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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 541 records · Page 30
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Texas A&M University in the JET Collaboration - Final Report

This final report summarizes the work done by PIs at Texas A&M University within the JET Topical Collaboration. The main focus of the group at Texas A&M has been the development and implementation of a hadronization model suitable to calculate hadronization of jet showers in heavy ion collisions event by event. The group successfully developed a hybrid model of parton recombination and remnant string fragmentation including recombination with thermal partons. A code realizing this model was developed and shared with other JET members. In addition, the group at Texas A&M worked on both open and hidden heavy flavor probes. In particular, they developed a description of heavy flavor hadronization based on recombination, and consistent with in-medium scattering rates of heavy quarks, and suggested the D s meson as a precise probe of the hadronization mechanism. Another noteworthy focus of their work was electromagnetic probes, in particular, dileptons and photons from interactions of jets with the medium. In the soft sector the group has made several contributions to modern topics, e.g. the splitting of elliptic flow between isospin partners and the role of the initial strong gluon fields.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Integrating Crack Detection and Pipe Shape Optimization for Enhanced Sewage System Durability

Crack detection in underground reinforced concrete pipes has been essential in determining the state of stormwater infrastructure. Detection models have been implemented for detecting cracks and other defects in pipes using CCTV footage for stormwater drainage systems. In addition, Finite element models have been used to determine optimum shapes and pipe thickness for different boundary conditions such as header pipes in power plants. The concept of shape optimization emerges as a crucial factor in power plant design and operation, with the potential to maximize performance while minimizing the use of materials. Shape optimization not only enhances efficiency but also contributes to reducing the environmental footprint. This paper discusses the integration of both topics by using the cracks detected in underground pipes as boundary conditions for shape optimization of the pipes. A machine learning model has been developed which uses limited data for training and outlines the location of detected cracks. A shape optimization methodology is proposed in which ANSYS modules are used to analyze fluid flow and then optimize the shape of the pipe. The crack detection model developed has been applied to a crack detected in lab setting and machine learning model used has an accuracy of 98% using a random forest algorithm.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2011

Paradigm Change: Alternate Approaches to Constitutive and Necking Models for Sheet Metal Forming

This paper reviews recent work proposing paradigm changes for the currently popular approach to constitutive and failure modeling, focusing on the use of non-associated flow rules to enable greater flexibility to capture the anisotropic yield and flow behavior of metals using less complex functions than those needed under associated flow to achieve that same level of fidelity to experiment, and on the use of stress-based metrics to more reliably predict necking limits under complex conditions of non-linear forming. The paper discusses motivating factors and benefits in favor of both associated and non-associated flow models for metal forming, including experimental, theoretical, and practical aspects. This review is followed by a discussion of the topic of the forming limits, the limitations of strain analysis, the evidence in favor of stress analysis, the effects of curvature, bending/unbending cycles, triaxial stress conditions, and the motivation for the development of a new type of forming limit diagram based on the effective plastic strain or equivalent plastic work in combination with a directional parameter that accounts for the current stress condition.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Final Report on "Collaborative Research to Narrow Uncertainties in Precipitation and the Hydrological Cycle in Climate Models"

The central objectives of this work have been to explore and improve the depiction of precipitation and related processes in climate models by developing and analyzing observations and their gridded analyses, and developing new approaches and metrics. All three groups worked with the NCAR-based Community Earth System Model (CESM) and international community Climate Model Inter-comparison Project version 5 (CMIP5) models in various ways. At NCAR and SUNYA an initial focus was on the observational record, including updating of the river discharge dataset. A major focus at NCAR was extensive work on new datasets of hourly precipitation from CMORPH (observations) and CESM, and commentary on and validation of the CESM. SUNYA contributed to the comparison and evaluation of existing precipitation products widely used in climate research, the analysis of precipitation characteristics in CESM and other CMIP5 models, and decadal precipitation variability associated with decadal variability. At NCAR and SUNYA work was focused on the frequency and intensity of precipitation, including their dependence on the temporal and spatial resolution of the data used to calculate the frequency and intensity, as well as additional analyses on the effects of precipitation data uncertainties on the estimated historical drying trends. LLNL focused on the diurnal cycle. New insights have resulted in the characteristics of precipitation (frequency, intensity, amount, duration, diurnal cycle, covariability in space and time) and evaluation of these in models. In general models perform poorly and this provides a much-needed focus on what aspects of models are greatly in need of improvement. A substantial number of papers have now been published on these topics. The focus on the characteristics of precipitation and not just amount also provides a natural entrée into examining the extremes of precipitation, that are very important to the general public in terms of impacts. Examples are the deluges from Florence and Harvey, and extensive work has been performed on the latter. On the other side of the coin, considerable work has been performed on dry spells and drought, including improvements in a drought index. There has been considerable outreach to the general public, especially through the media, but also via talks and lectures, and a strong educational component at SUNYA. For example, the Harvey paper has an altimetrics rating of 827 and is the highest for any paper from that journal, it is at the 99th percentile of all papers of the same age, and is in the top 95 percent of all papers. The energy cycle and ocean heat content has been another focus. The entire atmospheric energy cycle has been reformulated and applied to the latest data to include effects from the enthalpy of precipitation. Relationships between ocean heat content and sea level rise have also been extensively explored in observations and models, with new insights into the role of Mount Pinatubo volcanic eruption on distorting and hiding the accelerating sea level rise. This work has been also widely featured in news media. The “year without a summer” has also been explored in the past using models, and how changes in the vertical structure and stability of the ocean with a warming climate may influence a future such volcanic event by amplifying the surface temperature response.

58 GEOSCIENCES↗
DOE OSTI2016

Boiling Closure Model Validation/Development Effort with TAMU Experimental Data

This report describes a model validation and developmental effort in INL based on the analysis of experimental data taken from TAMU subcooled flow boiling facility. This report first describes briefly the test loop, experimental strategy, measurement techniques, data quality achieved, and test boundary conditions. Then, two main topics are discussed based on the experimental observation, bubble departure frequency and sliding bubble characteristics. The comparison of experimental data with the prediction of bubble departure frequency models shows that the predictive capability of existing models depends strongly on flow conditions. Also, the best performance region of each bubble departure frequency model could be determined from this analysis. Another critical achievement through this study is that the limitation of existing CFD boiling models dealing with sliding bubble effect was clearly identified. Specifically, the experimental observation indicates that the wall area influenced by sliding bubbles is not just a function of bubble size, but also depends strongly on sliding bubble trajectory and sliding distance. As a result, the bubble influence factor ( K ) for the small size of sliding bubbles was often found substantially higher than those reported in literature. In this regard, an effort is currently being made in INL to develop a new model to predict the sliding bubble effect on wall heat transfer based on the insight achieved from TAMU subcooled flow boiling experiment.

42 ENGINEERING↗
DOE OSTI2018

Characterization of C-ring component assembly in flagellar motors from amino acid coevolution

Bacterial flagellar motility, an important virulence factor, is energized by a rotary motor localized within the flagellar basal body. The rotor module consists of a large framework (the C-ring), composed of the FliG, FliM and FliN proteins. FliN and FliM contacts the FliG torque ring to control the direction of flagellar rotation. We report that structure-based models constrained only by residue coevolution can recover the binding interface of atomic X-ray dimer complexes with remarkable accuracy (approx. 1 Å RMSD). We propose a model for FliM–FliN heterodimerization, which agrees accurately with homologous interfaces as well as in situ cross-linking experiments, and hence supports a proposed architecture for the lower portion of the C-ring. Furthermore, this approach allowed the identification of two discrete and interchangeable homodimerization interfaces between FliM middle domains that agree with experimental measurements and might be associated with C-ring directional switching dynamics triggered upon binding of CheY signal protein. Our findings provide structural details of complex formation at the C-ring that have been difficult to obtain with previous methodologies and clarify the architectural principle that underpins the ultra-sensitive allostery exhibited by this ring assembly that controls the clockwise or counterclockwise rotation of flagella.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2011

Recent Developments in SHERPA

Some recent QCD-related developments in the SHERPA event generator are presented. In the past decades, event generators such as PYTHIA [1, 2] and HERWIG [3, 4] have been central for nearly all physics analyses at particle physics experiments at the high-energy frontier. This will also hold true at the LHC, where a large number of interesting signals for new particles or new phenomena (the Higgs boson or any other manifestation of the mechanism behind electro-weak symmetry breaking, supersymmetry, extra dimensions etc.) is hampered by a plethora of severe, sometimes overwhelming backgrounds. Nearly all of them are largely influenced by QCD. Therefore it seems fair to say that the success of the LHC in finding new physics may very well depend on a deep and detailed understanding of old physics, like QCD. Examples for this include, among others, the central-jet veto for the vector boson fusion channel for Higgs production or topologies, where gauge bosons emerge in association with many jets, a background for many search channels. In a reflection on increased needs by the experimental community, aiming at higher precision, incorporation of new physics models and so on, the work horses of old have undergone serious renovation efforts, resulting in new, improved versions of the respective codes, namely PYTHIA8 [5] and HERWIG++ [6]. In addition a completely new code, SHERPA [7], has been constructed and is in the process of maturing. The status of this code is the topic of this contribution. SHERPA's hallmark property is the inclusion of higher-order tree-level QCD contributions, leading to an improved modelling of jet production. They are introduced through a full-fledged matrix element generator, AMEGIC++ [8], which is capable of generating matrix elements and corresponding phase space mappings for processes with multi-particle final states in various models, including the Standard Model, anomalous gauge triple and quadruple couplings according to [9, 10], the Minimal Supersymmetric Standard Model with Feynman rules from [11], the ADD-model of extra dimensions [12, 13], and a model with an extra U(1) singlet coupling to the Higgs boson only [14]. The code has been thoroughly tested and validated [15]. This code, however, is limited, especially in the treatment of many ({ge} 6) external QCD particles. Therefore, in the near future, SHERPA will incorporate another, new matrix element generator, COMIX, which is based on Berends-Giele recursion relations [16] and color-dressing [17] rather than color-ordering. In Tabs. 1 and 2 some example cross sections for gg {yields} ng at fixed energies and pp {yields} b{bar b} + n jets obtained with this program are exhibited and compared to those from other programs. In addition, concerning the calculation of higher-order matrix elements and cross sections, there have been first steps towards an automation of such calculations at truly next-to leading order accuracy. They manifest themselves in the implementation of a procedure [19] to fully automatically construct and evaluate Catani-Seymour dipole subtraction terms [20] for the real part of such NLO calculations. The results from the matrix element calculations are merged with the subsequent parton shower through the formalism of [21, 22]. The results of its implementation in SHERPA [23] has recently been compared with other algorithms [24]. Although there remains some dispute about the theoretical equivalence of the different approaches, the overall results show satisfying agreement with each other, such that they can be used with confidence for data analysis.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Model-Based Diagnostics and Mitigation of Cyber Threats

The report summarizes key tasks performed to develop a toolkit for detecting cyber-attack events in instrumentation and control (I&C) systems of nuclear power plants. The toolkit connects the state-of-the-art GPWR Simulator with the RELAP5 code providing best-estimate nuclear steam supply system (NSSS) analyses, via the application programming interface (API), and allows users to introduce potential cyber-attack scenarios into power plant operational simulation. This summary for the project reflects topical reports submitted during the project as well as a journal paper published in 2022. The focus areas of the summary include: (1) modeling I&C systems for the AP1000 Generation III+ nuclear plant and GPWR simulator, (2) simulation and monitoring of plant response to cyber-attack events, (3) API structure for the toolkit interfacing the GPWR simulator and RELAP5 code, and (4) restructuring of the three-loop NSSS software of GPWR to model the two-loop AP1000 structure. Discussed in some details are (a) the attack tree analysis assessing the susceptibility of the AP1000 I&C system, resulting in reactor trips, in terms of the attack possibility and component sensitivity and (b) realistic estimation of the time to steam generator trip due to cyber-intrusions in the GPWR Simulator. Finally, sample demonstrations of the cyber-security tool kit, in the form of the GPWR-RELAP5 API, are summarized.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

Data Driven Approach to Public Opinion Mining on Autonomous Vehicles: Sentiment Analysis of Social Media Comments Using Large Language Models

In the realm of online identity, social media has emerged as a rich and dynamic source of user-generated content, making it an invaluable resource for understanding public sentiment on a wide range of topics. Individuals often share their raw emotions and candid opinions on these platforms without fear of judgment or backlash. In this study, we conduct a sentiment analysis on user comments collected from various online platforms, with a specific focus on discussions surrounding autonomous vehicles. Leveraging the capabilities of large language models (LLMs), we classify each comment into one of five sentiment categories: Very Negative, Negative, Neutral, Positive, and Very Positive. Our approach demonstrates the effectiveness of LLMs in capturing nuanced contextual sentiment, offering a scalable and state-of-the-art alternative to traditional manual annotation methods. The results reveal key trends and insights into public perception, enabling a deeper understanding of how autonomous vehicle technologies are received by the online community. Our findings underscore the dynamic nature of public sentiment, which is shaped not only by advances in autonomous vehicle technology but also by contextual events such as regulatory developments, political adjustment and safety incidents.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

DECOVALEX-2023: An international collaboration for advancing the understanding and modeling of coupled thermo-hydro-mechanical-chemical (THMC) processes in geological systems

The DECOVALEX initiative is an international research collaboration (www.decovalex.org), initiated in 1992, for advancing the understanding and modeling of coupled thermo-hydro-mechanical-chemical (THMC) processes in geological systems. DECOVALEX stands for “DEvelopment of COupled Models and VALidation against EXperiments”. The creation of this international initiative was motivated by the recognition that prediction of these coupled effects is an essential part of the performance and safety assessment of geologic disposal systems for radioactive waste and spent nuclear fuel. DECOVALEX emphasizes joint analysis and comparative modeling of the complex perturbations and coupled processes in geologic repositories and how these impact long-term performance predictions. The most recent phase of the DECOVALEX Project, here referred to as DECOVALEX-2023, started in early 2020 and ended in late 2023. More than fifty research teams associated with 17 international DECOVALEX partner organizations participated in the comparative evaluation of eight modeling tasks covering a wide range of spatial and temporal scales, geological formations, and coupled processes. This Virtual Special Issue on DECOVALEX-2023 provides an in-depth overview of these collaborative research efforts and how these have advanced the state-of-the-art of understanding and modeling coupled THMC processes. While primarily focused on radioactive waste, much of the work included here has wider application to many geoengineering topics.

Coupled processes↗
DOE OSTI2012

Community Modeling and Long-Term Predictions of the Integrated Water Cycle. Report from the September 2012 Workshop

Water is a key component of the earth and human systems due to its strong interactions with the energy cycle and its vital roles in the energy-water-land system. Uncertainties in predicting the integrated water cycle can limit our abilities to address the energy and environmental challenges today and in the future. Modeling the integrated water cycle contributes to the Department of Energy’s (DOE) core competencies in integrative modeling, drawing from unique and highly relevant research on cloud, aerosol, terrestrial ecosystem, carbon cycle, and subsurface processes, as well as climate and earth system modeling and integrated assessment modeling. Synthesizing new process knowledge and innovative computational methods in integrated models of the human-earth system can advance predictive capabilities relevant to DOE missions. This report describes the DOE workshop on Community Modeling and Long-Term Predictions of the Integrated Water Cycle, held September 2012 in Washington DC. The workshop serves as a launching point and major organizing event to identify challenges and plan the development of next-generation human-earth system models for improving long-term predictions of the regional-scale integrated water cycle. More specifically, the workshop aims to: identify core modeling capabilities while identifying key research gaps, with an emphasis on improving model fidelity; reveal relevant and critical capabilities and needs for observations, analytical frameworks, and data management that underpin the development, testing, and validation of our main models and model components; engage the research community in strategies for improving synthesis and integration; elucidate opportunities for collaborations within DOE and with other agencies and institutions that have complementary and essential expertise in specific aspects of the water cycle; and improve understanding of the nature and characteristics of long-term scientific information requirements for DOE’s energy and environmental missions and, as appropriate, for mission needs of other partner agencies. The workshop benefited from substantial inputs provided by the broad scientific community and interagency participation. The topical and crosscutting research challenges identified at the workshop have been synthesized into three overarching Science Grand Challenges and three Integrative Modeling Experiments summarized in this report. These challenges represent remarkable opportunities for interagency collaborations to improve predictions of the integrated water cycle for significant scientific and user impacts.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Science of the Van Allen Probes Science Operations Centers

The Van Allen Probes mission operations materialized through a distributed model in which operational responsibility was divided between the Mission Operations Center (MOC) and separate instrument specific SOCs. The sole MOC handled all aspects of telemetering and receiving tasks as well as certain scientifically relevant ancillary tasks. Each instrument science team developed individual instrument specific SOCs proficient in unique capabilities in support of science data acquisition, data processing, instrument performance, and tools for the instrument team scientists. In parallel activities, project scientists took on the task of providing a significant modeling tool base usable by the instrument science teams and the larger scientific community. With a mission as complex as Van Allen Probes, scientific inquiry occurred due to constant and significant collaboration between the SOCs and in concert with the project science team. Planned cross-instrument coordinated observations resulted in critical discoveries during the seven-year mission. Instrument cross-calibration activities elucidated a more seamless set of data products. Specific topics include post-launch changes and enhancements to the SOCs, discussion of coordination activities between the SOCs, SOC specific analysis software, modeling software provided by the Van Allen Probes project, and a section on lessons learned. One of the most significant lessons learned was the importance of the original decision to implement individual team SOCs providing timely and well-documented instrument data for the NASA Van Allen Probes Mission scientists and the larger magnetospheric and radiation belt scientific community.

47 OTHER INSTRUMENTATION↗
DOE OSTI2016

Multimodal Event Detection in Twitter Hashtag Networks

In this study, event detection in a multimodal Twitter dataset is considered. We treat the hashtags in the dataset as instances with two modes: text and geolocation features. The text feature consists of a bag-of-words representation. The geolocation feature consists of geotags (i.e., geographical coordinates) of the tweets. Fusing the multimodal data we aim to detect, in terms of topic and geolocation, the interesting events and the associated hashtags. To this end, a generative latent variable model is assumed, and a generalized expectation-maximization (EM) algorithm is derived to learn the model parameters. The proposed method is computationally efficient, and lends itself to big datasets. Lastly, experimental results on a Twitter dataset from August 2014 show the efficacy of the proposed method.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Generalized Bose–Hubbard Hamiltonians exhibiting a complete non-Hermitian degeneracy

Highlights: • Hot topic: physics with non-Hermitian Hamiltonians. • Computer algebra used to construct new, next-to-BH models. • Degeneracy verification via variable-precision arithmetics. • Unfolding patterns at N>5 (recent problem solved). - Abstract: The method of construction of the tridiagonal and symmetric complex-matrix Hamiltonians H{sup (N)}(z) exhibiting an exceptional-point (EP) degeneracy of the Nth (i.e., maximal) order at a preselected parameter z=z{sup (EPN)}=1 is proposed and tested. In general, the implementation of the method requires the use of computer-assisted symbolic manipulations, especially at the larger matrix dimensions N. The well known PT−symmetric N-by-N-matrix Bose–Hubbard Hamiltonians as well as their recent N≤5 non-Bose–Hubbard alternatives are obtained as special solutions. Several other N≥6 non-Bose–Hubbard models H{sup (N)}(z) exhibiting the maximal EPN degeneracy are also constructed and analyzed in detail. In particular, their z−dependent, real or complex spectra of energies are displayed and discussed near as well as far from z{sup (EPN)}.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Machine learning for international freight transportation management: A comprehensive review

Machine learning (ML) offers a promising avenue for international freight transportation management (IFTM) given its capability to harness the power of data that have become increasingly available to freight transportation researchers and practitioners. This paper conducts a comprehensive investigation of the state-of-the-art in developing ML models for applications to different aspects of IFTM. We start by giving an overview of various fundamental ML methods. Then, how different ML methods have been employed, adapted, and applied to a multitude of subject areas in IFTM are discussed, including demand forecast, operation and asset maintenance, and vehicle trajectory and on-time performance prediction. The potential data sources that may be used to develop ML models are further examined. Subsequently, a synthesis of the exiting work is performed to identify the specific topics addressed in the existing research, ML methods used, the trends of research, and opportunities for further explorations. Four directions for future research are proposed in the end.

Data sources↗
DOE OSTI2015

Advances in refrigeration and heat transfer engineering

This special edition of Science and Technology for the Built Environment (STBE) presents selected high quality papers that were presented at the 15th International Refrigeration and Air Conditioning Conference held at Purdue University during July 14-17 2014. All papers went through the additional review before being finally accepted for publication in this special issue of Science and Technology and the Built Environment. Altogether 20 papers made to this special issue that cover a wide range of topics, including advancements in alternative refrigerants, heat exchangers/heat transfer, nano-fluids, systems design and optimization and modeling approaches. Although CO 2 may perhaps have been the most researched and popular refrigerant in the past decade, R32 is being seriously considered lately as an alternative and environmentally friendly refrigerant for small systems due to its low Global Warming Potential (GWP).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Efficient prediction of time- and angle-resolved photoemission spectroscopy measurements on a nonequilibrium BCS superconductor

We study how time- and angle-resolved photoemission (tr-ARPES) reveals the dynamics of BCS-type, s -wave superconducting systems with time-varying order parameters. Approximate methods are discussed, based on previous approaches to either optical conductivity or quantum dot transport, to enable computationally efficient prediction of photoemission spectra. One use of such predictions is to enable extraction of the underlying order parameter dynamics from experimental data, which is topical given the rapidly growing use of tr-ARPES in studying unconventional superconductivity. The methods considered model the two-time lesser Green's functions with an approximated lesser self-energy that describes relaxation by coupling of the system to two types of baths. The approach primarily used here also takes into consideration the relaxation of the excited states into equilibrium by explicitly including the level-broadening of the retarded and advanced Green's functions. Here, we present equilibrium and nonequilibrium calculations of tr-ARPES spectrum from our model and discuss the signatures of different types of superconducting dynamics.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗