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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Generalized Canonical Polyadic Tensor Decomposition

Tensor decomposition is a fundamental unsupervised machine learning method in data science, with applications including network analysis and sensor data processing. This work develops a generalized canonical polyadic (GCP) low-rank tensor decomposition that allows other loss functions besides squared error. For instance, we can use logistic loss or Kullback--Leibler divergence, enabling tensor decomposition for binary or count data. We present a variety of statistically motivated loss functions for various scenarios. We provide a generalized framework for computing gradients and handling missing data that enables the use of standard optimization methods for fitting the model. Furthermore, we demonstrate the flexibility of the GCP decomposition on several real-world examples including interactions in a social network, neural activity in a mouse, and monthly rainfall measurements in India.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1978

Silicon ribbon technology assessment 1978-1986 - A computer-assisted analysis using PECAN

The paper presents a 1978-1986 economic outlook for silicon ribbon technology based on the capillary action shaping technique. The outlook is presented within the framework of two sets of scenarios, which develop strategy for approaching the 1986 national energy capacity cost objective of $0.50/WE peak. The PECAN (Photovoltaic Energy Conversion Analysis) simulation technique is used to develop a 1986 sheet material price ($50/sq m) which apparently can be attained without further scientific breakthrough.

Kran, A.↗
NASA NTRS1983

Theory of interstellar medium diagnostics

The theoretical interpretation of observed interplanetary resonance luminescence patterns is used as one of the must promising methods to determine the state of the local interstellar medium (LISM). However, these methods lead to discrepant results that would be hard to understand in the framework of any physical LISM scenario. Assuming that the observational data are reliable, two possibilities which could help to resolve these discrepancies are discussed: (1) the current modeling of resonance luminescence patterns is unsatisfactory and has to be improved, and (2) the extrapolated interstellar parameters are not indicative of the unperturbed LISM state, but rather designate an intermediate state attained in the outer regions of the solar system. It is shown that a quantitative treatment of the neutral gas-plasma interaction effects in the interface between the heliospheric and the interstellar plasmas is of major importance for the correct understanding of the whole complex.

Fahr, H. J.↗
NASA NTRS1993

The Beta Pictoris circumstellar disk. XV - Highly ionized species near Beta Pictoris

Temporal variations of the Fe II, Mg II, and Al III circumstellar lines towards Beta Pictoris have been detected and monitored since 1985. However, the unusual presence of Al III ions is still puzzling, since the UV stellar flux from an A5V star such as Beta Pic is insufficient to produce such an ion. In order to better define the origin of such a phenomenon, new observations have been carried out to detect faint signatures of other highly ionized species in the short UV wavelength range, where the stellar continuum flux is low. These observations reveal variations not only near the C IV doublet lines, but also in C I and Al II lines, two weakly ionized species, not clearly detectable until now. In the framework of an infalling body scenario, highly ionized species would be created in the tail, far from the comet head, by collisions with ambient gas surrounding the star, or a weak stellar wind. Spectral changes have also been detected near a CO molecular band location, which, if confirmed, would provide the first molecular signature around Beta Pictoris.

Deleuil, M.↗
NASA NTRS2006

A Test of Sensitivity to Convective Transport in a Global Atmospheric CO2 Simulation

Two approximations to convective transport have been implemented in an offline chemistry transport model (CTM) to explore the impact on calculated atmospheric CO2 distributions. GlobalCO2 in the year 2000 is simulated using theCTM driven by assimilated meteorological fields from the NASA s Goddard Earth Observation System Data Assimilation System, Version 4 (GEOS-4). The model simulates atmospheric CO2 by adopting the same CO2 emission inventory and dynamical modules as described in Kawa et al. (convective transport scheme denoted as Conv1). Conv1 approximates the convective transport by using the bulk convective mass fluxes to redistribute trace gases. The alternate approximation, Conv2, partitions fluxes into updraft and downdraft, as well as into entrainment and detrainment, and has potential to yield a more realistic simulation of vertical redistribution through deep convection. Replacing Conv1 by Conv2 results in an overestimate of CO2 over biospheric sink regions. The largest discrepancies result in a CO2 difference of about 7.8 ppm in the July NH boreal forest, which is about 30% of the CO2 seasonality for that area. These differences are compared to those produced by emission scenario variations constrained by the framework of Intergovernmental Panel on Climate Change (IPCC) to account for possible land use change and residual terrestrial CO2 sink. It is shown that the overestimated CO2 driven by Conv2 can be offset by introducing these supplemental emissions.

Bian, H.↗
NASA NTRS2019

A Joint NICER and XMM-Newton View of the "Magnificent" Thermally Emitting X-ray Isolated Neutron Star RX J1605.3+3249

Thermally emitting X-ray isolated neutron stars (NSs) represent excellent targets for testing cooling surface emission and atmosphere models, which are used to infer the physical parameters of the NS. Among the seven known members of this class, RXJ1605.3+3249 is the only one that still lacks confirmation of its spin period. Here we analyze NICER and XMM-Newton observations of RXJ1605.3+3249, in order to address its timing and spectral behavior. Contrary to a previous tentative detection, but in agreement with the recent work by Pires et al., we find no significant pulsation with a pulsed fraction higher than 1.3% (3σ) for periods above 150 ms. We also find a limit of 2.6% for periods above 2 ms, despite searches in different energy bands. The X-ray spectrum can be fit by either a double-blackbody model or by a single-temperature magnetized atmosphere model, both modified by a Gaussian absorption line at ∼0.44 keV. The origin of the absorption feature as a proton cyclotron line or as an atomic transition in the NS atmosphere is discussed. The predictions of the best-fit X-ray models extended to IR, optical, and UV bands, are compared with archival data. Our results are interpreted in the framework of a fallback disk scenario.

Christian Malacaria↗
NASA NTRS2012

Using Game Theoretic Models to Predict Pilot Behavior in NextGen Merging and Landing Scenario

In this paper, we present an implementation of the Semi Network-Form Game framework to predict pilot behavior in a merging and landing scenario. In this scenario, two aircraft are approaching to a freeze horizon with approximately equal distance when they become aware of each other via an ADS-B communication link that will be available in NextGen airspace. Both pilots want to gain advantage over the other by entering the freeze horizon earlier and obtain the first place in landing. They re-adjust their speed accordingly. However, they cannot simply increase their speed to the maximum allowable values since they are concerned with safety, separation distance, effort, possibility of being vectored-off from landing and possibility of violating speed constraints. We present how to model these concerns and the rest of the system using semi network-from game framework. Using this framework, based on certain assumptions on pilot utility functions and on system configuration, we provide estimates of pilot behavior and overall system evolution in time. We also discuss the possible employment of this modeling tool for airspace design optimization. To support this discussion, we provide a case where we investigate the effect of increasing the merging point speed limit on the commanded speed distribution and on the percentage of vectored aircraft.

Yildiz, Yildiray↗
DOE OSTI2021

Advancing a toolkit of diverse futures approaches for global environmental assessments

Global Environmental Assessments (GEAs) support national and international policy making for sustainable development. They rely on quantitative scenarios produced by Integrated Assessment Models (IAMs) to assess alternative futures. IAM-based scenarios can provide a coherent assessment framework that integrates different subsystems and their interactions. However, these top-down approaches have limited ability to represent key local dynamics, unexpected events, or the role of diverse actors. Other methods, including participatory scenarios, can help co-create narratives that emphasize diverse contents with clear links to existing decision-making. However, these bottom-up approaches provide only limited insight into global processes and are not constrained by measurable parameters. In our review, we identify four key challenges for current GEA scenarios: surprise, scale, diversity and imagination. We illustrate how these challenges can be overcome by combining top-down and bottom-up scenario approaches and conclude with a call to action for future research to take on this trans-disciplinary challenge.

Pereira, Laura M.↗
NASA NTRS2011

Optimizing Decision Preparedness by Adapting Scenario Complexity and Automating Scenario Generation

Klein's recognition-primed decision (RPD) framework proposes that experts make decisions by recognizing similarities between current decision situations and previous decision experiences. Unfortunately, military personnel arQ often presented with situations that they have not experienced before. Scenario-based training (S8T) can help mitigate this gap. However, SBT remains a challenging and inefficient training approach. To address these limitations, the authors present an innovative formulation of scenario complexity that contributes to the larger research goal of developing an automated scenario generation system. This system will enable trainees to effectively advance through a variety of increasingly complex decision situations and experiences. By adapting scenario complexities and automating generation, trainees will be provided with a greater variety of appropriately calibrated training events, thus broadening their repositories of experience. Preliminary results from empirical testing (N=24) of the proof-of-concept formula are presented, and future avenues of scenario complexity research are also discussed.

Dunne, Rob↗
DOE OSTI2021

Optimal Decision Making in High-Throughput Virtual Screening Pipelines

ABSTRACT Effective selection of the potential candidates that meet certain conditions in a tremendously large search space has been one of the major concerns in many real-world applications. In addition to the nearly infinitely large search space, rigorous evaluation of a sample based on the reliable experimental or computational platform is often prohibitively expensive, making the screening problem more challenging. In such a case, constructing a high-throughput screening (HTS) pipeline that pre-sifts the samples expected to be potential candidates through the efficient earlier stages, results in a significant amount of savings in resources. However, to the best of our knowledge, despite many successful applications, no one has studied optimal pipeline design or optimal pipeline operations. In this study, we propose two optimization frameworks, applying to most (if not all) screening campaigns involving experimental or/and computational evaluations, for optimally determining the screening thresholds of an HTS pipeline. We validate the proposed frameworks on both analytic and practical scenarios. In particular, we consider the optimal computational campaign for the long non-coding RNA (lncRNA) classification as a practical example. To accomplish this, we built the high-throughput virtual screening (HTVS) pipeline for classifying the lncRNA. The simulation results demonstrate that the proposed frameworks significantly reduce the effective selection cost per potential candidate and make the HTS pipelines less sensitive to their structural variations. In addition to the validation, we provide insights on constructing a better HTS pipeline based on the simulation results.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Developing an Analytical Framework for Cumulative Effects

The extended dry storage scenario for spent nuclear fuel (SNF) in the United States introduces the possibility of more than one transportation campaign to move the SNF from its point of origin to one or more interim storage facilities before it reaches its final destination. While the structural integrity of SNF and its storage and transportation systems are often evaluated under single event loading conditions, the reality is that a single SNF system will experience multiple structural loading events during its life cycle, the number and severity of which will depend on its individual circumstances. SNF systems will also be subjected to environmental exposure that will affect their temperature and the potential for cracks to develop in the SNF canister walls. Considered separately, many different events and scenarios might be strong enough to challenge the integrity of SNF cladding and the storage and transportations canisters that contain SNF. But considered together, over the full life cycle of an SNF system, there is the possibility that individual low-magnitude events could cause enough incremental damage to components of the SNF system to challenge its structural integrity if the time span is long enough or if the life cycle includes a sufficient number of loading events. The concern is that the cumulative effect of relatively small mechanical loads, thermal stresses, or cracking can add up to conditions that could compromise SNF or its containment structures. This report is a first step in establishing an analysis framework for evaluating these cumulative effects.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Optimal management of electric hotel loads in mild hybrid heavy duty truck

Here, the problem of engine idling for heavy-duty trucks has been under study for decades with Auxiliary Power Units (APUs) and Truck Stop Electrification (TSE) as the most compelling solutions. With the electrification of trucks approaching feasibility in terms of cost-effective technology, hybridization offers another “degree of freedom” to tackle the problem. Here, this work aims at exploiting a battery pack of a 48 V mild-hybrid heavy-duty truck to store sufficient onboard energy for powering the auxiliary loads during the hoteling. This problem is not trivial, as the battery packs typically cannot recover the entire energy required through regeneration alone; hence an optimal energy management strategy needs to be employed to charge the battery through the engine during drive operation. This strategy optimizes powertrain performances among the four modes: (i) Engine of Coasting (EOC), (ii) Regeneration by braking, (iii) Regeneration by engine, and (iv) engine idling. This paper presents the development of a Dynamic Programming (DP) framework that employs a multi-objective cost function to minimize the fuel consumption and maximize the regeneration using the above-mentioned four modes. A typical heavy-duty truck drive cycle is used to represent the drive phase, with mandatory hoteling stops as per regulations. A comprehensive powertrain model is developed using validated components’ model. The DP employs two state variables: battery State-of-Charge (SOC) and engine mode, and three control inputs: (i) the engine ON–OFF state, (ii) clutch engagement state, and (iii) power request at the Electric Machine (EM) for calculating optimal SOC trajectory. The framework also tackles rapid engine ON–OFF scenarios to avoid the challenges associated with DP and the compromises in fuel cost with those approaches. Finally, the effectiveness of the proposed framework is tested for potential fuel savings on two different battery packs by performing the full cycle simulations. The results show 6.47% of fuel consumption reduction as compared to traditional APU-based heavy-duty truck.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

Sleptonic SUSY: from UV framework to IR phenomenology

We study an attractive scenario, “Sleptonic SUSY”, which reconciles the 125 GeV Higgs scalar and the non-observation of superpartners thus far with potentially pivotal roles for slepton phenomenology: providing viable ongoing targets for LHC discovery, incorporating a co-annihilation partner for detectable thermal relic dark matter, and capable of mediating the potential muon g – 2 anomaly. This is accomplished by a modestly hierarchical spectrum, with sub-TeV sleptons and electroweakinos and with multi-TeV masses for the other new states. We study new elements in the UV MSSM realization of Sleptonic SUSY based on higher-dimensional sequestering and the synergy between the resulting gaugino-mediation, hypercharge D-term mediation and Higgs-mediation of SUSY-breaking, so as to more fully capture the range of possibilities. This framework stands out by harmoniously solving the flavor, CP and μ – Bμ problems of the supersymmetric paradigm. We discuss its extension to orbifold GUTs, including gauge-coupling and b-tau unification. We also develop a non-minimal model with extra Higgs fields, in which the electroweak vacuum is more readily cosmologically stable against decay to a charge-breaking vacuum, allowing a broader range of sleptonic spectra than in the MSSM alone. We survey the rich set of signals possible at the LHC and future colliders, covering both R-parity conservation and violation, as well as for dark matter detection. While the multi-TeV squarks imply a Little Hierarchy Problem, intriguingly, small changes in parameter space to improve naturalness result in dramatic phase transitions to either electroweak-preservation or charge-breaking. In a Multiverse setting, the modest unnaturalness may then be explained by the “principle of living dangerously”.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Integrated modeling for assessing climate change impacts on water resources and hydropower potential in the Himalayas

Regional hydroclimatic variability and change can affect water resources and hydropower generation. It is essential to assess hydropower potential under current and future climatic conditions to inform the design and operation of hydropower infrastructures. Here, we employ an integrated modeling framework to assess the impact of projected hydroclimatic conditions on water resource systems and hydropower generation. The integrated framework samples climate model outputs under different scenarios to force a hydrologic model and produces streamflow projections. The projected streamflows are inputs for the future hydropower potential assessment. We implement the framework in the central Himalayan river basin. Our results demonstrate substantial spatiotemporal variability in different water balance components (precipitation, evapotranspiration, and water yield) under current and future climatic conditions. For the Himalayan Tila river basin, the annual average energy production is expected to increase under future hydroclimatic conditions (up to 39% in Tila-2 hydropower project, suggested by ensemble mean). Furthermore, this increase in energy is driven mainly by the increased streamflow projections, particularly during the dry season and in the late century. Our results highlight the impacts of hydroclimatic variability in hydropower productions and are of practical use to provide decision-relevant information for designing and operating hydropower infrastructures. The integrated modeling framework presented here is region-specific; however, the approach is reproducible, and the overall insights are generalizable across the Himalayan region.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

A modeling framework for designing and evaluating curbside traffic management policies at Dallas-Fort Worth International Airport

Emerging mobility technologies are changing the transportation system landscape. This is especially evident at airports, such as the Dallas-Fort Worth International Airport (DFW). Without careful analysis, these changes could lead to inefficient and costly airport operations. This paper presents a modeling framework that integrates travel mode encoding, demand projection, and microsimulation to enable airports to develop, simulate, and evaluate curbside traffic managements policies and measure their impact. Here, the framework is utilized to analyze several traffic scenarios and policies for DFW: a baseline scenario which represents DFW traffic pattern as observed in 2018 and projected to 2045, a transit network company (TNC) electrification policy, a TNC queuing policy, a policy that increased transit ridership, a bus-only policy which considers the use of only buses inside DFW, an autonomous vehicle (AV) policy which investigates the impact of autonomous vehicle (AV) adoption on airport operations, and an example COVID-19 scenario which models the impact of the COVID19 pandemic. The simulations’ results demonstrate that: increasing the DFW transit ridership postpones the need for airport curbside expansion the most; encouraging shared-mobility with the bus-only policy produces the most savings in curbside congestion delays; automation and electrification for all passenger vehicle trips to/from DFW generates the most saving in fuel consumption and emissions; and uncontrolled AV adoption incurs the highest increase in fuel consumption, delay, and emissions and could require immediate airport capacity extension. Without policy intervention or investment in additional infrastructure capacity, these results predict the current operations would face significant congestion on high demand days starting as early as 2028. While derived in close partnership with DFW, the methodology presented here can be generalized to any airport.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

A Digital Twin Framework for Liquid-cooled Supercomputers as Demonstrated at Exascale

We present ExaDigiT, an open-source framework for developing comprehensive digital twins of liquid-cooled supercomputers. It integrates three main modules: (1) a resource allocator and power simulator, (2) a transient thermo-fluidic cooling model, and (3) an augmented reality model of the supercomputer and central energy plant. The framework enables the study of "what-if" scenarios, system optimizations, and virtual prototyping of future systems. Using Frontier as a case study, we demonstrate the framework's capabilities by replaying six months of system telemetry for systematic verification and validation. Such a comprehensive analysis of a liquid-cooled exascale supercomputer is the first of its kind. ExaDigiT elucidates complex transient cooling system dynamics, runs synthetic or real workloads, and predicts energy losses due to rectification and voltage conversion. Throughout our paper, we present lessons learned to benefit HPC practitioners developing similar digital twins. We envision the digital twin will be a key enabler for sustainable, energy-efficient supercomputing.

Brewer, Wes↗
DOE OSTI2022

Augmented Gaussian random field: Theory and computation

We propose the novel augmented Gaussian random field (AGRF), which is a universal framework incorporating the data of observable and derivatives of any order. Rigorous theory is established. We prove that under certain conditions, the observable and its derivatives of any order are governed by a single Gaussian random field, which is the aforementioned AGRF. As a corollary, the statement "the derivative of a Gaussian process remains a Gaussian process" is validated, since the derivative is represented by a part of the AGRF. Moreover, a computational method corresponding to the universal AGRF framework is constructed. Both noiseless and noisy scenarios are considered. Formulas of the posterior distributions are deduced in a nice closed form. A significant advantage of our computational method is that the universal AGRF framework provides a natural way to incorporate arbitrary order derivatives and deal with missing data. We use four numerical examples to demonstrate the effectiveness of the computational method. The numerical examples are composite function, damped harmonic oscillator, Korteweg-De Vries equation, and Burgers' equation.

Mathematics↗
DOE OSTI2026

Cybersecurity Center for Offshore Wind Energy (Final Project Report)

This project establishes a Cybersecurity Center for Offshore Wind Energy with the objective of designing and operating a cyber-physical testbed for wind energy farms (WEFs) that enables comprehensive cybersecurity research. The testbed incorporates a Supervisory Control and Data Acquisition (SCADA) system connected to turbine models via industrial-grade programmable logic controllers (PLCs) and remote terminal units (RTUs). It supports side-channel data acquisition, implementation and analysis of various cyberattack scenarios, and development of attack detection, mitigation, and best-practice guidance tailored to wind energy systems. During the project, the team expanded the number and fidelity of mathematical turbine models (MTMs), integrated these models with SCADA infrastructure, and deployed a scaled physical turbine and associated sensors. High-resolution operational and side-channel data streams were collected and used to refine machine-learning (ML)-based attack detection systems and to extend the WindCRAFT framework to multi-turbine threat scenarios. The project demonstrated a realistic, scalable environment for evaluating cyber threats, validated attack detection approaches using enriched datasets, and identified new multi-turbine and inter-turbine communication attack vectors. The resulting testbed, models, and security mechanisms provide a foundation for ongoing R&D and deployment of cyber-resilient offshore wind energy systems.

17 WIND ENERGY↗