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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 1,333 records · Page 74
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

WE-G-BRC-03: Risk Assessment for Physics Plan Review

Failure Mode and Effects Analysis (FMEA) originated as an industrial engineering technique used for risk management and safety improvement of complex processes. In the context of radiotherapy, the AAPM Task Group 100 advocates FMEA as the framework of choice for establishing clinical quality management protocols. However, there is concern that widespread adoption of FMEA in radiation oncology will be hampered by the perception that implementation of the tool will have a steep learning curve, be extremely time consuming and labor intensive, and require additional resources. To overcome these preconceptions and facilitate the introduction of the tool into clinical practice, the medical physics community must be educated in the use of this tool and the ease in which it can be implemented. Organizations with experience in FMEA should share their knowledge with others in order to increase the implementation, effectiveness and productivity of the tool. This session will include a brief, general introduction to FMEA followed by a focus on practical aspects of implementing FMEA for specific clinical procedures including HDR brachytherapy, physics plan review and radiosurgery. A description of common equipment and devices used in these procedures and how to characterize new devices for safe use in patient treatments will be presented. This will be followed by a discussion of how to customize FMEA techniques and templates to one’s own clinic. Finally, cases of common failure modes for specific procedures (described previously) will be shown and recommended intervention methodologies and outcomes reviewed. Learning Objectives: Understand the general concept of failure mode and effect analysis Learn how to characterize new equipment for safety Be able to identify potential failure modes for specific procedures and learn mitigation techniques Be able to customize FMEA examples and templates for use in any clinic.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

TH-EF-BRB-06: Implementation of a Modulated-Arc Total Body Irradiation (TBI) Technique Using the RayStation Treatment Planning System

Purpose: To develop a clinical workflow for delivering a modulated-arc total body irradiation (TBI) with RayStation scripting. This technique uses arc fields with the patient lying at floor level on a padded table and is validated through measurements taken on a custom-made TBI phantom. Methods: Treatment planning was performed for a retrospective cohort of eight patients with a diverse range of heights and body types. Each was replanned using an open-field dual arc method, with the patient in supine and prone positions on the floor of the vault. All plans were optimized using Raystation Planning 4.7.2.5 (RaySearch Laboratories, Stockholm, Sweden), with 200 cGy prescribed to the 95% of the body contour − 5mm. This results in an open-field beam that sweeps craniocaudally across the length of the patient. The technique is validated with measurements at 10 cm intervals in a custom-milled, 5 cm thick acrylic phantom. A centrally located CC13 ion chamber and a Mobile MOSFET (Best Medical Canada, Ottawa, ON) detector array were used to measure dose. Supine and prone arcs for each patient were consecutively delivered, and the aggregate dose at each point was compared to the planned dose calculated in the phantom. Results: The ion chamber measurements differed from the planned dose by an average of .5%, with a standard deviation of 2.1%. All measured data for the MOSFETS were within 10% of the corresponding planned dose except for two outlying points. The standard deviation of dose differences across the entire cohort was 4.0%. Most significant discrepancies occurred either in inhomogeneous regions with large gradients, or at inferior points where beam angle was steepest. Conclusion: We have confirmed that the planned dose is well matched to our measurements within 10% for this method of planning and delivery. We are currently incorporating this technique into our clinical workflow. This work is supported by RaySearch.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Sci-Sat AM: Radiation Dosimetry and Practical Therapy Solutions - 07: A mould room in a box – 3D scanning and printing technology in the radiotherapy clinic

Purpose: We describe the process by which our centre is currently implementing 3D printing and scanning technology for treatment accessory fabrication. This technology can increase efficiency and accuracy of accessory design, production and placement during daily use. Methods: A low-cost 3D printer and 3D optical scanner have been purchased and are being commissioned for clinical use. Commissioning includes assessing: the accuracy of the 3D scanner through comparison with high resolution CT images; the dosimetric characteristics of polylactic acid (PLA) for electron beams; the clinical utility of the technology, and; methods for quality assurance. Results: The agreement between meshes generated using the 3D scanner and CT data was within 2 millimeters for an anthropomorphic head phantom. In terms of electron beam attenuation, 1 centimetre of printed PLA was found equivalent to 1.17 cm of water. In proof-of-concept tests, several types of treatment accessories have been prototyped to date that will benefit from this technology. These include electron and photon bolus for areas with complex surface contours including the ear for electron treatments, the extremities for photon treatments and lead shielding for orthovoltage treatments. Imaging with CT and x-ray showed minimal defects, which will have no significant clinical impact. Geometric fidelity and fit to volunteers and patients was found to be excellent. Conclusions: 3D Printing and scanning can increase efficiency in the clinic for treatments requiring custom accessories. Customized boluses and shielding had excellent fit and reduced uncertainty in positioning.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Principles for designing proteins with cavities formed by curved β sheets

Active sites and ligand-binding cavities in native proteins are often formed by curved β sheets, and the ability to control β-sheet curvature would allow design of binding proteins with cavities customized to specific ligands. Toward this end, we investigated the mechanisms controlling β-sheet curvature by studying the geometry of β sheets in naturally occurring protein structures and folding simulations. The principles emerging from this analysis were used to design, de novo, a series of proteins with curved β sheets topped with α helices. Nuclear magnetic resonance and crystal structures of the designs closely match the computational models, showing that β-sheet curvature can be controlled with atomic-level accuracy. Our approach enables the design of proteins with cavities and provides a route to custom design ligand-binding and catalytic sites.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Control optimization for parametric Hamiltonians by pulse reconstruction

Optimal control techniques provide a means to tailor the control pulses required to generate customized quantum gates, which helps to improve the resilience of quantum simulations to gate errors and device noise. However, the significant amount of (classical) computation required to generate customized gates can quickly undermine the effectiveness of this approach, especially when pulse optimization needs to be iterated. We propose a method to reduce the computational time required to generate the control pulse for a Hamiltonian that is parametrically dependent on a time-varying quantity. We use simple interpolation schemes to accurately reconstruct the control pulses from a set of pulses obtained in advance for a discrete set of predetermined parameter values. We obtain a reconstruction with very high fidelity and a significant reduction in computational effort. We report the results of the application of the proposed method to device-level quantum simulations of the unitary (real) time evolution of two interacting neutrons based on superconducting qubits.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2019

MAC: Memory Access Coalescer for 3D-Stacked Memory

Emerging data-intensive applications, such as graph analytics and data mining, exhibit irregular memory access patterns. Research has shown that with these memory-bound applications, traditional cache-based processor architectures, which exploit locality and regular patterns to mitigate the memory-wall issue, are inefficient. Meantime, novel 3D-stacked memory devices, such as Hybrid Mem- ory Cube (HMC) and High Bandwidth Memory (HBM), promise significant increases in bandwidth that appear extremely appealing for memory-bound applications. However, conventional memory interfaces designed for cache-based architectures and JEDEC DDR devices fit poorly with the 3D-stacked memory, which leads to significant under-utilization of the promised high bandwidth. As a response to these issues, in this paper we propose MAC (Memory Access Coalescer), a coalescing unit for the 3D-stacked memory. We discuss the design and implementation of MAC, in the context of a custom designed cache-less architecture targeted at data-intensive, irregular applications. Through a custom simulation infrastructure based on the RISC-V toolchain, we show that MAC achieves a coalescing efficiency of 52.85% on average. It improves the performance of the memory system by 60.73% on average for a large set of irregular workloads.

Wang, Xi↗
DOE OSTI2021

Uncertainty Visualization for Renewable Energy Potential

In this paper, we present the reV (Renewable Energy Potential) Dashboard, an interactive browser-based tool for uncertainty visualization and data exploration built using customized plotly dash components. With continuing development and utilization of computational models to study the power sector there is an increasing need for data-driven visualization tools which allow scientists, researchers, and engineers to interact with their data in real-time. Our principle motivation for developing this interactive uncertainty visualization was to provide domain scientists and modelers a platform which allows them to better understand and communicate scientific findings stemming from intricate information encoded in their data that is otherwise difficult to capture by conventional analysis. The development of customized dashboard components using the React programming paradigm, combined with fully pre-processed data, allows for users to select a variety of data options to update and manipulate the visualization in a straightforward computationally efficient manner.

dashboard↗
DOE OSTI2022

Online distributed price-based control of DR resources with competitive guarantees

Demand response (DR) of building HVAC load can provide crucial demand-side flexibility for the future smart grid. Compared to direct load control, price-based control can respect the customers’ autonomy and privacy. However, it is challenging for price-based control to attain provable performance guarantees under future uncertainty. In this paper, we propose a framework for a utility to perform price-based control of flexible building load within the utility’s service area, in order to attain competitive performance guarantees in terms of controlling the system peak demand under future uncertainty. By adopting a two-step approach, our online price-based control solution can attain a provable competitive ratio for all possible realizations within a given uncertainty set. Simulation experiments demonstrate that, with a robustification procedure, our solution can perform well not only for worst-case inputs, but also for average-case inputs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Cross-Facility Orchestration of Electrochemistry Experiments and Computations

Instrument-computing ecosystems supporting automated electrochemical workflows typically require the integration of disparate instruments such as syringe pump, fraction collector, and potentiostat, all connected to an electrochemical cell. These specialized instruments with custom software and interfaces are not typically designed for network integration and remote automation. We developed a networked ecosystem of these instruments and computing platforms, which includes software to enable automated workflow orchestration from remote computers. Specifically, we developed Python wrappers of APIs and custom Pyro client-server modules to support remote operation of these instruments over the ecosystem network. Herein, we describe a specific workflow for generating and validating voltammogram (I-V) measurements of an electrolyte solution pumped into the electrochemical cell. We demonstrate the orchestration of this workflow which is composed using a Jupyter notebook and executed on a remote computer.

Al Najjar, Anees↗
DOE OSTI2025

OmniFed: A Modular Framework for Configurable Federated Learning from Edge to HPC

Federated Learning (FL) is critical for edge and High Performance Computing (HPC) where data is not centralized and privacy is crucial. We present OmniFed, a modular framework designed around decoupling and clear separation of concerns for configuration, orchestration, communication, and training logic. Its architecture supports configuration-driven prototyping and code-level override-what-you-need customization. We also support different topologies, mixed communication protocols within a single deployment, and popular training algorithms. It also offers optional privacy mechanisms including Differential Privacy (DP), Homomorphic Encryption (HE), and Secure Aggregation (SA), as well as compression strategies. These capabilities are exposed through well-defined extension points, allowing users to customize topology and orchestration, learning logic, and privacy/compression plugins, all while preserving the integrity of the core system. We evaluate multiple models and algorithms to measure various performance metrics. By unifying topology configuration, mixed-protocol communication, and pluggable modules in one stack, OmniFed streamlines FL deployment across heterogeneous environments. Github repository is available at https://github.com/at-aaims/OmniFed.

Tyagi, Sahil [ORNL] (ORCID:0009000783144745)↗
DOE OSTI2025

Complex Parsing for In-Network Acceleration of High-Energy Physics Experiments

This paper describes a novel application and evaluation of programmable networking in High-Energy Physics (HEP): a complete parser for the custom packet format used by Fermilab’s DUNE experiment. Notably, this parser is implemented on a Tofino programmable network switch and evaluated on the FABRIC testbed by using network traffic generated by the ICEBERG DUNE prototype. The parsed network traffic consists of Jumbo Ethernet frames that contain digitizations of sensor readings from ICEBERG’s detector.This work is an early investigation into providing in-network processing support for HEP experiments. The paper describes DUNE’s custom packet format, the challenges encountered when implementing a parser for that format, and an exploration of the techniques that are needed to overcome those challenges. We identify performance bottlenecks and discuss directions for future research.

Sagstad, Bjoern [IIT, Chicago] (ORCID:000900033610↗
DOE OSTI2024

Electrolyte and Cutoff Potential Effects on Cycle Life of Li4Ti5O12/LiNi0.9Mn0.1O2 Batteries for Behind-the-Meter Storage Applications

Behind-the-Meter Storage (BTMS) is a stationary battery energy storage system that is connected to the electrical distribution system on the customer's side of the utility's service meter. BTMS systems are used to store electrical energy from the grid as well as inconstant, renewable energy, such as local solar and wind generation. A successful BTMS system will allow the customer to pair their energy generation and storage to optimize electrical consumption from the grid, improving reliability and minimizing cost. For BTMS applications, batteries must be designed and optimized with different set of criteria from other leading segments of the Li-ion battery market, like transportation, due the system being stationary and proximal to the residential or commercial building it's benefitting. BTMS applications prioritize safety, cost (low/no-critical materials), reliability (20-year calendar life), and durability (10,000 cycle life), while having the ability to (minimally) compromise energy density and rate capability. Lithium titanate (Li4Ti5O12-, LTO) is a promising anode candidate for BTMS applications due to its high safety and capacity retention, while maintaining a reasonable 160 mAhg-1 reversable capacity and composition of relatively abundant materials. (1) Specifically, LTO has a high working voltage which helps to prevent Li dendrite formation, improving safety. Furthermore, LTO also has negligible lithiation-based volume change, leading to less mechanical pulverization, or loss of active material, upon cycling. For the cathode, materials with little or no Co are of high interest due to the high cost and low abundance of Co. LiMn2O4 (LMO) has been paired with LTO for BTMS applications in the past due to its safety, low cost (abundancy), and reasonably high operating voltage. (2-4) However, the low capacity of LMO limits energy density and specific energy. While not the highest priority for BTMS applications, increasing energy density will enable deployment in space constrained BTMS applications and decrease total cost. LiNi0.9Mn0.1O2 (LN-MO) is a recently developed material with promise due to its high operating voltage and relatively low price. (5) However, Ni-rich layered oxides, including LNMO, tend to struggle with capacity retention during high-voltage cycling due to mechanical pulverization, irreversible phase transitions, and unstable solid-electrolyte interphase. The study presented here focuses on building an understanding of how electrolyte solvent and varied cutoff potentials will impact the cycle life of LTO/LN-MO cells. Specifically, a comparison is provided between ethylene carbonate (EC), ethyl methyl carbonate (EMC), fluoroethylene carbonate (FEC), and Gen2 electrolyte solvents with 1M Lithium hexafluorophosphate (LiPF6) salt, cycling to two upper termination potentials, 2.6V and 2.7V. Electrochemical testing and diagnostics (e.g., differential capacity analysis, area specific impedance, constant voltage hold, and rate capability) and post-mortem characterization will be used to understand the aging behavior and failure mechanisms of the 8 cell combinations (four electrolytes and two voltage cutoffs). Cells with FEC electrolyte showed a lower initial capacity compared to cells with Gen2, EMC, and EC cycling at both voltages; however, the cells with FEC showed consistent trends in capacity retention with 2.6V and 2.7V termination potentials, while the cells with the other electrolytes showed much higher rates of capacity loss when cycling to the higher voltage. These results indicate that FEC may play a role in improving durability of high-voltage, Ni-rich electrode systems for use in high-cycle applications, such as BTMS.

electrolyte↗
DOE OSTI2014

A high-density, high-channel count, multiplexed μECoG array for auditory-cortex recordings

Our understanding of the large-scale population dynamics of neural activity is limited, in part, by our inability to record simultaneously from large regions of the cortex. Here, we validated the use of a large-scale active microelectrode array that simultaneously records 196 multiplexed micro-electrocortigraphical (μECoG) signals from the cortical surface at a very high density (1,600 electrodes/cm 2 ). We compared μECoG measurements in auditory cortex using a custom “active” electrode array to those recorded using a conventional “passive” μECoG array. Both of these array responses were also compared with data recorded via intrinsic optical imaging, which is a standard methodology for recording sound-evoked cortical activity. Custom active μECoG arrays generated more veridical representations of the tonotopic organization of the auditory cortex than current commercially available passive μECoG arrays. Furthermore, the cortical representation could be measured efficiently with the active arrays, requiring as little as 13.5 s of neural data acquisition. Next, we generated spectrotemporal receptive fields from the recorded neural activity on the active μECoG array and identified functional organizational principles comparable to those observed using intrinsic metabolic imaging and single-neuron recordings. Furthermore, this new electrode array technology has the potential for large-scale, temporally precise monitoring and mapping of the cortex, without the use of invasive penetrating electrodes.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Sci-Vis Framework

SVF is a full featured OpenGL 3d framework that allows for rapid creation of complex visualizations. The SVF framework handles much of the lifecycle and complex tasks required for a 3d visualization. Unlike a game framework SVF was designed to use fewer resources, work well in a windowed environment, and only render when necessary. The scene also takes advantage of multiple threads to free up the UI thread as much as possible. Shapes (actors) in the scene are created by adding or removing functionality (through support objects) during runtime. This allows a highly flexible and dynamic means of creating highly complex actors without the code complexity (it also helps overcome the lack of multiple inheritance in Java.) All classes are highly customizable and there are abstract classes which are intended to be subclassed to allow a developer to create more complex and highly performant actors. There are multiple demos included in the framework to help the developer get started and shows off nearly all of the functionality. Some simple shapes (actors) are already created for you such as text, bordered text, radial text, text area, complex paths, NURBS paths, cube, disk, grid, plane, geometric shapes, and volumetric area. It also comes with various camera types for viewing that can be dragged, zoomed, and rotated. Picking or selecting items in the scene can be accomplished in various ways depending on your needs (raycasting or color picking.) The framework currently has functionality for tooltips, animation, actor pools, color gradients, 2d physics, text, 1d/2d/3d textures, children, blending, clipping planes, view frustum culling, custom shaders, and custom actor states

Arthur Bleeker, PNNL↗
DOE OSTI2017

colormap_util

Our Python module, colormap_module, presented here can be used to analyze and manipulate colormaps and has two main aims: (i) compare existing and new custom colormaps quantitatively by comparing their values in a color space, called CAM02-UCS, that directly shows how a human perceives their hue, saturation, and lightness values and (ii) create isoluminant colormaps from existing or custom colormaps and (iii) mix isoluminant colormap data with a 4th dimension of data by manipulating lightness values across the image and present the new image. Our module was designed to be a tool for the community to use as a whole, allowing scientists to present, analyze, and manipulate colormaps they have created and/or decided to use for a particular type of data. By being able to do this, the scientific community as a whole will think more about the colormaps they choose, see why particular colormaps are bad to use for certain types of data, and move toward using colormaps our eyes can interpret much more efficiently.

Source record↗
DOE OSTI2017

Alternative Fueling Station Locator - ANDROID [SWR 17-07]

The Alternative Fueling Station Locator app helps you find fueling stations that offer electricity, natural gas, biodiesel, ethanol (E85), propane, and hydrogen. Use your current location or enter a custom location to find the 20 closest stations within a 30-mile radius. View the stations on a map or see a list of stations ordered by distance from your location. Select your alternative fuel of choice and adjust the custom filters to fit your needs. Select a station from the map or list to view contact info and other details: - address, phone number, and hours of operation - payment types accepted - public or private access - special services - compression (natural gas) - vehicle size access (natural gas) - number and types of chargers (electric) - blends available (biodiesel) - blender pumps (ethanol) The free app draws information from the U.S. Department of Energy's Alternative Fuels Data Center, which houses the most comprehensive, up-to-date database of alternative fueling stations in the United States. The database contains location information for more than 25,000 alternative fueling stations throughout the country.

Rahill, Matt↗
DOE OSTI2018

Real-Time Optimization of Distribution-level Energy Resources [SWR-18-27]

Researchers at NREL have developed a novel real-time control architecture to optimize the operation of DERs at residential, commercial, and industrial levels. The real-time system enables (portions of) feeders to emulate virtual power plants providing services to the rest of the grid, while ensuring satisfaction of electrical limits and maximizing customers’ benefits. This system can be integrated with legacy hardware and/or new advanced systems to optimally manage both individually-controlled DERs and aggregations of DERs. By virtue of the proposed engineering approach, the DERs collectively regulate the powers at an electrical point to respond to grid dispatch signals such as an automatic generation control, a ramping signal, or a 5-minute dispatch. Overall, this architecture allows end customers to minimize their payments and partake in grid operations while guaranteeing power quality in the distribution network.

Dall-Anese, Emiliano↗
DOE OSTI2019

CatCost™ (Catalyst Cost Estimation Tool) [SWR-18-74]

CatCost™ is a state-of-the-art cost estimation tool designed to reduce the cost uncertainty associated with pre-commercial catalyst materials. The tool combines industry-standard cost estimation methods and resources into an intuitive suite of tools to bring actionable cost insight to every step of catalyst research and development. CatCost™ allows the rapid development of comprehensive catalyst cost estimates. It incorporates detailed insight into manufacturing methods, especially for pre-commercial catalysts, without requiring any process design experience. The tool has been designed from the ground up with a number of user-selectable estimation methods, pricing libraries, and ease-of-use features to tailor an estimate to a user's skill level and need for customization, empowering researchers of all skill-levels to make better R&D decisions throughout the catalyst development cycle. Our costing methods are fully transparent and enable power-users the ability to adjust any estimate to the economic realities of their operation. The tool has been designed from the ground up with a number of user-selectable estimation methods, pricing libraries, and ease-of-use features to tailor an estimate to a user's skill level and need for customization, empowering researchers of all skill-levels to make better R&D decisions throughout the catalyst development cycle. Our costing methods are fully transparent and enable power-users the ability to adjust any estimate to the economic realities of their operation. Features include: Raw materials pricing: Libraries of common chemicals, cost scaling indices, guidance for obtaining bulk quotes, and methods for extrapolating laboratory-scale prices to bulk. Simplified step method for synthesis by a contract manufacturer: All-in hourly cost for process equipment using methods and data from tollers. (Excel-only in v1.0)

Baddour, Frederick↗