high-dimensional, and algorithms for visualizing these data sets using clinically interpretable features are lacking. We propose methods that compute distances based on the optimal transportation problem and graph edit distances to address this problem. We also propose the use of optimal transport-based distances, spatial statistics, and network structure to classify image data sets, We apply these algorithms to electron micrographs of the peripheral nervous system in the digestive tract. (d) The design of data-intensive algorithms on emerging architectures, specifically, noisy, intermediate-scale quantum (NISQ) devices. Quantum computers offer the possibility of exploring large solution spaces due to the principle of superposition, but current quantum computers are limited by few qubits, short coherence times due to noise, poor interconections among the qubits, etc. We propose the use of the divide and conquer paradigm to solve large-scale problems, wherein collections of small subproblems are solved on the quantum devices, and the solutions to the subproblems are integrated into a solution for the original problem on a classical computer.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

SU-C-9A-07: Fabrication and Calibration of a Novel High-Sensitivity Collimator for Brain SPECT Imaging

Purpose: We have designed a novel collimator for brain SPECT imaging that yields greatly increased sensitivity near the center of the brain without loss of resolution. The collimator was manufactured and initial evaluation has been completed. Methods: The collimator was time-consuming and challenging to build. Because our desired hole pattern required substantial variations in hole angle, we designed two supporting plates to securely position about 34,000 hexagonal, slightly tapered, 75-mm long steel pins. The holes in the plates were modeled to yield the desired focal length, hole length and septal thickness. Molten lead was poured in between the plates, and all pins were removed after cooling. The sensitivity gain compared to a fan-beam collimator was measured using a point source placed along the central ray at several distances from the collimator face. Visual inspection of the holes was not possible as the collimator was sealed so it could be safely mounted on a SPECT system. Therefore, we prepared a 2D array of 768, ∼48μCi Tc-99m point sources, separated by 1.6 cm. The array was imaged for 10 minutes at 4 shifted locations to reduce sampling distance to 8 mm. Results: The sensitivity of the novel cone-beam collimator varied with distance from the detector face; it was higher than that of the fan-beam collimator by factors ranging from 3 to 176. Examination of the projections of the 4×768 point sources revealed that fewer than 2% of the holes were fully or partially blocked, which indicates that the intensive manual fabrication process was very successful. Conclusion: We have designed and manufactured a novel collimator for brain SPECT imaging. As expected, the sensitivity is much higher than that of a fan-beam collimator. Because of differences between the manufactured collimator and its design, reconstruction of the data will require a measured system function.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Extreme-Scale Stochastic Particle Tracing for Uncertain Unsteady Flow Visualization and Analysis

We present an efficient and scalable solution to estimate uncertain transport behaviors-stochastic flow maps (SFMs)-for visualizing and analyzing uncertain unsteady flows. Computing flow maps from uncertain flow fields is extremely expensive because it requires many Monte Carlo runs to trace densely seeded particles in the flow. We reduce the computational cost by decoupling the time dependencies in SFMs so that we can process shorter sub time intervals independently and then compose them together for longer time periods. Adaptive refinement is also used to reduce the number of runs for each location. We parallelize over tasks-packets of particles in our design-to achieve high efficiency in MPI/thread hybrid programming. Such a task model also enables CPU/GPU coprocessing. We show the scalability on two supercomputers, Mira (up to 256K Blue Gene/Q cores) and Titan (up to 128K Opteron cores and 8K GPUs), that can trace billions of particles in seconds.

CPU-GPU hybrid parallelism↗
DOE OSTI2022

Evaluation of integrated daylighting and electric lighting design projects: Lessons learned from international case studies

This article presents and discusses the lessons learned from the monitoring of 25 integrated daylighting and electric lighting international case study projects. The case studies consist of real occupied buildings that have been monitored as part of the International Energy Agency (IEA) SHC Task 61/EBC Annex 77 Programme. The general goal of the case studies was to balance lighting energy use with occupants’ visual and non-visual requirements. This was achieved using innovative solutions for daylighting and electric lighting with advanced controls, but also implementing simple and out-of-the-box strategies. The findings suggest that energy demands for lighting can significantly be reduced by combining sensible daylight provision, efficient lighting sources, and advances in controls. Yet, the effective achievement of project goals requires adequate monitoring, fine-tuning, and verification. The findings also suggest that the adoption of “integrative” lighting – that is, lighting systems that address both visual and non-visual responses – is getting increasingly popular. Catering to non-visual requirements will likely drive further innovation in lighting technology. Currently, there is limited investment available for developing daylighting systems for integrative lighting, and the current related electric strategies often come at the risk of energy rebound effects. Overall, providing daylighting and understanding user requirements are fundamental steps towards achieving quality projects, with potential benefits beyond saving energy.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

WM26 Paper Multi-Robot Collaboration for Hazardous Environments

Hazardous nuclear and industrial facilities are rarely designed for robots. Work in these domains demand precise manipulation and robust mobility in cluttered, constrained spaces where off-the-shelf platforms struggle and “one-size-fits-all” machines become costly and complex. Idaho National Laboratory (INL) is developing an autonomous, multi-robot inspection system that coordinates task-specific platforms rather than relying on a single omni-tool robot. An electric truck serves as a power and compute hub for a custom manipulator co-developed with Florida International University (FIU), a commercial mini crawler, a pan–tilt–zoom camera, and a Nexxis Argus LiDAR mapping system. Working in concert, these robots generate spatial, radiation, and temperature maps of the pit environments at the Hanford Waste Tank Farms. These systems will capture visual records and environmental telemetry to allow for analysis post inspection. The system architecture uses Robot Operating System 2 (ROS 2) for publish/subscribe integration, NVIDIA Isaac Sim and Unity for simulation and visualization, and algorithms such as NVBlox to fuse data into unified 3D overlays. This robot-agnostic approach reduces operator burden by enabling autonomy across heterogeneous platforms and lets each robot be used where it is strongest. Having autonomous functions means operators don’t have to fully control multiple different components. The ease of use could allow for more widespread adoption of advanced robotics at waste management sites that see continued use. By coordinating simpler, purpose-built mechanisms, the approach lowers design and manufacturing complexity, reduces capital risk in contaminated settings, and improves controllability for complex inspection and manipulation tasks. We present the architecture, early results, and lessons learned from building and deploying this coordinated multi-robot system, with the goal of accelerating safe, cost-effective adoption of advanced robotics at waste-management sites.

42 - ENGINEERING↗
DOE OSTI2014

Optimization of an urea decomposition chamber using CFD and VR

Selective Catalytic Reduction (SCR) is an important air pollution control process that consists of injecting ammonia (NH 3 ) into the boiler flue gas and passing the flue gas through a catalyst bed where the NO x and NH 3 react to form nitrogen gas (N 2 ) and water vapor (H 2 O). At a coal-fired power station, a decomposition chamber uses combustion air and a natural gas burner to provide the necessary temperature, air flow and pressure to convert the injected urea solution into ammonia gas. Inspections of this decomposition chamber indicate debris formations occurring at the burner/roof prevent the chamber from achieving proper temperature for conversion and redirect the burner flame/flow, which can potentially shift the flow pattern in the chamber. In order to identify the cause of this debris formation, Computational Fluid Dynamics (CFD) and Virtual Reality (VR) have been employed to simulate and visualize the flow distribution and species concentration inside this decomposition chamber. Furthermore, by analyzing the simulation data, excessive ammonia recirculation have been identified as the cause of the debris formation at the top of the chamber. We have also conduced the parametric studies in order to optimize the existing chamber design by introducing multiple baffles to eliminate the excessive recirculation, thus minimizing debris formation.

42 ENGINEERING↗
DOE OSTI2015

Prostate Hypofractionated Radiation Therapy With Injection of Hyaluronic Acid: Acute Toxicities in a Phase 2 Study

Purpose: Hypofractionated radiation therapy (RT) in prostate cancer can be developed only if the risk of rectal toxicity is controlled. In a multicenter phase 2 trial, hypofractionated irradiation was combined with an injection of hyaluronic acid (HA) to preserve the rectal wall. Tolerance of the injection and acute toxicity rates are reported. Methods and Materials: The study was designed to assess late grade 2 toxicity rates. The results described here correspond to the secondary objectives. Acute toxicity was defined as occurring during RT or within 3 months after RT and graded according to the Common Terminology Criteria for Adverse Events version 4.0. HA tolerance was evaluated with a visual analog scale during the injection and 30 minutes after injection and then by use of the Common Terminology Criteria at each visit. Results: From 2010 to 2012, 36 patients with low-risk to intermediate-risk prostate cancer were included. The HA injection induced a mean pain score of 4.6/10 ± 2.3. Thirty minutes after the injection, 2 patients still reported pain (2/10 and 3/10), which persisted after the intervention. Thirty-three patients experienced at least 1 acute genitourinary toxicity and 20 patients at least 1 acute gastrointestinal toxicity. Grade 2 toxicities were reported for 19 patients with urinary obstruction, frequency, or both and for 1 patient with proctitis. No grade 3 or 4 toxicities were reported. At the 3-month visit, 4 patients described grade 2 obstruction or frequency, and no patients had any grade 2 gastrointestinal toxicities. Conclusions: The injection of HA makes it possible to deliver hypofractionated irradiation over 4 weeks with a dose per fraction of > 3 Gy, with limited acute rectal toxicity.

62 RADIOLOGY AND NUCLEAR MEDICINE↗