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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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135 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

What fuel properties enable higher thermal efficiency in spark-ignited engines?

The Co-Optimization of Fuels and Engines (Co-Optima) initiative from the US Department of Energy aims to co-develop fuels and engines in an effort to maximize energy efficiency and the utilization of renewable fuels. Many of these renewable fuel options have fuel chemistries that are different from those of petroleum-derived fuels. Because practical market fuels need to meet specific fuel-property requirements, a chemistry-agnostic approach to assessing the potential benefits of candidate fuels was developed using the Central Fuel Property Hypothesis (CFPH). The CFPH states that fuel properties are predictive of the performance of the fuel, regardless of the fuel's chemical composition. In order to use this hypothesis to assess the potential of fuel candidates to increase efficiency in spark-ignition (SI) engines, the individual contributions towards efficiency potential in an optimized engine must be quantified in a way that allows the individual fuel properties to be traded off for one another. This review article begins by providing an overview of the historical linkages between fuel properties and engine efficiency, including the two dominant pathways currently being used by vehicle manufacturers to reduce fuel consumption. Then, a thermodynamic-based assessment to quantify how six individual fuel properties can affect efficiency in SI engines is performed: research octane number, octane sensitivity, latent heat of vaporization, laminar flame speed, particulate matter index, and catalyst light-off temperature. The relative effects of each of these fuel properties is combined into a unified merit function that is capable of assessing the fuel property-based efficiency potential of fuels with conventional and unconventional compositions.

42 ENGINEERING↗
DOE OSTI2020

Challenges and Opportunities in Turning Large U.S. Archives of Analog Seismograms into a Modern Usable Resource

Abstract Quantitative seismology is based firmly on the analysis of actual ground motions, and the transition to digital recording in the 1980s enabled sophisticated new capabilities to extract useful results from waveforms. With some effort, these tools can also be applied to analog records. Focusing on assets available within U.S. institutions, we review the necessary steps and the challenges in enabling “data rescue”—that is, preserving the scientific information latent in large analog seismogram archives and making it usable. They include: determining what assets are available (the analog seismogram archives held by various institutions, with associated metadata on instrument responses, station locations, and timing information); developing a consensus on the top level of a triage process (which analog records most definitely should be rescued?); deciding the level of quality needed in copying original seismograms to media suitable for digitizing; assessing the relative merits of scanning and digitizing; and, the need for a community service in distributing scans and digital records, as they accumulate. The necessary level of effort can benefit from practical experience. For example, specific studies have used digitized versions of analog recordings to model earthquake sources and assess seismic hazard. Other studies have used them to gain experience with nuclear explosion signals recorded at regional distances, noting that regional signals enable explosions to be monitored down to levels much lower than those attainable teleseismically. The opportunities presented by large archives of analog seismograms include the insights they present to current and future seismologists studying earthquakes and explosions, into the practical areas of assessing seismic hazard, monitoring for test ban compliance down to low explosion yields—and prompt characterization of actual explosions should they occur, as well the traditional academic pursuit of a better understanding of earthquake physics.

Geochemistry & Geophysics↗
DOE OSTI2025

Implementation of Stochastic Gradient Descent in an Automated Glow Peak Identification Software for Multiple Thermoluminescent Dosimeter Types

A glow-curve analysis code was previously developed in C++ to analyze thermoluminescent dosimeter glow curves using automated peak detection while applying a first-order kinetics model. A newer version of this code was implemented to improve the automated peak detection and curve fitting models. The Stochastic Gradient Descent Algorithm was introduced to replace the prior approach of taking first and second-order derivatives for peak detection. Additionally, early stopping mechanisms were invoked to improve the previously used Levenberg-Marquardt Algorithm employed for curve fitting. The two software versions were compared through glow curve analysis of different thermoluminescent dosimeter materials and calculation of the corresponding figures of merit. Altogether improvements were shown, namely an increase in the number of peaks detected and a reduction of the mean figure of merit by approximately 46%.

137Cs↗
DOE OSTI2023

A research agenda for the science of actionable knowledge: Drawing from a review of the most misguided to the most enlightened claims in the science-policy interface literature

Linking science with action affords a prime opportunity to leverage greater societal impact from research and increase the use of evidence in decision-making. Success in these areas depends critically upon processes of producing and mobilizing knowledge, as well as supporting and making decisions. For decades, scholars have idealized and described these social processes in different ways, resulting in numerous assumptions that now variously guide engagements at the interface of science and society. We systematically catalog these assumptions based on prior research on the science-policy interface, and further distill them into a set of 26 claims. We then elicit expert perspectives (n = 16) about these claims to assess the extent to which they are accurate or merit further examination. Out of this process, we construct a research agenda to motivate future scientific research on actionable knowledge, prioritizing areas that experts identified as critical gaps in understanding of the science-society interface. The resulting agenda focuses on how to define success, support intermediaries, build trust, and evaluate the importance of consensus and its alternatives – all in the diverse contexts of science-society-decision-making interactions. We further raise questions about the centrality of knowledge in these interactions, discussing how a governance lens might be generative of efforts to support more equitable processes and outcomes. We offer these suggestions with hopes of furthering the science of actionable knowledge as a transdisciplinary area of inquiry.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

Review—Meeting Fuel Cell Catalyst Requirements for Heavy-Duty Vehicle Applications

Catalyst requirements for proton exchange membrane (PEM) fuel cells differ by applications. Commercial heavy-duty vehicle (HDV) applications consume more H 2 fuel and demand higher durability than many others and the total cost of ownership (TCO) of the vehicle is largely related to the performance and durability of catalysts. This article is written to bridge the gap between the industrial requirements and academic activity for advanced cathode catalysts with an emphasis on durability. From a materials perspective, the underlying nature of the carbon support, Pt-alloy crystal structure, stability of the alloying element, cathode ionomer volume fraction, and catalyst-ionomer interface play a critical role in improving performance and durability. We provide our perspective on four major approaches, namely, mesoporous carbon supports, ordered PtCo intermetallic alloys, thrifting ionomer volume fraction, and shell-protection strategies that are currently being pursued. While each approach has its merits and demerits, their key developmental needs for future are highlighted.

Ramaswamy, Nagappan (ORCID:0000000234302758)↗
DOE OSTI2023

Laboratory Directed Research and Development Program FY 2020 Annual Summary of Completed Projects

ORNL has established a program with four complementary subprograms to meet its LDRD objectives and to fulfill the particular needs of the laboratory. A provision for multiple routes of access to ORNL LDRD funds maximizes the likelihood that novel ideas with scientific and technological merit will be recognized and supported. The ORNL LDRD Program comprises the following four subprograms: 1) The Director’s R&D Program supports projects that advance research frontiers, capabilities, and expertise at ORNL in key strategic areas. 2) The Seed Program supports innovative high-risk/high-reward research to the proof-of-principle stage. 3) The Strategic Hire Program supports the research of key new staff whose expertise and capabilities address a critical strategic need for the laboratory. 4) The Distinguished Staff Fellowships assist the laboratory in bringing in exceptional early-career scientists to refresh and expand its scientific and technical expertise. The total ORNL LDRD Program budget authorized by DOE for FY 2020 was $\$$55 million. FY 2020 allocations totaled $\$$52.5 million and supported 153 projects. An additional $\$$95,827 was allocated to administrative costs for conducting proposal reviews. Overall, 96.4% of the allocated funds were spent. The expenditure of $\$$50.6 million was about 3.2% of the laboratory’s total budget of $\$$1,572 million for operating and capital expenses, which is well below the maximum of 6% allowed by DOE Order 413.2C and is in accordance with Section 309 of Division D of the Consolidated Appropriations Act.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2024

Performance analysis of photodetectors based on 2D materials and heterostructures

The unprecedented demand for sophisticated, self-powered, compact, ultrafast, cost-effective, and broadband light sensors for a myriad of applications has spurred a lot of research, precipitating in a slew of studies over the last decade. Apart from the photosensing ability of an active element in the light sensor, the device architecture is crucial in terms of photoinduced charge carrier generation and separation. Since the inception of graphene and the subsequent research growth in the atomically thin 2D materials, researchers have developed and adapted different families of 2D materials and device architectures, including single element 2D, 0D/2D, 2D/2D, 1D/2D stacked structures, and so on. Here this review discusses the recent reports on the light-sensing properties of various 2D materials, their heterostructures, and characteristics applicable to the ultraviolet-near infrared (UV-NIR), short-wave IR (SWIR), mid-wave IR (MWIR), long-wave IR (LWIR), and terahertz (THz) spectral ranges. It highlights the novelty of the burgeoning field, the heightened activity at the boundaries of engineering and materials science, particularly in the generation of charge carriers, their separation, and extraction, and the increased understanding of the underpinning science through modern experimental approaches. Devices based on the simultaneous effects of the pyro-phototronic effect (PPE) and the localized surface plasmon resonance (LSPR) effect, the photothermoelectric effect (PTE)-assisted photodetectors (PDs), waveguide-integrated silicon-2D PDs, metal-2D-metal PDs, and organic material PDs are examined rigorously. Theoretical treatment utilizing various computational approaches to investigate 2D materials and heterostructures for photodetection applications is also briefly discussed. At the end, current challenges and solutions to enhance the figures of merit of photodetectors are proposed.

2D transition metal chalcogenides↗
DOE OSTI2025

Moving beyond post hoc explainable artificial intelligence: a perspective paper on lessons learned from dynamical climate modeling

AI models are criticized as being black boxes, potentially subjecting climate science to greater uncertainty. Explainable artificial intelligence (XAI) has been proposed to probe AI models and increase trust. In this review and perspective paper, we suggest that, in addition to using XAI methods, AI researchers in climate science can learn from past successes in the development of physics-based dynamical climate models. Dynamical models are complex but have gained trust because their successes and failures can sometimes be attributed to specific components or sub-models, such as when model bias is explained by pointing to a particular parameterization. We propose three types of understanding as a basis to evaluate trust in dynamical and AI models alike: (1) instrumental understanding, which is obtained when a model has passed a functional test; (2) statistical understanding, obtained when researchers can make sense of the modeling results using statistical techniques to identify input–output relationships; and (3) component-level understanding, which refers to modelers' ability to point to specific model components or parts in the model architecture as the culprit for erratic model behaviors or as the crucial reason why the model functions well. We demonstrate how component-level understanding has been sought and achieved via climate model intercomparison projects over the past several decades. Such component-level understanding routinely leads to model improvements and may also serve as a template for thinking about AI-driven climate science. Currently, XAI methods can help explain the behaviors of AI models by focusing on the mapping between input and output, thereby increasing the statistical understanding of AI models. Yet, to further increase our understanding of AI models, we will have to build AI models that have interpretable components amenable to component-level understanding. We give recent examples from the AI climate science literature to highlight some recent, albeit limited, successes in achieving component-level understanding and thereby explaining model behavior. The merit of such interpretable AI models is that they serve as a stronger basis for trust in climate modeling and, by extension, downstream uses of climate model data.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Composite Analysis for Low-Level Waste Disposal in the Hanford Site Central Plateau (FY 2020) (Rev. 2)

This document provides an updated Hanford Site composite analysis (CA). A Hanford Site CA was prepared and issued in 1998 (PNNL-11800) with an addendum provided in 2002 (PNNL-11800 Addendum 1). The CA was approved in 2002 (Frei, 2002) and has been maintained (DOE/RL-2000-29 and subsequent revisions) to support low-level waste disposal performance assessments (PAs) and disposal authorizations for facilities at the Hanford Site, including the following: Continued operation of the Environmental Restoration Disposal Facility (ERDF) and the 200 East and 200 West Low-Level Burial Grounds; Construction of the Integrated Disposal Facility (IDF); Forthcoming closure of tank residual waste systems such as Waste Management Area (WMA) C. The CA maintenance program resulted in a determination in 2015 (DOE/RL-2015-66) that the Hanford Site CA needed an update for the following reasons: While the initial Hanford Site CA has been maintained since 2001, the accumulation of basis changes reported in the annual summary reports over the succeeding 14 years merit evaluation in an updated analysis; The U.S. Department of Energy (DOE) Headquarters requested in a memorandum in 2015 (Gilbertson and Marcinowski, 2015) that “as soon as the relevant PAs are complete, the CA will be revised to account for all of the new information.” This updated Hanford Site CA accounts for the following new information: 1. Inclusion of a detailed Hanford Site baseline disposition that projects remedial activities through site closure. There have been significant changes through decision making in the Comprehensive Environmental Response, Compensation, and Liability Act of 1980 (CERCLA) process that were not available when the original CA was produced; 2. Inclusion of an updated inventory basis, new modeling capabilities, and new decisions reached in the associated record of decision (ROD) that was provided by issuance of DOE/EIS-0391 in fiscal year (FY) 2013. Development of a Hanford Site groundwater model from the baseline provided in a technical transfer of models for the Final Tank Closure and Waste Management Environmental Impact Statement (DOE/EIS-0391) commenced in FY 2014 and resulted in the plateau-to-river (P2R) groundwater flow model that is used in this updated Hanford Site CA; 3. Accounting for pump and treat systems, which were not evaluated in the initial CA. Pump and treat systems have had significant impact on groundwater flow system behavior, contaminant transport, and contaminant removal from Hanford Site groundwater. This process is accounted for in the use of the P2R model for this updated Hanford Site CA; 4. Inclusion of water-level data collected since the initial CA was completed. Data collected as the unconfined aquifer water levels continue to recede since the cessation of large liquid discharges in the late 1990s have led to marked improvement in understanding of the flow system for future conditions, particularly regarding northward flow potential in the critical Gable Gap area. The calibration in the latest version of the P2R model accounts for this information; 5. Inclusion of results from the revised ERDF PA completed in 2013 (WCH-5209) that account for updated inventory and expansion of the ERDF facility to about twice the size that was evaluated in the original CA; 6. Use of updated geoframeworks to provide the structural basis for numerical fate and transport models in the groundwater pathway of this updated CA. The geologic basis for groundwater models has continued to improve with additional data collection and interpretation with the creation and maintenance of the Hanford South Geoframework and the Central Plateau Vadose Zone Geoframework tools; 7. Incorporation of updated tank residual inventory estimates. Tank residual inventory estimates have improved with the incorporation of tank retrieval inventory data for those tanks that have completed retrieval. The CA inventory data package includes this updated information; 8. Incorporation of WMA C PA results. Two additional PAs for tank farm closure decisions are in preparation during the period required to prepare an updated Hanford Site CA: WMA C (FY 2016) and WMA A-AX (in preparation). The WMA C PA results are incorporated into the updated Hanford Site CA, and its grouted residuals model is used as the basis for a release model to account for the other tank farm systems modeling in this updated CA; 9. An update to the IDF PA was submitted in FY 2017 and has been reviewed and approved. The results of the IDF PA are incorporated into this updated CA; 10. Updated risk assessment scenarios. The risk assessment scenarios currently in use for Hanford Site CERCLA and Resource Conservation and Recovery Act of 1976 (RCRA) analyses differ from those evaluated in the initial Hanford Site CA. The representative person exposure scenario evaluated in this updated Hanford Site CA is consistent with recent PAs and CERCLA and RCRA analyses as the Hanford Site. This updated Hanford Site CA provides the following: A comparison of the updated Hanford Site CA all-pathway dose results with the performance measures during the compliance period, which is assumed to begin with site closure in calendar 2070 with the last scheduled disposal action and continue for 1,000 years postclosure (to calendar year 3069); A comparison of Hanford Site CA all-pathway dose results with the performance measures during the postcompliance period to address potential peaks beyond the compliance period. This is accomplished by evaluating dose in the period for 9,000 years following the compliance period (i.e., from calendar year 3070 to 12070).

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗