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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 OSTI2020

Advanced Engine and Fuel Technologies Annual Progress Report (FY2019)

On behalf of the Vehicle Technologies Office of the U.S. Department of Energy, we are pleased to introduce the Fiscal Year (FY) 2019 Annual Progress Report for the Advanced Engine and Fuel Technologies Program. In support of the Vehicle Technology Office’s goal for future U.S. economic growth, the Program focuses on early-stage research and development to improve understanding of combustion processes, fuel properties, and emissions control technologies, generating knowledge and insight necessary for industry to cost-effectively develop the next generation of engines and fuels. One of the most promising and cost-effective approaches to improving the fuel economy of the U.S. vehicle fleet is to introduce the next generation of higher-efficiency, very-low-emission combustion engines that meet future federal emissions regulations into the passenger and commercial vehicle markets. Advanced fuel formulations that can incorporate non-petroleum-based blending agents could further enhance engine efficiency, reduce greenhouse gas emissions, and provide fuel diversification. Also, innovations in combustion, fuels, emissions control, air control, turbomachinery, and energy recovery could potentially increase fuel economy considerably compared to today’s vehicles. The expected national economic, environmental, and energy security benefits from these next-generation engines and fuels would be significant inasmuch as the majority of vehicles sold over the next several decades will still include an engine. The Program has set the following goals for passenger and commercial vehicle fuel economy improvements. By 2030, increase light-duty engine efficiency to demonstrate 35% improvement in passenger vehicle fuel economy (25% improvement from engine efficiency and 10% from fuel co-optimization) relative to a 2015 baseline vehicle, while meeting the U.S. Environmental Protection Agency Tier 3 Emission and Fuel Standards. By 2030, improve heavy-duty engine efficiency by 35% relative to a 2009 baseline vehicle and identify cost-effective high-performance fuels that can further increase efficiency up to an additional 4%, while meeting prevailing U.S. Environmental Protection Agency emissions standards. The Program utilized advanced combustion processes to increase engine efficiency, resulting in a modeled passenger vehicle fuel economy improvement of 19.4% (over a Model Year 2015 baseline) in FY 2019. This report highlights progress achieved by the Advanced Engine and Fuel Technologies Program during FY 2019. The nature, current focus, and recent progress of the Program are described together with summaries of National Laboratory, industry, and university projects that provide an overview of the exciting work being conducted to address critical technical barriers and challenges to commercializing the next generation of higher-efficiency engine, emissions control, and fuel technologies for passenger and commercial vehicles.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

Halfway to Zero: Progress towards a Carbon-Free Power Sector

Sharply reducing carbon emissions is imperative to prevent the worst effects of climate change. Yet even in the power sector—often viewed as the lynchpin to economy-wide decarbonization, and where low-carbon solutions are increasingly plentiful and cost-effective—the pace and scale of the required transformation can be daunting. A review of historical trends, however, shows the progress the power sector has already made in reducing emissions. Fifteen years ago, many business-as-usual projections anticipated that annual carbon dioxide (CO 2 ) emissions from power supply in the United States would reach 3,000 million metric tons (MMT) in 2020. In fact, direct power-sector CO 2 emissions in 2020 were 1,450 MMT—roughly 50% below the earlier projections. By this metric, in only 15 years the country’s power sector has gone halfway to zero emissions. Other metrics also evolved differently than projected: total consumer electricity costs (i.e., bills) were 18% lower; costs to human health and the climate were 92% and 52% lower, respectively; and the number of jobs in electricity generation was 29% higher. Economic, technical, and policy factors contributed to this success, including sectoral changes, energy efficiency, wind and solar, continued operations of the nuclear fleet, and coal-to-gas fuel switching. This historical record demonstrates the ability of technological and policy changes to set the power sector on a dramatically different emissions trajectory. Past success, however, does not trivialize the challenges that remain for further decarbonization in the power sector and beyond. Nor does it offer a specific roadmap for how best to achieve additional power-sector emissions reductions. Numerous challenges confront a zero-emissions pathway, and future strategies will likely differ from those of the past. Many recent studies have assessed how to make further progress in decarbonizing the power sector on the pathway to decarbonizing the economy as a whole. We summarize the core results of those studies, but the primary goal of this report is to highlight the progress that has already been made in reducing power-sector emissions. As the country maps out a plan for further decarbonization, experience from the past 15 years offers two central lessons. First, policy and technology advancement are imperative to achieving significant emissions reductions. Second, our ability to predict the future is limited, and so it will be crucial to adapt as we gain policy experience and as technologies advance in unexpected ways.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Progress on Computational Modeling of Water-Based NSTF (FY2021)

This report documents the FY21 progress and achievements made in the computational analyses of the water-based NSTF. Both system-level and high-fidelity Computational Fluid Dynamics (CFD) analyses were performed to gain a complete understanding of the complex flow and heat transfer phenomena in natural convection systems. The progress on the waterbased NSTF experimental testing is summarized in a companion report (ANL-ART-230). As a continuation of progress from previous years, in FY21 the RELAP5 model of the NSTF was first updated to include a representative heated cavity that incorporated convection and conduction means of heat transfer. Two different cavity models were developed, one that models the radiation heat exchange among all surfaces in one enclosure (Cavity Model 1), and another that employs multiple radiation enclosures with each considering the surfaces at one axial level (Cavity Model 2). This updated RELAP5 deck was benchmarked with single-phase test data to tune form loss coefficients of the elbows and tees, along with heat transfer coefficients within the cavity and off the external insulation panels. This tuned model was then found to accurately predict fluid temperatures within 2.5% and both system and riser flow rates within 6% during single-phase, steady-state simulations. For transient simulations, there is a slight over prediction of the flow rate, fluid temperatures, and heater temperatures during the heat-up period, which indicate that the transient heat loss may be underestimated. Following, the capabilities of RELAP5-3D were examined, which feature a conduction enclosure model that is not present in the current version of RELAP5-MOD3.3 used for all previous NSTF simulations. As an initial comparison of the two codes, single-phase simulations were run that used similar input decks. The results indicate that the single-phase flow predicted by the two codes was very similar, however RELAP5-3D appears to predict a higher system flow during the two-phase transient when compared to the flow rates predicted by RELAP5-MOD3.3. Furthermore, RELAP5-3D run did not capture the density wave oscillations or geysering phenomena, which are large oscillation flow instabilities observed in the experimental facility. To further the prediction capabilities for capturing two-phase instabilities, Options 55, 57, 58, 61, which are implemented by default in RELAP5-MOD3.3 but not in RELAP5-3D, were investigated. When enabling Option 61, RELAP5-3D agrees well with MOD3.3 in predicting the total system flow, while other options have negligible effect on the predicted total system flow by RELAP5-3D. However, none of these options enables RELAP5-3D to produce the same flow instabilities. For future steps, efforts are currently underway to investigate RELAP5-3D’s different behavior in predicting low-pressure two-phase instabilities. STAR-CCM+ was used to perform CFD analysis of the water-based test facility and provide simulation results for comparisons to experimental data. Efforts first focused on describing the characteristics of flow within the heated cavity. A study was performed on whether possible leakage flow between the two sides of the cavity could substantially impact and explain the results. An additional second assumption was examined which defined adiabatic side walls, so physical insulation structures were added to the models to allow conduction across this outer insulation. The results suggest that potential porosity of the insulation could be a major factor in the temperature distribution within the cavity and should be considered in any studies where it is desirable to know the cavity wall temperatures to higher accuracy.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2017

VERA Core Physics Benchmark Progression Problem Results for VERA 3.6

This report contains a comparison of results obtained with VERA 3.6 Release Candidate 0 for the Core Physics Benchmark Progression Problems 1 through 9 to both computational tools and measured data from Watts Bar Unit 1 (WBN1). (Ref. 1 and Ref. 2) These problems progress from single pin cell analyses to full core depletion calculations. VERA results obtained for Problems 1 through 5 are compared against results obtained using the SCALE 6.2 Beta code KENO-VI. Results for Problem 6 and 7 are compared against those obtained using a coupled neutronic and thermal-hydraulic combination of the KAPL software MC21 and the CASL tool CTF. (Ref. 3, Ref. 4 and Ref. 5) VERA results from problems 5 and 9 are compared to data from WBN1. For all of the analyses contained in this report, VERA provided similar results to other state-of-the-art software programs and real reactor data. This indicates that the program is capable of modeling a full-scale PWR in a more discretized and computationally efficient manner than any other reactor physics program. Since the descriptions of the Core Physics Benchmark Progression Problems and the logic behind their selection is discussed in-depth elsewhere it is not covered in the scope of this document. Additionally, in-depth discussions of the software programs used in this analysis are not provided for the same rationale.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2013

VERA Core Physics Benchmark Progression Problem Specifications

Provided are the detailed specifications for the AMA Core Physics Benchmark Progression Problems 1 through 5. These problems were selected to assist software and methods developers and analysts in progressing through capabilities needed to model U.S. nuclear power reactors and their operations. The problems provide a prioritization of the VERA requirements for the virtual reactor, beginning at the fuel pin level and progressing to full core, multi-physics problems. They also enable clear and concise communication about what capabilities have been achieved. In addition to the specifications, reference solutions are provided, if available, from a continuous energy Monte Carlo transport solution.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2017

Progressive CPU Volume Rendering with Sample Accumulation

Here, we present a new method for progressive volume rendering by accumulating object-space samples over successively rendered frames. Existing methods for progressive refinement either use image space methods or average pixels over frames, which can blur features or integrate incorrectly with respect to depth. Our approach stores samples along each ray, accumulates new samples each frame into a buffer, and progressively interleaves and integrates these samples. Though this process requires additional memory, it ensures interactivity and is well suited for CPU architectures with large memory and cache. This approach also extends well to distributed rendering in cluster environments. We implement this technique in Intel’s open source OSPRay CPU ray tracing framework and demonstrate that it is particularly useful for rendering volumetric data with costly sampling functions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Progress towards the POCO of UK Highly Active Storage Tanks - 20112

In the UK Highly Active (HA) waste is stored in stainless steel Highly Active Storage Tanks (HASTs) prior to encapsulation in glass in one of three operating vitrification plants. Significant progress has been made towards the reduction in the volume of HA Liquor (HAL) stored in these HASTs and several tanks currently operate at heel levels. In recent years a strategy has been developed towards the Post Operational Clean Out (POCO) of the tanks and significant progress has been made in confirming this strategy since it was last presented at WMS [1]. For a variety of reasons changes to associated operational assumptions have also been made. This paper will highlight recent progress and changes associated with the strategy, including a description of some of the challenges that have been overcome and associated technical work undertaken. It will also detail current plans to POCO the HASTs, as quickly as possible, while minimising the risk and continuing to support other ongoing reprocessing and clean-up programmes as part of the overall UK clean-up mission. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2018

SECARB Daily Operations and Progress Reports

Monthly and quarterly technical progress reports, daily summaries of field activities, and overall progress of SECARB project from the Gulf Coast Carbon Center. Some folders may contain drafts of reports that were later revised before submission.

carbon capture and storage↗
DOE OSTI2024

Long duration battery sizing, siting, and operation under wildfire risk using progressive hedging

Battery sizing and siting problems are computationally challenging due to the need to make long-term planning decisions that are cognizant of short-term operational decisions. This paper considers sizing, siting, and operating batteries in a power grid to maximize their benefits, including price arbitrage and load shed mitigation, during both normal operations and periods with high wildfire ignition risk. Here we formulate a multi-scenario optimization problem for long duration battery storage while considering the possibility of load shedding during Public Safety Power Shutoff (PSPS) events that de-energize lines to mitigate severe wildfire ignition risk. To enable a computationally scalable solution of this problem with many scenarios of wildfire risk and power injection variability, we develop a customized temporal decomposition method based on a progressive hedging framework. Extending traditional progressive hedging techniques, we consider coupling in both placement variables across all scenarios and state-of-charge variables at temporal boundaries. This enforces consistency across scenarios while enabling parallel computations despite both spatial and temporal coupling. The proposed decomposition facilitates efficient and scalable modeling of a full year of hourly operational decisions to inform the sizing and siting of batteries. With this decomposition, we model a year of hourly operational decisions to inform optimal battery placement for a 240-bus WECC model in under 70 min of wall-clock time.

25 ENERGY STORAGE↗
DOE OSTI2017

Constitutive behavior and progressive mechanical failure of electrodes in lithium-ion batteries

The electrodes of lithium-ion batteries (LIB) are known to be brittle and to fail earlier than the separators during an external crush event. Thus, the understanding of mechanical failure mechanism for LIB electrodes (anode and cathode) is critical for the safety design of LIB cells. In this paper, we present experimental and numerical studies on the constitutive behavior and progression of failure in LIB electrodes. Mechanical tests were designed and conducted to evaluate the constitutive properties of porous electrodes. Constitutive models were developed to describe the stress-strain response of electrodes under uniaxial tensile and compressive loads. The failure criterion and a damage model were introduced to model their unique tensile and compressive failure behavior. The failure mechanism of LIB electrodes was studied using the blunt rod test on dry electrodes, and numerical models were built to simulate progressive failure. The different failure processes were examined and analyzed in detail numerically, and correlated with experimentally observed failure phenomena. Finally, the test results and models improve our understanding of failure behavior in LIB electrodes, and provide constructive insights on future development of physics-based safety design tools for battery structures under mechanical abuse.

25 ENERGY STORAGE↗
DOE OSTI2024

Evaluating direct vessel injection accident-event progression of AP1000 and key figures of merit to support the design and development of water-cooled small modular reactors

The passive safety systems (PSSs) within water-cooled reactors are meticulously engineered to function autonomously, requiring no external power source or manual intervention. They depend exclusively on inherent natural forces and the fundamental principles of reactor physics, such as gravity, natural convection, and phase changes, to manage, alleviate, and avert the release of radioactive materials into the environment during accident scenarios like a loss-of-coolant accident (LOCA). PSSs are already integrated into such operating commercial reactors as the Advanced Pressurized Reactor-1000 MWe (AP1000) and the Water-Water Energetic Reactor-1200 MWe (WWER-1200) are adopted in most of the upcoming small modular reactor (SMR) designs. Examples of water-cooled SMR PSSs are the passive emergency core-cooling system (ECCS), passive containment cooling system (PCCS), and passive decay-heat removal system, the designs of which vary based on reactor system-design requirements. However, understanding the accident-event progression and phases of a LOCA is pivotal for adopting a specific PSS for a new SMR design. This study covers the accident-event progression for direct vessel injection (DVI) small-break loss-of-coolant accident (SB-LOCA), associated physics phenomena, knowledge gaps, and important figures of merit (FOMs) that may need to be evaluated and assessed to validate thermal-hydraulics models with an available experimental dataset to support new SMR design and development.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2015

Integration of progressive hedging and dual decomposition in stochastic integer programs

We present a method for integrating the Progressive Hedging (PH) algorithm and the Dual Decomposition (DD) algorithm of Carøe and Schultz for stochastic mixed-integer programs. Based on the correspondence between lower bounds obtained with PH and DD, a method to transform weights from PH to Lagrange multipliers in DD is found. Fast progress in early iterations of PH speeds up convergence of DD to an exact solution. As a result, we report computational results on server location and unit commitment instances.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Deep learning-based model for progress variable dissipation rate in turbulent premixed flames

A deep neural network (DNN) based large eddy simulation (LES) model for progress variable dissipation rate in turbulent premixed flames is presented. The DNN model is trained using filtered data from direct numerical simulations (DNS) of statistically planar turbulent premixed flames with n-heptane as fuel. Training data was comprised of flames with varying turbulence levels leading to a range of Karlovitz numbers. Through a-priori tests the DNN model is shown to predict the subfilter contribution to progress variable dissipation rate accurately over a range of filter widths and for all Karlovitz numbers examined in this study. Superior performance of the DNN model relative to an established physics-based model is also demonstrated. Additionally, transferability of the DNN model is highlighted by a-priori evaluation of the model using filtered DNS data from multiple cases with different Karlovitz numbers and fuel species than those that were used for training the model.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2018

Modeling Alzheimer’s Disease Progression with Fused Laplacian Sparse Group Lasso

Alzheimer’s disease (AD), the most common type of dementia, not only imposes a huge financial burden on the health care system, but also a psychological and emotional burden on patients and their families. There is furthermore an urgent need to infer trajectories of cognitive performance over time and identify biomarkers predictive of the progression. Here, we introduce the multi-task learning with fused Laplacian sparse group lasso model, which can identify biomarkers closely related to cognitive measures due to its sparsity-inducing property, and model the disease progression with a general weighted (undirected) dependency graphs among the tasks. An efficient alternative directions method of multipliers based optimization algorithm is derived to solve the proposed non-smooth objective formulation. The effectiveness of the presented model is demonstrated by its superior prediction performance over multiple state-of-the-art methods and accurate identification of compact sets of cognition-relevant imaging biomarkers that are consistent with prior medical studies.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2011

International Linear Collider-A Technical Progress Report

The International Linear Collider: A Technical Progress Report marks the halfway point towards the Global Design Effort fulfilling its mandate to follow up the ILC Reference Design Report with a more optimised Technical Design Report (TDR) by the end of 2012. The TDR will be based on much of the work reported here and will contain all the elements needed to propose the ILC to collaborating governments, including a technical design and implementation plan that are realistic and have been better optimised for performance, cost and risk. We are on track to develop detailed plans for the ILC, such that once results from the Large Hadron Collider (LHC) at CERN establish the main science goals and parameters of the next machine, we will be in good position to make a strong proposal for this new major global project in particle physics. The two overriding issues for the ILC R&D programme are to demonstrate that the technical requirements for the accelerator are achievable with practical technologies, and that the ambitious physics goals can be addressed by realistic ILC detectors. This GDE interim report documents the impressive progress on the accelerator technologies that can make the ILC a reality. It highlights results of the technological demonstrations that are giving the community increased confidence that we will be ready to proceed with an ILC project following the TDR. The companion detector and physics report document likewise demonstrates how detector designs can meet the ambitious and detailed physics goals set out by the ILC Steering Committee. LHC results will likely affect the requirements for the machine design and the detectors, and we are monitoring that very closely, intending to adapt our design as those results become available.

43 PARTICLE ACCELERATORS↗
DOE OSTI2015

Biogas Opportunities Roadmap Progress Report

In support of the Obama Administration's Climate Action Plan, the U.S. Department of Energy, the U.S. Environmental Protection Agency, and U.S. Department of Agriculture jointly released the Biogas Opportunities Roadmap Progress Report, updating the federal government's progress to reduce methane emissions through biogas systems since the Biogas Opportunities Roadmap was completed by the three agencies in July 2014. The report highlights actions taken, outlines challenges and opportunities, and identifies next steps to the growth of a robust biogas industry.

09 BIOMASS FUELS↗
DOE OSTI2019

MicroRNAs as biomarkers of diabetic retinopathy and disease progression

Diabetes mellitus, together with its complications, has been increasing in prevalence worldwide. Its complications include cardiovascular disease (e.g., myocardial infarction, stroke), neuropathy, nephropathy, and eye complications (e.g., glaucoma, cataracts, retinopathy, and macular edema). In patients with either type 1 or type 2 diabetes mellitus, diabetic retinopathy is the leading cause of visual impairment or blindness. It is characterized by progressive changes in the retinal microvasculature. The progression from nonproliferative diabetic retinopathy to a more advanced stage of moderate to severe nonproliferative diabetic retinopathy and proliferative diabetic retinopathy occurs very quickly after diagnosis of mild nonproliferative diabetic retinopathy. The etiology of diabetic retinopathy is unclear, and present treatments have limited effectiveness. Currently diabetic retinopathy can only be diagnosed by a trained specialist, which reduces the population that can be examined. A screening biomarker of diabetic retinopathy with high sensitivity and specificity would aid considerably in identifying those individuals in need of clinical assessment and treatment. The majority of the studies reviewed identified specific microRNAs in blood serum/plasma able to distinguish diabetic patients with retinopathy from those without retinopathy and for the progresion of the disease from nonproliferative diabetic retinopathy to proliferative diabetic retinopathy. In addition, certain microRNAs in vitreous humor were dysregulated in proliferative diabetic retinopathy compared to controls. A very high percentage of patients with diabetic retinopathy develop Alzheimer’s disease. Thus, identifying diabetic retinopathy by measurement of suitable biomarkers would also enable better screening and treatment of those individuals at risk of Alzheimer’s disease.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

MicroRNAs in blood and cerebrospinal fluid as diagnostic biomarkers of multiple sclerosis and to monitor disease progression

Multiple sclerosis is a chronic autoimmune disease of the central nervous system. It is the main cause of non-traumatic neurological disability in young adults. Multiple sclerosis mostly affects people aged 20–50 years; however, it can occur in young children and much older adults. Factors identified in the distribution of MS include age, gender, genetics, environment, and ethnic background. Multiple sclerosis is usually associated with progressive degrees of disability. The disease involves demyelination of axons of the central nervous system and causes brain and spinal cord neuronal loss and atrophy. Diagnosing multiple sclerosis is based on a patient’s medical history including symptoms, physical examination, and various tests such as magnetic resonance imaging, cerebrospinal fluid and blood tests, and electrophysiology. The disease course of multiple sclerosis is not well correlated with the biomarkers presently used in clinical practice. Blood-derived biomarkers that can detect and distinguish the different phenotypes in multiple sclerosis may be advantageous in personalized treatment with disease-modifying drugs and to predict response to treatment. The studies reviewed have shown that the expression levels of a large number of miRNAs in peripheral blood, serum, exosomes isolated from serum, and cerebrospinal fluid are altered in multiple sclerosis and can distinguish the disease phenotypes from each other. Further studies are warranted to independently validate these findings so that individual or pairs of miRNAs in serum or cerebrospinal fluid can be used as potential diagnostic markers for adult and pediatric multiple sclerosis and for monitoring disease progression and response to therapy.

60 APPLIED LIFE SCIENCES↗