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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Quantifying Supply Risk at a Cellulosic Biorefinery

In order to increase the sustainability and security of the nation’s energy supply, the U.S. Department of Energy through its Bioenergy Technology Office has set a vision for one billion tons of biomass to be processed for renewable energy and bioproducts annually by the year 2030. The Renewable Fuels Standard limits the amount of corn grain that can be used in ethanol conversion sold in the U.S, which is already at its maximum. Therefore making the DOE’s vision a reality requires significant growth in the advanced biofuels industry where currently three cellulosic biorefineries convert cellulosic biomass to ethanol. Risk mitigation is central to growing the industry beyond its infancy to a level necessary to achieve the DOE vision. This paper focuses on reducing the supply risk that faces a firm that owns a cellulosic biorefinery. It uses risk theory and simulation modeling to build a risk assessment model based on causal relationships of underlying, uncertain, supply driving variables. Using the model the paper quantifies supply risk reduction achieved by converting the supply chain from a conventional supply system (bales and trucks) to an advanced supply system (depots, pellets, and trains). Results imply that the advanced supply system reduces supply system risk, defined as the probability of a unit cost overrun, from 83% in the conventional system to 4% in the advanced system. Reducing cost risk in this nascent industry improves the odds of realizing desired growth.

09 BIOMASS FUELS↗
DOE OSTI2019

Governance & Management Framework

NNSA’s Strategic Vision identifies our vision for the future, policy direction, and mission priorities, as well as the current challenges that we must overcome. This Governance & Management Framework lays out the path and the tools for NNSA as a team to deliver its mission in a resilient, agile, and responsive manner. This Framework is the how to the Vision’s what and explains how Governance and Management (G&M) serves a key role in managing the nuclear security enterprise. This Framework encompasses the federal headquarters and field office staff, our partner laboratory, plant, and site personnel, and the partners’ corporate parents.

Source record↗
DOE OSTI2016

Completing the Cleanup of the US Department of Energy's East Tennessee Technology Park - Four Years Early - 16067

On August 1, 2011, URS - CH2M Oak Ridge LLC (UCOR) began its $2.6 billion cleanup of the East Tennessee Technology Park (ETTP), the former Oak Ridge Gaseous Diffusion Plant, located on the U.S. Department of Energy's (DOE) Oak Ridge Reservation (ORR) in Tennessee. Under the contract, the scope of work to be completed includes demolition of all gaseous diffusion buildings, namely K-25, K-31 and K-27, as well as other facilities such as the Toxic Substance Control Act (TSCA) Incinerator, the K-1200 Centrifuge Complex and the K-1037 Barrier Plant. Additionally, UCOR will remove contaminated soils and treat contaminated groundwater. Waste generated by these cleanup activities will be disposed at onsite as well as offsite facilities. UCOR will also continue to manage hundreds of the DOE Oak Ridge Office of Environmental Management (OREM)-owned facilities across the ORR. Due largely to funding challenges early in the project, the DOE estimated in their October 2013 Program Plan 2014-2024 that ETTP cleanup would not be achieved until 2024, four years later than originally scheduled in UCOR's contract with the DOE. In November 2014, the DOE Manager for OREM, Susan Cange, publicly shared her 'vision' for ETTP cleanup by 2020, four years earlier than the DOE's current plan. As part of Vision 2020, all gaseous diffusion buildings would be demolished by the end of 2016. In response to Ms. Cange's vision, UCOR published a Strategic Plan describing how ETTP could be cleaned up by 2020, provided that a number of funding and programmatic and technical challenges could be overcome. UCOR is in the midst of implementing its Strategic Plan, and progress is being made to that end. Since assuming its responsibilities as the ETTP cleanup contractor, UCOR has completed its life-cycle Performance Measurement Baseline (PMB); received its Earned Value Management System (EVMS) certification; completed the D and D of the 44-acre K-25 and 17-acre K-31 gaseous diffusion buildings; completed the K-1070- B Burial Ground remediation project; completed RCRA closure of the TSCA Incinerator; and disposed of more than 541,411 cubic yards of cleanup waste while managing the on-site Environmental Management Waste Management Facility (EMWMF). In 2015, UCOR achieved safety 'Star Status' under the DOE's Voluntary Protection Program (VPP); completed the demolition of the K-31 gaseous diffusion building; advanced the characterization and deactivation of the K-27 gaseous diffusion building, readying the building for the start of demolition in 2016; and began characterization activities in the K-1037 Barrier Plant as well as a number of facilities in the Poplar Creek Area of the ETTP Site. Project performance through December 31, 2015, is as follows: Cost Performance Index - 1.12, Schedule Performance Index - 1.02. Since safety is the foundation of all cleanup work, UCOR's safety record goes hand-in-hand with its project performance. Through calendar year 2015, UCOR's recordable injury rate was 0.94 occurrences per 200,000 work hours, and the day away case rate was 0.31. These rates are both below the DOE and UCOR goals. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2019

Collaborative Robots vs. Master/Slaves - 19522

This paper will discuss the feasibility, application, and economy of applying collaborative robots (co-bots) in lieu of traditional through-the-wall tele-operated manipulator systems, traditionally used within hazardous (radioactive) environments. Both fixed facility and mobile applications will be discussed. Both single- and dual-armed co-bot systems will be employed. The six-axis, plus gripper, single-armed co-bots will provide for machine vision enhanced pick-n-place applications within shielded rooms and also include force-reflecting (haptic) teleoperations controls for non-routine materials-handling operations. The dual-armed system will be mounted to a motorized stand with motorized adjustment both vertically and rotationally (around its base). To complement these co-bots, both two-dimensional and three-dimensional vision technologies will be implemented. The vision technologies, in these applications, are used in lieu of traditional radiation shielding windows. two-dimensional video systems will provide for large area viewing, incorporating pan, tilt, and zoom capabilities. Three-dimensional video systems will be mounted to the dual-armed robot stand and provide viewing, including depth-of-perception, to the operator, performing material handling and other tasks, from an operator workstation located outside the hazardous environment. The unique workstation used with the dual-armed systems will also be described. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Session 097B - Panel: Pathway to End State at the East Tennessee Technology Park in Oak Ridge, TN (2/4) (R1.16b)

This panel was to focus on the 'Pathway to End State at the East Tennessee Technology Park (ETTP)'. It was to discuss the DoE's long-term vision for the ETTP site and the process for converting the site into a multi-use industrial park, historic preservation and national park, and conservation area. The Panelists were to discuss the challenges in executing a cleanup project of this magnitude, the waste management, and the monitoring efforts that supported the achievement of the Oak Ridge Office of Environmental Management (OREM) Vision 2020. This session integrated with panel sessions 97A, 97C, and 97D. Panelists with presentations: Beginning with the End in Mind (Kevin Ironside); Project Execution (Daniel Macias); Waste Management (John Wrapp); Environmental Remediation (Samantha Pack); Waste Management (Josh Pemberton); DOE's Long-Range Vision (Laura Wilkerson)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Session 097A - Panel: Accomplishments and Update of the East Tennessee Technology Park in Oak Ridge, TN (1/4) (R1.16a)

This panel was deferred until 2021. The session was designed to highlight and celebrate the accomplishment of Vision 2020 at US DoE's East Tennessee Technology Park (ETTP) in Oak Ridge, Tennessee. Vision 2020 is the overarching strategy and guidance that have formed the foundation of success in closing one of the largest cleanup site in the DOE Complex. The session was supposed to feature representatives from the DOE Oak Ridge Office of Environmental Management (OREM) and its contractor, UCOR, in exploring the partnerships and performance excellence that have made the difference in achieving success. OREM's Vision 2020 is a collaboration with entities that have made a difference in its success: economic developers, workforce developers, the University of Tennessee, and community partners. The vigorous Oak Ridge small business contracting community has also been instrumental in helping achieve success. This session plans to celebrate the entire process, its numerous players, and the spirit of accomplishment as the Oak Ridge community comes to realize the promise of 30 years of continuous cleanup excellence. This session integrated with panel sessions 97B, 97C and 97D. Panelists with presentations: Beyond Cleanup: Achieving Risk Reduction through Partnerships and Performance Excellence (Kenneth Rueter); Strategic Approach to Achieve End States at the East Tennessee Technology Park (Jay Mullis)

61 RADIATION PROTECTION AND DOSIMETRY↗
NASA NTRS2006

Acceleration of Stereo Correlation in Verilog

To speed up vision processing in low speed, low power devices, embedding FPGA hardware is becoming an effective way to add processing capability. FPGAs offer the ability to flexibly add parallel and/or deeply pipelined computation to embedded processors without adding significantly to the mass and power requirements of an embedded system. This paper will discuss the JPL stereo vision system, and describe how a portion of that system was accelerated by using custom FPGA hardware to process the computationally intensive portions of JPL stereo. The architecture described takes full advantage of the ability of an FPGA to use many small computation elements in parallel. This resulted in a 16 times speedup in real hardware over using a simple linear processor to compute image correlation and disparity.

machine vision↗
DOE OSTI2025

Automated Fire Detection for Industrial Settings with Pretrained Convolutional Networks

Early fire detection in industrial environments is critical to preventing equipment damage, personal injury, and operational disruptions. Traditional smoke detectors, while effective, often experience delays due to the time required for smoke to reach sensors, allowing fires to spread. Manual fire watch operations and human surveillance of camera feeds are resource-intensive and prone to human error. To address these challenges, this paper explores the application of convolutional neural networks for automated fire detection, specifically in industrial settings. By leveraging 11 different pre-trained machine vision models from TensorFlow and enhancing them with transfer learning on a custom-built industrial fire dataset, we optimized fire detection performance. Here, we analyzed each machine vision model architecture in terms of its depth, width, and input image resolution, considering both resource requirements and detection accuracy. We further explored the option of combining multiple models into an ensemble classifier to evaluate whether the performance improvements could justify the much greater computational complexity and other practical impacts. A cost-benefit analysis is presented to evaluate the trade-offs between performance and computational expense. Our findings identify that EfficientNetV2L, specifically tailored for industrial applications, provides the optimal balance between costs involved in training and using the model versus the overall fire detection performance. Additionally, we present a qualitative analysis of model performance using the technique of gradient-based class activation mapping to provide explainability by visualizing model decisions.

artificial intelligence↗
DOE OSTI2023

In situ characterization of material extrusion printing by near-infrared spectroscopy

Material extrusion printing of reactive resins and inks present a unique challenge due to the time-dependent nature of the rheological and chemical properties they possess. As a result, careful print optimization or process control is important to obtain consistent, high quality prints via additive manufacturing. Here, we present the design and use of a near-infrared (NIR) flow through cell for in situ chemical monitoring of reactive resins during printing. Differences between in situ and off-line benchtop measurements are presented and highlight the need for in-line monitoring capability. Additionally, in-line extrusion force monitoring and off-line post inspection using machine vision is demonstrated. By combining NIR and extrusion force monitoring, it is possible to follow cure reaction kinetics and viscosity changes during printing. When combined with machine vision, the ability to automatically identify and quantify print artifacts can be incorporated on the printing line to enable real-time, artificial intelligence-assisted quality control of both process and product. Together, these techniques form the building blocks of an optimized closed-loop process control strategy when complex reactive inks must be used to produce printed hardware.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Proton Radiation Therapy for the Treatment of Retinoblastoma

Purpose: To investigate long-term disease and toxicity outcomes for pediatric retinoblastoma patients treated with proton radiation therapy (PRT). Methods and Materials: This is a retrospective analysis of 49 retinoblastoma patients (60 eyes) treated with PRT between 1986 and 2012. Results: The majority (84%) of patients had bilateral disease, and nearly half (45%) had received prior chemotherapy. At a median follow-up of 8 years (range, 1-24 years), no patients died of retinoblastoma or developed metastatic disease. The post-PRT enucleation rate was low (18%), especially in patients with early-stage disease (11% for patients with International Classification for Intraocular Retinoblastoma [ICIR] stage A-B disease vs 23% for patients with ICIR stage C-D disease). Post-PRT ophthalmologic follow-up was available for 61% of the preserved eyes (30 of 49): 14 of 30 eyes (47%) had 20/40 visual acuity or better, 7 of 30 (23%) had moderate visual acuity (20/40-20/600), and 9 of 30 (30%) had little or no useful vision (worse than 20/600). Twelve of 60 treated eyes (20%) experienced a post-PRT event requiring intervention, with cataracts the most common (4 eyes). No patients developed an in-field second malignancy. Conclusions: Long-term follow-up of retinoblastoma patients treated with PRT demonstrates that PRT can achieve high local control rates, even in advanced cases, and many patients retain useful vision in the treated eye. Treatment-related ocular side effects were uncommon, and no radiation-associated malignancies were observed.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2026

Advancements in reflected target nonintrusive assessment (ReTNA) for large optical surface measurement

Reflected computer vision targets are a powerful tool for measurement of mirror surface shape, with several important advantages over traditional fringe deflectometry methods. This method was first presented in 2021 and has undergone significant improvement and demonstration since. We describe a new baseline system using reflected computer vision targets, and present results from a large-scale measurement campaign conducted on both commercial heliostats and test mirrors in the laboratory. Calibration of the measurement system with photogrammetry allows for accurate measurement without careful control of target shape or camera position. Overall, the results show that a baseline setup using this method achieves measurement uncertainties in the slope error root-mean-square less than ±0.11 milliradian due to a series of repeatability conditions, varying sample position, rotation, lighting, camera settings, and system rebuild and recalibration. We present a detailed description of the setup, the results generated by this measurement tool, repeated measurement results, and the strengths and limitations of this metrology system.

14 SOLAR ENERGY↗
DOE OSTI2023

A survey of techniques for optimizing transformer inference

Recent years have seen a phenomenal rise in the performance and applications of transformer neural networks. The family of transformer networks, including Bidirectional Encoder Representations from Transformer (BERT), Generative Pretrained Transformer (GPT) and Vision Transformer (ViT), have shown their effectiveness across Natural Language Processing (NLP) and Computer Vision (CV) domains. Transformer-based networks such as ChatGPT have impacted the lives of common men. However, the quest for high predictive performance has led to an exponential increase in transformers' memory and compute footprint. Researchers have proposed techniques to optimize transformer inference at all levels of abstraction. Further, this paper presents a comprehensive survey of techniques for optimizing the inference phase of transformer networks. We survey techniques such as knowledge distillation, pruning, quantization, neural architecture search and lightweight network design at the algorithmic level. We further review hardware-level optimization techniques and the design of novel hardware accelerators for transformers. We summarize the quantitative results on the number of parameters/FLOPs and the accuracy of several models/techniques to showcase the tradeoff exercised by them. We also outline future directions in this rapidly evolving field of research. We believe that this survey will educate both novice and seasoned researchers and also spark a plethora of research efforts in this field.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Block segmentation in feature space for realtime object detection in high granularity images

Computer vision has applications in object detection, image recognition and classification, and object tracking. One of the challenges of computer vision is the presence of useful information at multiple distance scales. Filtering techniques may sacrifice details at small scales in order to prioritize the analysis of large-scale features of the image. We present a strategy for coarse-graining multidimensional data while maintaining fine-grained detail for subsequent analysis. The algorithm is based on fixed-size block segmentation in the feature space. We apply this strategy to solve the long-standing challenge of detecting particle trajectories at the Large Hadron Collider in real time.

Computer vision↗
DOE OSTI2017

Advanced Control Systems for Wave Energy Converters

This submission contains several papers, a final report, descriptions of a theoretical framework for two types of control systems, and descriptions of eight real-time flap load control policies with the objective of assessing the potential improvement of annual average capture efficiency at a reference site on an MHK device developed by Resolute Marine Energy, Inc. (RME). The submission also contains an LCOE model that estimates the performance and related energy cost improvements that each advanced control system might provide and recommendations for improving DOE's LCOE model. The two types of control systems are for wave energy converters which transform data into commands that, in the case of RME's OWSC wave energy converter, provide real-time adjustments to damping forces applied to the prime mover via the power take-off system (PTO). The control theories developed were: 1) Model Predictive Control (MPC) or so-called "non-causal" control whereby sensors deployed seaward of a wave energy converter measure incoming wave characteristics and transmit that information to a data processor which issues commands to the PTO to adjust the damping force to an optimal value; and 2) "Causal" control which utilizes local sensors on the wave energy converter itself to transmit information to a data processor which then issues appropriate commands to the PTO. The two advanced control policies developed by Scruggs and Re Vision were then compared to a simple control policy, Coulomb damping, which was utilized by RME during the two rounds of ocean trials it had conducted prior to the commencement of this project. The project work plan initially included a provision for RME to conduct hardware-in-the-loop (HIL) testing of the data processors and configurations of valves, sensors and rectifiers needed to implement the two advanced control systems developed by Scruggs and Re Vision Consulting but the funding for that aspect of the project was cut at the conclusion of Budget Period 1. Accordingly, more work needs to be done to determine: a) means and feasibility of implementing real-time control; and b) added costs associated with such implementation taking into account estimated effects on system availability in addition to component costs.

16 TIDAL AND WAVE POWER↗
DOE OSTI2019

GeoVision Analysis Supporting Task Force Report: Electric Sector Potential to Penetration

This report describes research and analysis performed in support of the U.S. Department of Energy Geothermal Technologies Office for its Geothermal Vision Study. A summary of the study is captured in DOE’s report, GeoVision: Harnessing the Heat Beneath Our Feet and included ground-breaking, detailed research on geothermal technologies. The study projects and quantifies the future electric and nonelectric deployment potentials of these geothermal technologies within a range of scenarios in addition to their impacts on U.S. jobs, the economy, and environment. Coordinated by the U.S. Department of Energy Geothermal Technologies Office, the Geothermal Vision Study development relied on collecting, modeling, and analyzing robust data sets through seven national laboratory partners that were organized into eight technical task force groups. These task forces and their respective principal leading national laboratory are listed in Table F-1. The table also provides a guide to the final research documents produced by each GeoVision task force. In most cases, these were prepared as laboratory reports, and they are referenced accordingly. Consult these external reports for detailed discussions of the topics contained within, which form the basis of the GeoVision analysis.

15 GEOTHERMAL ENERGY↗
NASA NTRS2000

Visual detection of spatial contrast patterns: evaluation of five simple models

The ModelFest Phase One dataset is a collection of luminance contrast thresholds for 43 two-dimensional monochromatic spatial patterns confined to an area of approximately two by two degrees. These data were collected by a collaboration among twelve laboratories, and were designed to provide a common database for calibration and testing of spatial vision models. Here I report fits of the ModelFest data with five models: Peak Contrast, Contrast Energy, Generalized Energy, a Gabor Channels model, and a Discrete Cosine Transform model. The Gabor Channels model provides the best fit, though the other, simpler models, with the exception of Peak Contrast, provide remarkably good fits as well. Though there are clear individual differences, regularities in the data suggest the possibility of constructing a standard observer for spatial vision. c2000 Optical Society of America.

NASA Discipline Space Human Factors↗
NASA NTRS2006

Attenuating Stereo Pixel-Locking via Affine Window Adaptation

For real-time stereo vision systems, the standard method for estimating sub-pixel stereo disparity given an initial integer disparity map involves fitting parabolas to a matching cost function aggregated over rectangular windows. This results in a phenomenon known as 'pixel-locking,' which produces artificially-peaked histograms of sub-pixel disparity. These peaks correspond to the introduction of erroneous ripples or waves in the 3D reconstruction of truly Rat surfaces. Since stereo vision is a common input modality for autonomous vehicles, these inaccuracies can pose a problem for safe, reliable navigation. This paper proposes a new method for sub-pixel stereo disparity estimation, based on ideas from Lucas-Kanade tracking and optical flow, which substantially reduces the pixel-locking effect. In addition, it has the ability to correct much larger initial disparity errors than previous approaches and is more general as it applies not only to the ground plane.

pixel locking effect↗
NASA NTRS2007

Overview of Key Saturn Probe Mission Trades

Ongoing studies, performed at NASA/JPL over the past two years in support of NASA's SSE Roadmap activities, proved the feasibility of a NF class Saturn probe mission. I. This proposed mission could also provide a good opportunity for international collaboration with the proposed Cosmic Vision KRONOS mission: a) With ESA contributed probes (descent modules) on a NASA lead mission; b) Early 2017 launch could be a good programmatic option for ESA-CV/NASA-NF. II. A number of mission architectures could be suitable for this mission: a) Probe Relay based architecture with short flight time (approx. 6.3-7 years); b) DTE probe telecom based architecture with long flight time (-11 years), and low probe data rate, but with the probes decoupled from the carrier, allowing for polar trajectories I orbiter. This option may need technology development for telecom; c) Orbiter would likely impact mission cost over flyby, but would provide significantly higher science return. The Saturn probes mission is expected to be identified in NASA's New Frontiers AO. Thus, further studies are recommended to refine the most suitable architecture. International collaboration is started through the KRONOS proposal work; further collaborated studies will follow once KRONOS is selected in October under ESA's Cosmic Vision Program.

probes↗